Jean-Chrisptohe Burie

Guillaume Demarcq

Ludovic Barusseau

Isabelle Goubet

Karine Salin

Margo Camille

Eliott Noémie

Emilie Arthure

Alexandre

Mélissande

Raph

Yaya

Chouquette, Gauthier, Léa, Laura, Mireia, Lauriane, Mery, Camille Arno

Margot Treden

Baptiste, La Reine Marc

Anais Mère

Anais Claire

Manu, Mathieu, Pascaline, Clément, Aurélie, Marine, Antoine, Kévin, Lucie Natascha

Magalie J R Raphael

Yann

Anne Laure, Le Pti Nico

Aurélien, Lorette, Vicky, Seboules, Nico, Cloé, Morgane, Greg Charlie Lahlafi

Vivi Toanui

Ugo Lopes

Océane Lebon

L'écriture des remerciements n'est pas un exercice facile, car il m'est impossible de trouver les mots suffisants pour exprimer pleinement mon ressenti. De plus, je ne voudrais omettre aucune des personnes qui ont compté pour moi dans mon parcours : Amis, collègues, rencontres, si vous n'êtes pas dans ces quelques lignes vous êtes tout de même dans mon coeur.

Je tiens tout d'abord à remercier mes encadrantes Laurence Murillo et Isabelle Brenon. Merci d'avoir cru en moi et de m'avoir permis de participer à ce super projet avec vous. Merci pour votre soutien, votre prévenance, votre bienveillance, votre gentillesse et votre humanité ! Un immense merci à vous ! Je tiens à remercier tout particulièrement les rapporteurs Amélie Châtel et Romaric Verney, ainsi que les examinateurs de ma thèse Marianne Graber, Jean-Marc Lebel, Laurent Barillé et Frédéric Olivier. Je vous remercie pour le temps que vous m'avez accordé, pour la richesse des échanges scientifiques et pour les nombreux conseils que vous m'avez prodigués.

Je souhaite ensuite remercier sincèrement l'ensemble des mes collaborateurs, notamment le Port de plaisance de la Rochelle. Un grand merci à Bertrand Moquay, Angélique Fontanaud, Adeline Thomassin, Pierre Rideau et à tous les acteurs du port des Minimes. Merci de m'avoir permis d'expérimenter dans ce splendide environnement. Merci pour tout le temps que vous m'avez accordé et pour la richesse de nos échanges.

J'aimerais remercier également le

Liste des figures et des tables (hors publication)

Les interactions permettent de lier les composants de l'écosystème et ont lieu entre les acteurs de la biocénose, entre les facteurs du biotope et entre le biotope et la biocénose. Les interactions au sein de la biocénose sont souvent classées en fonction des effets qu'elles occasionnent sur les organismes (Figure 2) mais les interactions au sein du biotope et entre le biotope et la biocénose sont difficile à définir tant elles sont nombreuses et diverses. L'Homme est souvent peu pris en compte dans les études écosystémiques. Pourtant la pression qu'exerce l'être humain sur son environnement fait qu'il est aujourd'hui considéré comme l'une des principales forces qui gouverne l'état, le fonctionnement et l'évolution de la planète [START_REF] Steffen | The Anthropocene: conceptual and historical perspectives[END_REF]. En effet l'ampleur de la résultante des actions anthropiques (perte de biodiversité, changement climatique, érosion des sols, etc.) font que l'Homme rivalise avec certaines des grandes forces de la nature [START_REF] Steffen | The Anthropocene: conceptual and historical perspectives[END_REF]. Certains scientifiques considèrent même qu'une nouvelle ère géologique, est amorcée depuis l'intensification des activités humaines à la révolution industrielle et que celle-ci se caractérise par la dominance des activités humaines sur l'ensemble des autres processus géologiques [START_REF] Crutzen | Geology of mankind[END_REF][START_REF] Steffen | The Anthropocene: are humans now overwhelming the great forces of nature[END_REF][START_REF] Steffen | The Anthropocene: conceptual and historical perspectives[END_REF]. Le terme « Anthropocène » est proposé par Paul Crutzen en 2002 pour qualifier cette nouvelle ère et conceptualiser la prise de conscience de la place de l'Homme dans l'écologie actuelle et l'impact de ses activités sur le fonctionnement des écosystèmes [START_REF] Crutzen | Geology of mankind[END_REF].

Même si ce concept est discuté, les impacts d'origine anthropique sur les milieux ne sont pas négligeables. Les conséquences des activités humaines ont d'ores et déjà été mises en évidence par la communauté scientifique : l'augmentation de la température des océans et leur acidification [START_REF] Raven | Ocean acidification due to increasing atmospheric carbon dioxide[END_REF][START_REF] Hoegh-Guldberg | The Impact of Climate Change on the World's Marine Ecosystems[END_REF] sont des exemples frappant de l'influence de l'Homme sur cet environnement.

Afin de réintégrer l'Homme dans les études écosystémiques comme une composante active du système et non plus comme un simple observateur, le concept de socio-écosystèmes ou système socio-écologique est proposé par une partie de la communauté scientifique [START_REF] Walker | Resilience, adaptability, and transformability in social -ecological systems[END_REF][START_REF] Folke | Social-ecological systems and adaptive governance of the commons[END_REF][START_REF] Lagadeuc | Les systèmes socio-écologiques : vers une approche spatiale et temporelle[END_REF][START_REF] Ostrom | A general framework for analyzing sustainability of social-ecological systems[END_REF]. Dans ce concept, l'Homme fait partie intégrante de la biocénose au même titre que les autres organismes et les facteurs anthropiques enrichissent ou redéfinissent les biotopes. Cette approche moderne permet de recentrer les recherches sur des problématiques actuelles, en partant du postulat que pour de nombreux environnements l'Homme et les facteurs anthropiques qu'il occasionne doivent être pris en compte. Considérer l'Homme comme un simple acteur limite les jugements de valeur à lui conférer : l'Homme n'est ni une nuisance, ni audessus du socio-écosystème, il en fait simplement partie.

Les littoraux sont des milieux à l'interface entre le continent et l'océan. Ils sont des points chauds de biodiversité et servent de refuge et de nourricerie à de nombreux organismes marins. Ils sont également le lieu d'une activité humaine importante, ce qui en fait de bons exemples d'écosystèmes où l'on ne peut soustraire l'action de l'Homme. Aujourd'hui, plus de 20 % de la population mondiale vit à moins de 30 km des côtes et 60 %, soit près de 3,8 milliards d'individus, à moins de 150 km, dans la grande zone côtière (Small and Nicholls, 2003 ;Béoutis et al., 2006). Certaines projections démographiques prévoient que plus de 75 % de la population mondiale vivra aux abords des côtes d'ici 2035 [START_REF] Haslett | Coastal systems[END_REF].

Les interactions entre l'Homme, les facteurs anthropiques et ces environnements sont multiples et proviennent de sources diverses. Ils sont liés tant à l'exploitation directe de ces milieux (pêche, nautisme, aménagement touristique etc.) qu'à des facteurs plus indirects liés au ruissellement des eaux de pluie par exemple (Figure 3) [START_REF] Groom | Principles of conservation biology Ed[END_REF][START_REF] Amara | Impact de l'anthropisation sur la biodiversité et le fonctionnement des écosystèmes marins. Exemple de la Manche-mer du nord[END_REF]Le Berre & Robert, 2017). [START_REF] Groom | Principles of conservation biology Ed[END_REF]. rejets dans l'environnent marin sont notamment légiférés par la Directive Cadre sur l'Eau (Le parlement européen et le conseil de l'union européennes, 2000). La Directive Cadre sur l'Eau (DCE) définit un cadre légal et méthodologique pour la hiérarchisation et le suivi des substances polluantes pour les milieux aquatiques. Les dernières directives de la DCE (2016-2021) prévoient de réaliser ou de maintenir un bon état écologique et chimique des eaux littorales en se basant notamment sur le suivi de contaminants considérés comme prioritaires ; soit des polluants industriels, des pesticides et des éléments traces métalliques (Le parlement européen et le conseil de l'union européennes, 2000).

Les éléments traces métalliques désignent indistinctement les métaux et les metalloïdes. Neuf d'entre eux (le cadmium (Cd), le plomb (Pb), le mercure (Hg), l'arsenic (As), le nickel (Ni), le chrome (Cr), le sélénium (Se), le cuivre (Cu) et le zinc (Zn) sont considérés à risque pour la santé humaine par le rapport 42 de l'Académie des Sciences (1998) et font l'objet d'une surveillance accrue dans l'environnement (Académie des sciences, 1998 ; [START_REF] Burnol | Recommandation pour la modélisation des transfert métalliques dans les sols et les eaux souterraines[END_REF]. Les ports en France sont également soumis au contrôle de leur présence dans les rejets de dragage selon la Circulaire N°2000-62 du 14 juin 2000 [START_REF] Hayet | DeramContexte et cadre réglementaire de la gestion des sédiments de dragage[END_REF].

La régie du port de plaisance de La Rochelle, dans une démarche écoresponsable, réalise en plus du suivi lié au cadre législatif, un suivi tout particulier des contaminants de ses eaux. Cette démarche lui a valu notamment plusieurs certifications ou normes internationales environnementales telles que les certifications ISO 14001 et Qualité 9001. Les rejets vers le milieu naturel et les zones de carénage du port de plaisance de La Rochelle font l'objet d'un suivi régulier. Au total huit éléments traces (As, Cd, Cr, Cu, Pb, Zn, Ni, Hg), une quantification des métaux toxique totaux et un indice d'hydrocarbure sont régulièrement analysés (CREOCEAN, 2018).

Le suivi de 16 contaminants dans une partie de la composante biotique (les bivalves) du port a également été effectué, à travers les travaux de thèse de Marine [START_REF] Breitwieser | What is the relationship between the bioaccumulation of chemical contaminants in the variegated scallop Mimachlamys varia and its health status? A study carried out on the French Atlantic coast using the Path ComDim model[END_REF]Breitwieser ( -2018)). Ces travaux en relation avec le projet DYnamiques POrtuaires, Milieux urbains et environnement MARitime (DYPOMAR) ont permis de suivre la présence de 14 éléments traces, d'hydrocarbures aromatiques polycycliques (HAP) et de polychlorobiphényles (PCB), dans les tissus des 3 bivalves (Mytilus edulis, Crassostrea gigas, Mimachlamys varia). Ils ont également permis d'identifier des biomarqueurs pertinents pour identifier la présence de ces éléments dans les organismes. Le projet DYPOMAR débuté en 2012 est un projet pluridisciplinaire collaboratif, entre les instances politiques, les autorités du port des Minimes et La Rochelle Université, visant à augmenter les connaissances relatives à l'environnement portuaire.

Les ports sont particulièrement soumis à la présence des éléments traces métalliques. Ces éléments proviennent de la dégradation des éléments de construction (structure métallique, coque en aluminium, etc.), des éléments de protections contre la corrosion et contre la présence d'organisme indésirable (anode sacrificielle, peinture antifouling), des activités nautiques (carburant, huile, etc.) mais aussi par leur localisation aux abords des côtes qui les conduit à recueillir les eaux de ruissellement (Galkus et al., 2012 ;Eklund and Eklund, 2014 ;Brignon and Gouzy, 2014 ;Bighiu et al., 2017). De plus, les ports sont faits de manière à limiter l'effet des vagues et des courants ce qui tend à amplifier les concentrations de ces éléments piégés dans ce milieu semi-fermé (Huguet et al., 2019 ;Sim et al., 2015).

Lors d'un relevé effectué en 2018, dans l'eau du port de plaisance de La Rochelle, le cuivre et le zinc étaient les éléments traces présentant les plus fortes concentrations respectivement 82 μg/L et 157 μg/L (CREOCEAN, 2018).

Le cuivre et le zinc, comme beaucoup d'autres éléments traces, ont des effets paradoxaux sur les organismes. Ils sont à la fois nécessaires à de nombreuses activités métaboliques et deviennent toxiques lorsqu'ils sont présents à des niveaux trop élevés (Olivares and Uauy 1996 ;[START_REF] Salgueiro | Zinc as an essential micronutrient: a review[END_REF][START_REF] Frassinetti | The role of zinc in life: a review[END_REF]. Le cuivre et le zinc sont notamment des cofacteurs essentiels pour de nombreuses enzymes (Olivares and Uauy 1996 ;King, 2011, Lontie, 2018). Le cuivre est également nécessaire au transport de l'oxygène dans l'hémolymphe de nombreux crustacés et bivalves (Holde et al., 2001 ;Gianazza et al., 2021). De même, le zinc joue un rôle important dans les réponses immunitaires, la division cellulaire et la régulation de la transcription de l'ADN [START_REF] Salgueiro | Zinc as an essential micronutrient: a review[END_REF]. Cependant, dans certaines conditions, le cuivre et le zinc peuvent nuire à l'activité enzymatique, à la défense antioxydants, à la croissance larvaire et même être létaux [START_REF] Jorge | Use of sodium dodecyl sulfate and zinc sulfate as reference substances for toxicity tests with the mussel Perna perna (Linnaeus, 1758) (Mollusca: Bivalvia)[END_REF]Mesquita et al., 2019).

I.II.II. L'envasement portuaire

Les sédiments ont été définis par [START_REF] Foucault | Dictionnaire de géologie[END_REF] comme « un ensemble constitué par la réunion de particules plus ou moins grosses ou de matières précipitées ayant, séparément, subi un certain transport ». Ces particules proviennent de l'érosion des sols et des roches, de matériaux détritiques organiques ainsi que des rejets locaux dus à l'activité humaine [START_REF] Dubois | Étude du comportement physico-mécanique et caractérisation environnementale des sédiments marins-Valorisation en technique routière[END_REF]. Elles sont ensuite transportées jusqu'au milieu marin par voie atmosphérique et par les cours d'eau. Le sédiment est une matrice très hétérogène, constitué d'eau interstitielle qui occupe l'espace entre les particules, d'une phase minérale (argiles, carbonate et silicates) et d'une phase organique [START_REF] Power | Assessing sediment quality[END_REF]. Ils sont classés selon la taille des particules qui les composent. Quand les particules sont fines (<63 µm) et cohésives elles forment des vases en sédimentant [START_REF] Van Leussen | Aggregation of particles, settling velocity of mud flocs a review[END_REF]Droppo, 2003;[START_REF] Bellair | Éléments de géologie[END_REF].

La problématique de l'envasement est au coeur de l'environnement portuaire. Pour permettre de naviguer en toute sécurité, les ports doivent avoir une hauteur d'eau suffisante. Les structures telles que les pontons, les pilotis et les digues entravent la circulation de l'eau et des sédiments et ont tendance à augmenter la sédimentation (Van Maren et al., 2009;Van Rijn, 2016;Huguet et al., 2020). Les sédiments ainsi piégés doivent être évacués pour ne pas impacter les activités nautiques. Le coût de ces opérations a été estimé à 2,5 milliards d'euros dans le monde en 2011 (IADC, 2011).

L'entretien du port des Minimes est effectué 8 mois par an et coûte près de 2 millions d'euros (Direction départementale des Territoires et de la Mer de la Charente-Maritime, 2018). En 2020, le port de plaisance estime par exemple avoir évacué par dragage et remis en suspension respectivement 219 450 m 3 et 8 000m 3 de vase (Port de plaisance de La Rochelle, 2021).

La compréhension des facteurs qui régissent le comportement des vases est un enjeu majeur pour les autorités portuaires, afin d'optimiser et de limiter les opérations d'entretien. D'autant que la distribution (Figure 7) et la qualité (structure et texture) des vases sont hétérogènes au sein de l'environnement portuaire (Huguet et al., 2020; Port de plaisance de La Rochelle, 2021). Dans cette optique une collaboration est menée entre le port de plaisance de la Rochelle et la Rochelle Université. Cette collaboration a permis notamment à travers les travaux de thèse de Jean-Rémy Huguet (2016Huguet ( -2019) ) d'étudier, expérimentalement et par modélisation, une partie des caractéristiques hydrodynamique et hydrosédimentaire du port des Minimes.

Les études hydrodynamiques et hydrosédimentaires permettent d'appréhender les paramètres physico-chimiques responsables de la composition et du comportement des vases.

I.II.II.I. Les caractéristiques hydrodynamiques de la zone d'étude

Les caractéristiques hydrodynamiques du Port de plaisance de La Rochelle ont été étudiées par Jean-Remy Huguet dans le cadre de sa thèse (2019) (Figure 8). Il démontre que les facteurs influençant majoritairement ces flux, outre les structures portuaires (les pontons, digues, …) sont : les vagues, les vents, les courants et les marées.

Figure 8. Modélisation de la vitesse moyenne en profondeur (m/s) générée, en présence de ponton, par un courant de flot (A), à marée haute (B), par un courant de jusant (C), à marée basse (D) (D'après Huguet, 2019).

A B C D

Le phénomène de marée est dû à deux forces : la force d'attraction gravitationnelle exercée sur la Terre par la Lune et le Soleil, et la force centrifuge provoquée par la rotation de la Terre sur ellemême. Le mouvement de rotation de la Lune autour de la Terre (environ 28 jours) entraine des variations de hauteur d'eau. Ainsi lorsque le Soleil, la lune et la Terre sont alignés (durant les phases de nouvelle et pleine lune appelées syzygies), les forces s'additionnent et le marnage atteint un maxima (ce sont les vives eaux). A l'inverse, lorsque le Soleil, la Lune et la Terre forme un angle droit (lorsque la lune en est à ses premiers et derniers quartiers appelés quadratures), l'amplitude des marées passent par un minimum (ce sont les mortes eaux). Dans les Pertuis Charentais, le type des marées est semi-diurne, on observe deux pleines mers (PM) et deux basses mers (BM) par jour [START_REF] Nicolle | Modélisation des marées et des surcotes dans les Pertuis Charentais[END_REF]. L'onde M2 est la composante principale de la marée dans les Pertuis Charentais, son amplitude atteint 177 centimètres dans le Port des Minimes et est amplifiée lorsque la profondeur diminue (Poincaré, 1910;[START_REF] Nicolle | Modélisation des marées et des surcotes dans les Pertuis Charentais[END_REF]. Les amplitudes et les phases des principales ondes de marées enregistré à la Pallice (point de référence du pertuis charentais) sont présentées dans la table 1 [START_REF] Nicolle | Modélisation des marées et des surcotes dans les Pertuis Charentais[END_REF]. Les ondes diurnes (O1 et K1) ont une amplitude faible (O1 + K1 = 14 cm) et ne représente que 6% des amplitudes des ondes semi-diurnes (M2 +S2 = 2.34 m). L'onde M4 (quart-diurne) est très importante et atteint 27 cm. Ces amplitudes sont caractéristiques des Pertuis Charentais, et engendre des marées asymétriques (la mer monte plus lentement qu'elle ne descend) [START_REF] Nicolle | Modélisation des marées et des surcotes dans les Pertuis Charentais[END_REF].

Dans le chenal d'accès au port de plaisance, les courants de marée sont dirigés Ouest/Sud-Ouest à marée descendante et Est/Nord-Est à marée montante. Leur vitesse est faible dans le port de plaisance de la Rochelle et ne dépasse pas 0,31m/s en vives eaux [START_REF] Creocean | Etude des conditions naturelles en vue de l'extension du port des Minimes[END_REF].

Le vent est un facteur climatique important de la dynamique océanique, il est notamment à l'origine du phénomène de houle (qui dépend de la vitesse du vent mais aussi de sa durée). Les vents dominants et les plus fortes houles du pertuis charentais proviennent de l'Ouest [START_REF] Bertin | Longshore transport estimation and inter-annual variability at a high-energy dissipative beach: St. Trojan beach, SW Oléron Island, France[END_REF].

Dans les Pertuis Charentais, l'amplitude moyenne annuelle des vagues est de 1,5 mètres. Néanmoins, l'amplitude des vagues varie en fonction des saisons, et peut dépasser les 8 mètres lors de tempêtes hivernales [START_REF] Bertin | The contribution of short-waves in storm surges: Two case studies in the Bay of Biscay[END_REF][START_REF] Dodet | Wave climate variability in the North-East Atlantic Ocean over the last six decades[END_REF].

I.II.II.II. Les caractéristiques hydro-sédimentaires de la zone d'étude

Les caractéristiques hydro-sédimentaires du port de plaisance de La Rochelle, ont été décrites et modélisées par Huguet et al., (2020). Des mesures in situ ont permis de mettre en évidence les principaux facteurs été influençant ces flux (Huguet et al., 2020) : les marées, les vents et les vagues (voir partie I.II.II.I). Le taux de sédiments moyen en suspension dans la colonne d'eau est marqué par l'alternance morte eaux vive eaux (Figure 9).

Les concentrations sédimentaires sont hétérogènes entre les quatre bassins du port de Minimes (Figure 9 Outre les apports maritimes de sédiments, les Pertuis Charentais sont soumis à des apports provenant de six principaux fleuves côtiers (Figure 10) : le Lay, la Sèvre Niortaise, le Curé, la Charente, La Seudre et l'estuaire de la Gironde (Garonne et Dordogne). C'est la Charente qui contribue le plus aux apports terrigènes du Pertuis d'Antioche (Soletchnick et al. 2014).

Les fonds marins des Pertuis Charentais sont constitués de vasières infralittorales [START_REF] Natura | Connaissance et gestion des habitas et des espèces d'intérêt communautaire, Tome 2-habitats côtiers[END_REF][START_REF] Natura | Connaissance et gestion des habitas et des espèces d'intérêt communautaire, Tome 2-habitats côtiers[END_REF]. Les sédiments rencontrés dans le port de plaisance de la Rochelle sont comparables à ceux de la Charente et sont principalement vaseux cohésifs. Leur composition est relativement homogène, est constituée en grande partie de particules fines inférieures à 0,63µm. Ces sédiments sont constitués d'une part de matière organique relativement importante. Les bivalves, ou lamellibranches, sont des mollusques dont le corps est protégé par une coquille composée de deux valves (symétriques ou non) articulées. Ces deux valves sont reliées par une charnière (composée de ligaments) et d'un muscle adducteur qui assure la fermeture de la coquille mais aussi le contrôle de l'entrebâillement des valves afin de permettre le passage d'eau pour l'oxygénation et l'alimentation de l'animal (Gosling, 2015).

Certains bivalves vivent fixés à des rochers ou à des structures immergées, comme les huîtres (en y cimentant leur valve), ou les pétoncles et les moules (en s'y attachant à l'aide de leur byssus) : ce sont des espèces dites sessiles.

Les éléments traces métalliques (Zn, Cd, Cr, Se) quant à eux, pourraient provoquer une réduction de la filtration chez des organismes comme Perna viridis, Septifer virgatus et Ruditapes phillipinarum [START_REF] Wang | Comparison of metal uptake rate and absorption efficiency in marine bivalves[END_REF].

Les quantités de fèces et pseudofèces rejetées par les bivalves peuvent aussi varier en fonction des conditions environnementales. L'huître et la moule, par exemple augmentent la proportion de pseudofèces dans leurs rejets quand la charge particulaire de l'environnement est élevée [START_REF] Haven | Aspects of biodeposition by oysters and other invertebrate filter feeders 1[END_REF][START_REF] Foster-Smith | The effect of concentration of suspension on the filtration rates and pseudofaecal production for Mytilus edulis L., Cerastoderma edule (L.) and Venerupis pullastra (Montagu)[END_REF]Sornin et al., 1983).

I.III.I.II. Les tuniciers

Les tuniciers les plus communément rencontrés dans le port de plaisance de la Rochelle sont les Ascidiacea (ascidie), avec comme espèces principales : Ciona intestinalis (Linnaeus, 1767), Clavelina sp (Müller, 1776) et Botryllus sp (Gaertner, 1774) (Figure 13). Les ascidies ont un régime alimentaire suspensivore, elles se nourrissent de particules organiques et de micro-organismes planctoniques (Holland, 2016). Elles sont entourées d'une tunique de nature cellulosique sécrétée par l'animal. Cette tunique comporte deux ouvertures, appelées « siphons ». L'un situé au sommet de l'ascidie (le siphon inhalant), permet l'entrée d'eau de mer et limite le passage des grosses particules et l'autre (le siphon exhalant) permet d'éliminer les rejets (Holland, 2016) (Figure14). Les ascidies ont également des branchies qui assurent des fonctions alimentaire et respiratoire (Figure 14).

I.III.II. Fonctions écosystémiques

De par leur mode de vie, les filtreurs (bivalves et tuniciers) ont une forte interaction avec leur environnement. En effet, en restant ancrés aux structures, ils sont constamment soumis aux facteurs environnementaux qui caractérisent le port. De plus, leur comportement alimentaire, la filtration, les amène à être en contact avec une grande quantité d'eau chargée de divers éléments (nourriture, éléments traces, sédiments etc.).

Ce mode de vie, leur capacité à accumuler certains éléments traces et leur sensibilité en font de bons bio-indicateurs (Papdopoulou and Kanias, 1977 ;Philips, 1977 ;Fred, 2019). Les huîtres (Crassostrea gigas) et les moules (Mytilus edulis) sont à ce titre utilisées par l'Ifremer, dans le cadre du réseau de surveillance ROCCH (ex RNO), pour suivre l'évolution de certains de ces éléments traces (argent, cadmium, chrome, cuivre, mercure, nickel, plomb, zinc et vanadium). Les pétoncles panachés (Mimachlamys varia) ont également été proposés comme modèle de biosurveillance écotoxicologique des milieux marins, notamment dans le port de plaisance de la Rochelle (Milinkovitch et al., 2015 ;Breitwieser et al., 2018 ;Breitwieser et al., 2020). Il en va de même pour les tuniciers tels que Microcosmus sulcatus et Ciona intestinalis qui sont proposés par Papadopoulou et Kanias (1977) pour surveiller la présence d'éléments traces dans l'environnement marin en raison de leur capacité à les bioaccumuler.

Les bivalves et les tuniciers sont également des espèces dites « ingénieures ». Leur présence modifie significativement l'environnement et crée de nouveaux habitats. En effet, ces organismes forment des couvertures très denses en recouvrant l'ensemble des parties immergées des pontons et des pylônes. Cette masse vivante permet à d'autres espèces plus petites de s'y réfugier (Jones et al., 1994 ;Gutierrez et al., 2003 ;Strain et al., 2020).

Ces organismes jouent également un rôle dans la formation des vases. Comme vu précédemment, les sédiments aspirés par ces filtreurs sont regroupés lors de la digestion dans les fèces ou en amont, par le mucus, dans les pseudofèces et sont rejetés. Ces rejets, appelés bioproduits, vont sédimenter plus efficacement et augmenter la quantité de vase environnante. Des études menées autour des activités conchylicoles (ostréicole et mytilicole), montrent que les moules, les huîtres et les tuniciers ont un impact sur la vitesse de sédimentation des particules en suspension mais aussi sur la distribution, la structure et la composition des vases environnantes (McKindsey et al., 2011 ;Walker et al., 2014 ;Wang et al., 2018).

Le mode d'alimentation des filtreurs et leur propension à bioaccumuler des contaminants font de ces organismes des modèles phares de l'éco-engineering. Ils permettraient, selon plusieurs études, de dépolluer leurs environnements en captant et en accumulant des polluants présents dans la colonne d'eau comme les métaux notamment (Kim et al., 2017 ;McCann, 2018 ;Vozzo et al., 2021).

I.IV. Positionnement des travaux et objectifs de thèse

Les travaux présentés ici ont pour objectif d'étudier l'écosystème du port de plaisance de La Rochelle, communément appelé port des Minimes.

L'étude d'un écosystème est complexe tant les possibilités d'approche sont grandes. J'ai ainsi choisi de limiter mes recherches sur des acteurs omniprésents et ayant des interactions fortes avec leur environnement : les organismes filtreurs, bivalves et tuniciers.

L'Homme étant au coeur de cet écosystème qu'il a lui-même bâti, j'ai concentré mes recherches sur les interactions entre ces organismes et les facteurs d'intérêt sociétaux les plus étudiés en relation avec cet environnement, à savoir les contaminants d'origine anthropique (et plus particulièrement les éléments traces) et l'envasement.

Les travaux de cette thèse s'organisent autour de trois axes principaux. Le premier vise à connaître les communautés de filtreurs présentes sous les pontons et à étudier ce qui les structure. Le second a pour but d'étudier l'effet des éléments traces sur leurs métabolismes. Le dernier tend à mettre en évidence le rôle des filtreurs dans la composition et le comportement des vases. (Figure 15)

Chapitre II

Les communautés d'organismes filtreurs, bivalve et tunicier, dans l'environnement portuaire

Il difficile d'imaginer de la vie dans ces écosystèmes fortement anthropisés que sont les ports. Cependant lorsque l'on regarde sous les pontons on remarque que chaque centimètre carré de structure disponible est colonisé (Figure 16). Les recensements ont été menés à deux reprises (2019 et 2020) à l'aide de photographie sousmarine pour ne pas endommager les espèces présentes. Les distributions ont ensuite été cartographiées et comparées, par espèce, par année, par bassin et par ponton.

Une estimation précise des populations nécessite un très grand nombre de données. L'utilisation d'une méthode pour automatiser l'analyse des photographies est alors devenue nécessaire. L'intelligence artificiel (AI) semble être l'outil idéal pour cela, comme le montrent plusieurs II.I. What is hidden under our pontoons? Abundance and distribution of filter feeders (bivalves and tunicates) in the port area revealed. Artificial intelligence: an interesting analysis tool?

II.I.I. Introduction

Coastal environments are biodiversity hotspots and provide refuge, food and nursery for many organisms (Henseler et al., 2019). They are also the site of significant human activity. Today, more than 20% of the world's population lives within 30 km of the coast and 60%, or nearly 3.8 billion, live within 150 km in the greater coastal zone (Small and Nicholls, 2003;Béoutis et al., 2009). This hyperanthropisation has significantly changed coastal ecosystems (Le Berre & Robert, 2017). More and more structures, such as ports, are emerging and establishing new ecosystems in their own right. In these highly anthropised environments, life seem to have no place. However, significant communities grow, out of sight, protected by the maze of pontoons that the port ecosystem offers (Connell & Glasby, 1999;Glasby, 1999;Connell, 2000).

Studies in Sydney's harbor (Australia) show that the abundance and diversity of subtidal epibiota is even increased by the presence of structures such as pontoons and pilings (Connell & Glasby, 1999;Connell, 2000). These structures offer new habitats that are easily colonizable by epibiota species such as mussels, ascidians, bryozoans, hydroids and sponges (Connell & Glasby, 1999;Connell, 2000). As Connell (2000) highlights, ports are indeed ecosystems in their own right because the communities present on their structures are not comparable to those present in the surrounding areas.

La Rochelle marina (France) is the largest marina in Europe with 70 hectares and some 5,000 moorings spread over more than 60 pontoons. This makes it an ideal study site for studying port's ecosystems.

Among the multitude of species that inhabit this marina, three groups seem particularly abundant: bivalves, tunicates and bryozoans. Indeed, after numerous scientific dives and several samples taken in La Rochelle marina, bivalves (mainly: Mytilus edulis (Linnaeus, 1758), Modiolus barbatus (Linnaeus, 1758), Crassostrea gigas (Thunberg, 1793) and Mimachlamys varia (Linnaeus, 1758)), tunicates (mainly: Ciona intestinalis (Linnaeus, 1767) and Clavelina sp (Müller, 1776)) and bryozoans (mainly: Bugula sp (Oken, 1815)) seem to cover every square centimeter of pontoon. These organisms, known as filter feeders, have the particularity of filtering water from the environment in order to extract their food and live anchored to their substrates for part of their lives. Because of their way of life, these filter feeders have a strong interaction with their environment, which makes them particularly interesting to study. Indeed, by remaining anchored to the structures, they are constantly subjected to the environmental factors that characterize the port (anthropogenic or not) and their feeding behavior leads them to be in contact with a large quantity of water charged with various elements (food, trace elements, sediments etc.).

This way of life makes them good bioindicators, especially because some species such as scallops are sensitive and have a high bioaccumulation potential towards trace elements (Ag, As, Cd, Co, Cr, Cu, Fe, Mn, Ni, Pb, Se, Sn, V and Zn) very present in port areas (Breitwieser, 2017). Therefore, scallops (Mimachlamys varia) and oysters (Crassostrea gigas) are used as an ecotoxicological biomonitoring model for marine environments, especially in La Rochelle marina (Bustamante et al., 2005;Milinkovitch et al., 2015;Breitwieser et al., 2018;Breitwieser et al., 2020).

Their feeding behavior, their propensity to bioaccumulate and their potential as engineer species make these filter feeders key models for eco-engineering. According to several studies, they can clean up their environments by capturing and accumulating pollutants, particularly trace elements, present in the water column (Kim et al., 2017;McCann and May, 2018;Vozzo et al., 2021). A project called the "Billion Oyster Project" was initiated in 2014 in New York. This project aims to reduce trace elements such as mercury in New York port through the filtration and bioaccumulation of oysters (Kim et al., 2017;McCann and May, 2018). Bivalves are also used to improve the ecological value of artificial structures (Bradford et al., 2020;Strain et al., 2018). These engineer species provide habitats for other mobile invertebrates and are a food source for many predators (Gutiérrez et al., 2003;Bradford et al., 2020;Strain et al., 2018). Bradford et al., (2020) show by seeding Saccostrea cuccullata oysters that their presence on artificial structures significantly increases their specific richness.

These organisms are all the more interesting to study because their feeding behavior leads them to be in contact with part of the sediments present in the water column. The sediments sucked up by these filter feeders are grouped during digestion in the faeces or upstream by the mucus in the pseudo-faeces. These rejects, called bioproducts, are involved in the composition of the mud (Walker et al., 2014;Zúñiga et al., 2014;Hamani et al., 2021). An experimental study conducted in La Rochelle marina shows that on the scale of this port (70ha) these organisms would be able to reject approximately 3.2 tons of bioproducts per day (Hamani et al., 2021). Studies carried out on oyster and mussel farms show that organisms such as mussels, oysters and tunicates have an impact on the quantity of surrounding mud, the sedimentation rate of suspended particles, the distribution, structure and composition of the mud (McKindsey et al., 2011;Walker et al., 2014;Wang et al., 2018). These organisms are therefore not to be neglected in an environment, such as ports, where the mud must be regularly dredged to allow navigation.

With all involvements previously explained, bivalves and tunicates appear to be key actors of port ecosystem. Then, to better understand the port environment, it seems important to know the current state of their populations and what conditions them. However, to our knowledge, no recent study has defined the state of their populations in port environments.

The objective of the present study is to investigate the abundance and distribution of filter feeders (bivalves and tunicates) in Europe's largest marina, while proving an innovative recognition method: artificial intelligence (AI) image analysis.

This study was carried out in a particular context: the first sampling campaign was carried out in June 2019, i.e. one year before the sanitary crisis caused by COVID-19, and the second campaign in June 2020, i.e. one month after the crisis. During this sanitary crisis, a total confinement, including a ban on navigation, was applied from March to May 2020, strongly reducing anthropic pressure on the study area (portlarochelle.com, 2020a, b, c). This study thus provides an overview of the effect of a major change in anthropogenic activity on model communities such as bivalves and tunicates.

In order to apply a non-destructive sampling method that is repeatable from year to year, the population survey was carried out using underwater photography. In a port of 70 hectares like La Rochelle marina, an efficient estimation of the populations requires a very large amount of data, especially if we want to include a time scale in our censuses. The automation of the analysis of photos has therefore become necessary. Artificial intelligence (AI) seems to be the ideal tool for this. Several studies, notably on coral reefs, show the relevance of this tool for detecting and identifying species in large image sets (Gonzalez-Rivero et al., 2020;Hamylton et al., 2020;Nunes et al., 2020). Gonzalez-Rivero et al. (2020) even state that when the computer has learned, the AI identifies corals 200 times faster than an operator and is much less expensive. This tool would therefore seem to be ideal for establishing regular, long-term monitoring of bivalves and tunicates in La Rochelle marina. However, ports are very dynamic environments and the turbidity of the water and therefore the quality of the photos can change quickly. In addition, the diversity of shape and the complexity of the entanglements that individuals may have under the pontoons should not be neglected. To ensure that the AI was able to overcome these difficulties and to prove its relevance, we propose here to present the first results of the survey of bivalves and tunicates carried out by an operator in La Rochelle marina and to compare them with those obtained by the AI. To ensure the quality of the abundance estimates, 27 collections of organisms were carried out in 2019 and 36 in 2020, i.e., 9 per basin (3 per pontoon on 3 separate pontoons). To carry out these collections, a floating quadra of 0.64m 2 was placed under the pontoon and all the organisms found there were collected by a scientific diver and then counted. This census was made possible to estimate the size of the bivalves (Width*Length*Height). Before each collection, photos of the area were taken to evaluate and correct the analysis method.

The collections of organisms allowed to formally estimate the number of individuals. As the organisms are entangled, the estimation by photo tends to underestimate their density (Table 1). In order to improve the estimates obtained by the photographic analysis, a corrective factor relating to the average number of organisms collected per basin is applied, per taxon, to each photo of the corresponding basin. This correction factor is an adaptation of the methods used to correct an estimate when the probability of detection of individuals is not certain (Burnham and Overton 1978;Otis et al., 1978;Gatti et al., 2011) This corrective factor is calculated for each basin as follows: Average number of organisms per square meter of a taxon, obtained by sampling/ Average number of organisms per square meter of a taxon, obtained by photographic analysis. Only the photos corresponding to the collections are used to calculate this corrective factor.

For example: For the Tamaris basin, in 2020, the average number of Mytilidae obtained per sampling is 157.55 / m 2 (Table 1). The average number of Mytilidae estimated on the corresponding photos is 72.71 / m 2 (Table 1). The correction factor is 157.55 / 72.71 = 2.16. Thus, for all photos of the Tamaris basin the number of Mytilidae per square meter is multiplied by 2.16.

All the results presented below are corrected by this method. Table 1. Estimation of the average number of individuals per square meter and the size of individuals by taxon and by basin, made by collection; and average number of individuals per square meter estimated from photographs taken in the same area, for the 2019 and 2020 campaigns. The dispersion around the means is expressed as standard deviations. Missing records are replaced by the sign NA (Not Applicable).

II.I.II.II.II. Image acquisition and analysis

The images were obtained using a GoPro ® HeRO8 black placed on a measuring rod to standardize the position of the camera and the image shooting (Fig. 2). As the port environment is often turbid, image feedback is necessary to ensure the quality of the image before shooting. A coaxial cable is added to the set-up to provide a WIFI link between the operator and the camera (Fig. 2). Each shot provides a 33.41 × 25.06 cm photoquadrate. Each image is geo-referenced according to the EPSG/3857-WGS84/Pseudo-Mercator system.

All image analysis is carried out using the Ikomia® software. The images are corrected by a color balance for a better reading. The individuals are then counted by an operator. For this, each individual recognized in an image is surrounded by a box corresponding to its taxon in the software (Fig. 3). A txt file is then extracted for each photo with the labels and size of each identified individual. Artificial intelligence is used in this study to automate the identification of individuals in images. This method is based on the concept of deep learning, a subcategory of machine learning, using neural network architectures which are inspired by the structure of the human brain. It works as a system of layers that analyzes the image one after other, usually the more layers there are, the more networks are able to learn. The raw data is input into the network and will be processed by each layer in a specific way. The result of this first processing will inform the next layer, which will in turn process the dataset until the last layer. Each layer corresponds to a piece of information useful for the recognition of the object.

The model used for this study was the fourth version of the Yolo model: Yolo-v4 model (Bochkovskiy et al., 2020). The two main advantages of this model are its accuracy and speed of execution. The first Yolo (You only Look Once) model was implemented in 2015 (Redmon et al., 2016;Bochkovskiy et al., 2020). Yolo model allowed an increase in the speed of program execution by processing the data in one go (the so-called one-pass approach) and not in two goes as previous models (Faster R-CNN, Mask R-CNN, ...) did. For example, on an image where different communities of organisms are present, the Yolo model allows the identification of the areas where the species are found as well as their identification at the same time for each layer.

Yolo-V4 model works in three main steps (Fig. 4.): -the image is sent to the first layer of the "backbone", which will allow an initial simplistic identification of the objects (by their shape, colour, etc.). The successive layers making up the "backbone" will extract maps indicating the location of the objects in the image.

-This data is sent to the "neck", which will sort out the relevant maps, extract them and combine them into useful images. These new images will allow a fine detection of all the objects present (from the simplest to the most complex objects, from low to high resolution images).

-Finally, the "head" or "dense prediction" will collect the information provided by the "neck" and conclude on the detection of objects. These objects will be boxed, and their nature will be determined. AI analysis is carried out in two stages, learning and analysis/validation; and these are carried out for each taxon. The first step consists in training the neural network to extract the relevant features in the image in order to recognize objects. To do this, images already annotated by an operator are presented to the network. It will use these annotations to adapt its own parameters to provide the good output : the recognition of the expected objects. The more images (samples) are presented to the system, the more it learns and becomes accurate. The second step consists of presenting images without annotations to the network and comparing the results obtained with those obtained by an operator on these same images. This step allows the method to be validated and the system error rate to be estimated.

II.I.II.III.II. Setting up the analysis by artificial intelligence

The analysis by artificial intelligence was carried out on the Ikomia® software, by implementing the Darknet framework (https://github.com/AlexeyAB/darknet), according to the protocol of Bochkovskiy et al. (2020). Only the resolution and the batch size were modified to correspond to the needs of the study; from 416 x 416 to 1536 x 1536 pixels for the resolution and 32 to 128 for the batch size. These modifications improve the detection quality, as the objects to be detected are small compared to the image size and improve the convergence of the algorithm.

The validation was carried out on the two most abundant taxa, Ascidiacea and Mytilidae, the other taxa are not present enough for the model to learn to recognize them.

The training was carried out on all the images (year 2019 and 2020) containing these taxa, i.e. 3553 images for Ascidiacea and 502 images for Mytilidae.

The validation was carried out on a sample of 100 images, randomly selected and not used for training. An operator manually re-analyzed these photos to estimate the rate and type of errors made by the software.

II.I.II.IV. Data analysis:

The abundance and distribution of organisms are compared spatially at the scale of the basins but also between pontoons and within pontoons; and temporally by comparing the 2 sampling campaigns. The data are presented in number of individuals per square meter (ind./m 2 ).

All the statistical tests have been carried out using the software R ® (Version 3.6.3 "Holding the Windsock") with a rejection threshold of 5%. The data do not comply with any of the conditions of application of the parametric tests. The Wilcoxon-Mann-Whitney test is used for simple comparisons. For multiple comparisons, the Kruskal Wallis test and the Wilcoxon Pairwise post-hoc test are used.

The distributions are mapped using QGIS® version 3.22., in EPSG/3857-WGS84/Pseudo-Mercator projection.

Only data collected by an operator are used to analyze the abundance and distribution of organisms.

II.I.III. Results

II.I.III.I. Spatial distribution and abundance of organisms

II.I.III.I.I. Inter-basin comparison

In 2019, Mytilidae were absent from the Bout Blanc basin and were few presents in the Marillac basin (1.57±34.03 ind./m 2 ). Mytilidae were statistically more abundant in the Tamaris basin, i.e., 80 times more than in the two other basins (127.19±639.25 ind./m 2 ). The Mytilidae are distributed homogeneously between the pontoons of the three basins sampled except for the most northeastern pontoon of the Tamaris basin, which has a larger population of Mytilidae with average densities of over 1500 individuals per square meter. (Fig. 5A and Table 2)

Ascidiacea are statistically more present in the Tamaris basin than in the Marillac basin and in the Bout blanc basin (Tamaris > Marillac > Bout blanc). They are eight times more present in the Tamaris basin (9228.49±5678.06 ind./m 2 ) than in the Marillac basin (1199.50±1288.31 ind./m 2 ) which is itself three times more densely populated than the Bout blanc basin (401.47±376.24 ind./m 2 ). The ascidiacea have clear distributions between the basins. However, the pontoons of the same basin have comparable densities (Fig. 5B andTable 2).

As for the ascidiacea, the Ostreïdae are statistically more present in the Tamaris basin than in the Marillac and the Bout blanc basins (Tamaris > Marillac > Bout blanc). Ostreïdae are more than five times more present in the Tamaris basin (119.39±312.36 ind./m2) than in the Marillac basin (22.24±110.06 ind./m 2 ), which is itself three times more densely populated than the Bout blanc basin (12.92±83.25 ind./m 2 ). Ostreïdae are homogeneously distributed in the pontoons of the Marillac and Bout Blanc basins. However, like the Mytilidae, they are more concentrated to the north of the Tamaris basin (Fig. 5C andTable 2).

Pectinidae are practically absent from the Bout blanc and Marillac basins with less than one individual per square meter. They are present in the Tamaris basin (3.14±8.20 ind./m 2 ). Even if their distribution is heterogeneous between the basins, their distribution is comparable between the pontoons of the same basin (Fig. 5D and Table 2). In 2020, Mytilidae are more present in the Tamaris basin than in the Lazaret basin and than in the Marillac and Bout blanc basins (Tamaris > Lazaret > Marillac = Bout blanc). The average number of Mytilidae per square metre in the Tamaris basin (198.88±308.57 ind./m 2 ) is more than 50 times higher than in the Bout blanc basin (3.51±27.82 ind./m 2 ). The distribution of Mytilidae is homogeneous between the pontoons of the Tamaris, Marillac and Bout Blanc basins. Their distribution is more

C D A B
heterogeneous in the Lazaret basin where we find density peaks in the two easternmost pontoons and in the northernmost pontoon. (Fig. 6A and Table 2)

The ascidiacea have a statistically different distribution between all the basins, as for the Mytilidae, they are more present in the Tamaris (949.50±552.02 ind./m 2 ) and Lazaret basins (959.44±1055.4774 ind./m 2 ). They are less present in the Marillac basin (288.41±315.90 ind./m 2 ), 8 times less than in the Tamaris and Lazaret basins. The distribution of ascidiacea is heterogeneous between and within each pontoon. With densities ranging from 0-300 to over 2000 individuals per square meter on a single pontoon. (Fig. 6B andTable 2)

Ostreïdae are also mainly present in the Tamaris basin (230.16±497.21 ind./m 2 ). Their distribution does not show any statistical difference between other basins. The distribution of Ostreïdae is similar between the pontoons of the Marillac, Bout Blanc and Lazaret basins but is heterogeneous in the Tamaris basin. Dense populations of Ostreïdae are found on some pontoons in the north of the Tamaris basin (Fig. 6C and Table 2).

In contrast, Pectinidae are almost absent from the Tamaris basin and are mainly present in the Lazaret (7.28±30.19 ind./m 2 ) and Marillac (7.27±46.61 ind./m 2 ) basins. They are 7 times more present in these two basins than in the Bout blanc basin (1.71±12.97 ind./m 2 ). Pectinidae are mainly found in the pontoons to the north of the Lazaret basin, as well as in the pontoons to the north and in the centre of the Marillac basin. The pontoons with the highest densities of Pectinidae are also those showing the greatest heterogeneity of distribution (Fig. 6D andTable 2).

II.I.III.I.II. Comparison between taxa per basin

In 2019, the Tamaris basin has more ascidiacea (9228.49±5678.06 ind./m 2 ) than Mytilidae (127.19±639.25 ind./m 2 ), Ostreïdae (119.39±312.36 ind./m 2 ) or Pectinidae (3.14±8.20 ind./m 2 ) (ascidiacea > Mytilidae > Ostreïdae > Pectinidae). It is the most contrasted basin, all taxa are represented (Fig. 7A, B andTable 2).

C D B A

The Marillac basin contains mainly ascidiacea (1199.50±1288.31 ind./m 2 ), Ostreïdae (22.24±110.06 ind./m 2 ) then Mytilidae (1.57±34.03 ind./m 2 ) and Pectinidae (0.29±2.59 ind./m 2 ) (ascidiacea > Ostreïdae > Mytilidae > Pectinidae). For bivalves, the Marillac basin is mainly represented by Ostreïdae (Fig. 7A,B and Table 2).

The Bout blanc basin contains only ascidiacea (401.47± 376.24 ind./m 2 ), Ostreïdae (12.92±83.25 ind./m 2 ) and Pectinidae (0.61±4.13 ind./m2). Mytilidae are absent. (Fig. 6 and Table 2)

For the whole marina, the ascidiacea are the most present in terms of number of individuals per square metre with densities ranging from 401.47±376.24 ind./m 2 to 1199.50±1288.31 ind./m 2 . On the opposite, the Pectinidae are the least present. The Pectinidae are mainly present in the Tamaris basin with a density of 3.14±8.20 ind./m 2 . Their density is less than one individual per square metre for the other basins. (Fig. 7A,B)

In 2020, whatever the basin, the ascidiacea are always the most present group in number of individuals per square metre with densities per basin ranging from 288.41±315.90 ind./m 2 to 959.44±1055.47 ind./m 2 (Fig. 7C, D andTable 2).

The Pectinidae are, on the opposite, the least present group whatever the basin with densities per basin ranging from 0.13±1.71 ind./m 2 to 7.27±46.61 ind./m 2 . At the scale of the marina the ascidiacea are 100 times more present than the Pectinidae with respective averages of 622.62±640.66 ind./m 2 and 3.37±18.77 ind./m 2 . (Fig. 7C, D andTable 2)

The Tamaris and Bout Blanc basins have similar communities (ascidiacea > Ostreïdae > Mytilidae > Pectinidae) but in different proportions and distribution. The same applies to the Marillac and Lazaret basins (ascidiacea > Mytilidae > Ostreïdae > Pectinidae) (Fig. 7C,D).

II.I.III.I.III. Inter-annual comparison

The communities change significantly between 2019 and 2020. The average number of bivalves (Mytilidae, Ostreidae and Pectinidae) per square metre was significantly higher in 2020 than in 2019 for the Tamaris (from 83.24±319.93 to 143.05±239.16 ind./m 2 ), Bout Blanc (from 4.51±29.12 to 16.75±64.82 ind./m 2 ) and Marillac (from 8.03±48.89 to 20.85±84.23 ind./m 2 ) basins.

C D A B

II.I.III.II. Analysis by artificial intelligence

In the 100 photos analyzed for Mytilidae the operator detected 932 individuals. The AI detected 896 objects of which 774 were Mytilidae and 122 were detection errors. The AI was therefore 16.96% less efficient than the operator and made 13.61% identification errors for this taxon.

For the Ascidiacea, in the 100 photos analyzed the operator identified 3740 individuals. The AI identified 3206 objects of which 3167 were Ascidiacea and 39 were identification errors. The AI is therefore 15.33% less efficient than an operator, but only makes 1.21% errors in the identification of this taxon.

II.I.IV. Discussion

Bivalves and tunicates are two model groups at the centre of the port environment. They are the guardian of its health as a bio-indicator and as an engineering species used in bio-engineering to limit the presence of metals in the water column (Milinkovitch et al., 2015;McCann and May, 2018;Breitwieser et al., 2020;Vozzo et al., 2021). They are also a refuge for many organisms and have a significant impact on the surrounding mud (Bradford et al., 2020;Strain et al., 2018;Zúñiga et al., 2014;Hamani et al., 2021). The establishment of a systematic and regular census allows us to study the evolution of their populations and what influences their distribution. The present study highlights the complexity of their communities and shows the speed of their evolution. A large amount of data is needed to understand what governs this complexity and dynamics; this is why an innovative method, using artificial intelligence, to automate the analyses, was tested during this study.

II.I.IV.I. Sampling and analysis methods

In order to have as less impact as possible on the communities studied, an underwater photographic survey is used. This method allows a systematic, standard and repeatable census. The main limitation of this method is that it leads to an underestimation of the populations. Indeed, photographs only allow a two-dimensional analysis, and individuals that are entangled or present under other organisms cannot be sampled by this method. This is the case for the estimation of Ostreïdae in particular, which are often at the base of communities, with other organisms coming to settle on them (observation by the scientific diver). This bias can be reduced by collecting samples to adjust the estimates.

Photographic analysis allows rapid and complete sampling of very large areas. This is a significant advantage for accurate sampling of populations present in a large and diverse environment such as the La Rochelle marina.

II.I.IV.II. Complex communities

II.I.IV.II.I. Distribution disparity

The communities studied are complex, with variable distributions between taxa, between basins and between pontoons. This disparity would be linked to the fact that the port offers a fragmented discontinuous habitat where each pontoon can be considered as an island of habitat (Connell, 2000). Many other factors such as the type of materials used for the construction of pontoons (Connell and Glasby 1999), the heterogeneity of the surface of the pontoons (Bradford et al., 2020) or interspecific competition (Shinen and Morgan, 2009;Bradford et al., 2020) could explain this disparity. Thus, it is very difficult in a complex and dynamic environment such as the marina of La Rochelle to discriminate the factors influencing the distribution of species as the environmental factors are so numerous and changing.

Nevertheless, we note that the Tamaris basin is the basin with the highest density of organisms of all taxa in 2019 and 2020. This is all the more visible in 2019 when we observe density peaks for the four taxa studied, particularly in the north of this basin. These high densities can be related to the strong hydrodynamics of the basin. Huguet (2020) shows in a study of the hydro-sedimentary flows in the marina of La Rochelle that the Tamaris basin is one of the basins with the highest hydrodynamics. Indeed, this basin is the closest to the open sea and is bordered to the north and south by the two water entrances of La Rochelle marina (Huguet, 2020). The water coming from the open sea is rich in seston and therefore in food, which could explain the fact that this basin is the most densely populated. This hypothesis could also explain the high densities of ascidiacea, Pectinidae and Mytilidae in the southernmost pontoon of the Lazaret, which is also located close to the port's entrance, in a zone of strong hydrodynamics (Huguet, 2020).

The larvae of the four taxa studied are planktonic and their recruitment is influenced by the hydrodynamics of the environment (Martel, 1993;Gosling, 2015;Holland, 2016). It is also possible that the densities observed in the Tamaris basin reflect the transport of these larvae (Martel, 1993).

II.I.IV.II.II. Density disparity between taxa

Ascidiacea is the predominant group in terms of density. They are present on all pontoons and in all basins in both 2019 and 2020. This predominance can be explained by their low sensitivity to anthropogenic pollutants and their great adaptability (Chebbi, 2010, Bouchard andBochard-Madrelle, 2018). Some species such as Ciona intestinalis, which is the predominant species in La Rochelle marina, have a high survival rate and a low malformation rate at the larval stage in presence of hydrocarbons and biocide such as tobacco tar (Bouchard and Bochard-Madrelle, 2018).

In contrast, Pectinidae is the least present group in the marina of La Rochelle. Several studies propose Mimachlamys varia, a Pectinidae commonly found in the Atlantic, as a bio-indicator for its capacity to accumulate trace elements and for its physiological sensitivity towards these trace elements (Bustamante et al., 2005;Milinkovitch et al., 2015;Breitwieser et al., 2018). This Pectinidae would be particularly sensitive to elements such as copper and zinc, which are elements linked to anthropic activity and common in port areas (Ory et al., 2021;Hamani et al., 2021). These elements at concentrations such as found in La Rochelle marina would impact several biological functions such as osmoregulation, oxidative stress, reproduction and energy metabolism (Ory et al., 2021;Hamani et al., 2021). This sensitivity to trace elements could influence the distribution of Pectinidae in the port area and their presence could be used as an indicator of trace element concentration in the environment. Long-term monitoring of their populations and trace element concentrations is necessary to validate this hypothesis.

II.I.IV.II.III. Inter-annual comparison

Between 2019 and 2020, bivalve densities increased in all basins. Populations of Mytilidae have appeared in the Bout Blanc basin and Pectinidae have increased by a factor of seven in the Marillac basin, whereas they were very low (less than one individual per square metre) in 2019. These taxa are sessile in the adult stage and have a lifetime of several years (Gosling, 2015;Holland, 2016). Interannual population changes are therefore related to larval recruitment and survival, but not to population movements. This population increase occurs in a particular context. Indeed, the first sampling campaign was carried out in June 2019, i.e., one year before the health crisis caused by COVID-19, and the second campaign in June 2020, i.e., one month after the crisis. During this health crisis, a total containment, including a navigation ban, was applied from March to May 2020, strongly reducing the anthropic pressure on the study area. This increase in bivalve density could reflect reduced anthropogenic pressure. This hypothesis supports the one presented above on Pectinidae which assumes that their populations are strongly influenced by anthropogenic activity and reinforces the fact that these organisms could be used as relevant bioindicators.

II.I.IV.III. Analysis by artificial intelligence

Image analysis using artificial intelligence allows rapid analysis of large datasets. Once trained, the software analyzed the 200 images in just a few minutes, whereas an operator would have done the work in several hours or even days.

This method of analysis is not yet fully optimized for data such as those in our study. Learning could only be performed on two of the four taxa of interest and the detection error rates were 13.63% for the Mytilidae. This is mainly explained by the fact that the organisms present under the pontoons are very entangled and take on very diverse postures and shapes, which makes learning more complex since the annotated data available does not sufficiently cover all these representations.

These results are nevertheless encouraging as the AI results are 98.79% accurate for ascidiacea. Moreover, the detection rates are equivalent to 83.04% for the Mytilidae and 84.67% for the Ascidiacea of those of an operator. The AI system will improve its learning with the number of available data, so the detection rates and accuracy should be improved with the new data collected at each campaign (if an operator has annotated them). If the AI can correctly identify two of the four taxa, the amount of work for the operators will be greatly reduced. However, in the future, the network could be trained to recognize more taxa.

Trying out other models or creating a model specific to our needs are also solutions to consider improving the results of this tool.

II.I.V. Conclusion

The structures that make up a port provide a habitat for many organisms. In Europe's largest marina, two groups of species, bivalves and tunicates, seem particularly interesting to study as they are abundant and play key roles, notably as engineer and bioindicator species. The present study shows the first results of the monitoring of their population.

The establishment of a systematic and regular census allows us to see the evolution of their populations and to study what influences their distribution. For this purpose, an underwater photographic census is used. This method allows a systematic, standard and repeatable census. A large amount of data is needed to understand what governs this complexity and dynamics; this is why an innovative method, using artificial intelligence, to automate the analyses, was tested during this study. This method allows the analysis of Mytilidae and Tunicates with detection rates of respectively 83.04% and 84.67% and with an associated error rate of 13.63% and 1.21% and is therefore not yet fully adapted to our research. However, analysis by artificial intelligence can be improved with more data available. Indeed, according to the concept of deep learning, the more the network is confronted with data, the more the network "learns" and improves its analyses. This promising method should make it possible in the future to simplify the overall monitoring of populations and to analyze larger datasets, thus providing the additional details needed to understand what conditions these communities, while saving considerable analysis time.

The study shows that the populations are partly conditioned by the hydrodynamics of the environment and by the anthropic activity which is carried out there. Results also suggests that to understand precisely what conditions the populations of bivalves and tunicates, further research is necessary as their distributions are so complex.

This study, carried out in a particular context (before and after the COVID-19 health crisis), shows the importance of anthropic pressure on these communities and supports the fact that bivalves, particularly Pectinidae, are relevant bioindicators.

seeded bivalves and habitat structure on species diversity and filtration rates. Mar. Environ. Res. 165. https://doi.org/10.1016/j.marenvres.2020.105243 Walker, T.R., Grant, J., Weise, A.M., McKindsey, C.W., Callier, M.D., Richard, M., 2014

Conclusion du chapitre II

Ce chapitre a permis d'entrevoir l'étendu des communautés de bivalves et de tuniciers présentes dans le port de plaisance de la Rochelle et montre la complexité de celles-ci (Figure 17). Ces organismes ont des distributions variables entre les bassins, au sein des bassins mais également entre les années. Cette hétérogénéité refléterait les effets de l'hydrodynamisme et de la pression anthropique. Cependant, Il est très difficile dans un environnement complexe et dynamique comme le port de plaisance de la Rochelle de discriminer l'ensembles des facteurs influençant la distribution des espèces tant ils sont nombreux et fluctuants. La poursuite du recensement et la mise en relation avec des données environnementales globales à l'échelle des bassins notamment, sur plusieurs années, (température des masses d'eau, salinité moyenne, taux de contaminants, concentrations et compositions sédimentaires etc.) permettra sans doute de déterminer à quoi sont liés ces disparités de distributions.

Les tuniciers et les bivalves, ont un impact notamment sur le taux d'éléments traces dans l'environnement (McCann et al., 2018 ;Vozzo et al., 2021), sur la présence d'espèces associées (Gutierrez et al., 2003 ;Strain et al., 2020) et sur les vases environnantes (Walker et al., 2014 ;Zúñiga et al., 2014). Ainsi, il-est légitime de se demander comment les disparités de distribution et l'abondance de ces organismes influence l'environnements portuaire ? Le chapitre IV de ce document apporte des éléments de réponse, sur l'implication de ces organismes dans la formation des vases.

Sampling by underwater photography

Abundance estimation and distribution

Key species:

bioindicator and engineer species

III.I.I. Introduction

Trace elements contamination of soil and water is a recurrent environmental problem that requires increased monitoring and is the subject of much worldwide research. Among these heavy metals, copper (Cu) seems particularly interesting to study because it is present in most compartments (soil, air and water) (Blossom, 2015;[START_REF] Ballabio | Copper distribution in European topsoils: An assessment based on LUCAS soil survey[END_REF]Zhang et al., 2021), and impacts many organisms (animals, plants and bacteria) (Giachino and Waldron, 2020;Malhotra et al., 2020;Kumar et al., 2021).

Copper, as many other trace elements, has paradoxical roles: it is necessary for many metabolic activities (Olivares and Uauy, 1996;Cairo et al., 2006;King, 2011) and becomes toxic when present at too high levels (Cairo et al., 2006;Nguyen et al., 2018;Ory et al., 2021). For example, the copper is an essential cofactor for many enzymes (Olivares and Uauy, 1996;Kamunde and Wood, 2004) and it is necessary for oxygen transport in the haemolymph of many crustaceans and bivalves (Van Holde et al., 2001;Gianazza et al., 2021). However, copper at higher concentrations can affect enzyme activity, antioxidant defence (Vieira et al., 2009) and haemocyte survival (Nguyen et al., 2018). Nguyen et al. show that mortality of mussel (Perna canaliculus) haemocytes significantly increases as soon as the amount of copper reaches 62.5 μM (i.e., 1 g/L), whereas it was almost absent at 25.0 μM (i.e., 0.4 g/L) (Nguyen et al., 2018). Similarly, Viera et al. showed that the enzymatic and antioxidant activities in the fish Pomatoschistus microps are affected by copper at concentrations between 25 to 200 μg/L (Vieira et al., 2009).

Copper is a common trace element in port areas. Indeed, due to human activities and their location along the coasts, ports are exposed to metal contamination coming from corrosion of structures, carburant, antifouling paints, and run-off water (Eklund and Eklund, 2014;Brignon and Gouzy, 2014). Especially, their shape tends to amplify the concentrations of these elements trapped in this semi-closed environment, as the structure of the ports is made in a way to limit the effect of waves and currents (Sim et al., 2015;Huguet et al., 2019). In an analysis conducted in 2018 in the Europe's largest marina (Les Minimes, France), among the 8 trace elements tested, copper was the most common element after zinc reaching a concentration of up to 82 μg/L in the water column of the Marillac basin, one of the four port basins (CREOCEAN, 2018).

Ports, although often ignored as such, are ecosystems in their own right (Connell and Glasby 1999;Glasby, 1999;Connell, 2000). As well as being the site of significant human activities, they are biodiversity hotspots and provide refuge, food and nursery for many organisms like most coastal environments (Glasby, 1999;Connell, 2000). For public health and environmental reasons, it seems legitimate to ask what effect copper has on the organisms, at concentration levels found in this environment. As such, Mimachlamys varia, commonly known as the variegated scallop, which is a filter-feeder bivalve frequently found in the marine regions of the Atlantic coast, is often used for marine biomonitoring, particularly in the Minimes marina (Metian et al., 2009;Metian et al., 2009;Bustamante et al., 2005;Milinkovitch et al., 2015;Breitwieser et al., 2018;Breitwieser et al., 2020). Because of its capacity to bio-accumulate trace elements such as copper and because of its sensitivity to these elements it appears to be a relevant bio-indicator species (Milinkovitch et al., 2015;Breitwieser et al., 2016;Breitwieser et al., 2018a;Breitwieser et al., 2018b). Bustamante et al. highlighted that Pectinidae such as the variegated scallop are of particular interest for biomonitoring programs, due to their high bioaccumulation potential compared to other bivalves (Bustamante et al., 2005). Furthermore, Milinkovitch et al. demonstrated the value of the variegated scallop as an indicator of environmental pollution, by showing that biomarkers of oxidative stress (Malondialdehyde and superoxide dismutases (SOD)) and a marker of the immune system (Laccase-type Phenoloxidase activity) present in this species responded efficiently to the presence of trace elements such as copper (Milinkovitch et al., 2015). Similarly, Breitwieser et al. showed that the variegated scallop could be used as a relevant bio-indicator by finding a correlation between concentrations of trace elements such as copper and indicators of oxidative stress, immune system impairment, altered mitochondrial respiration or modified enzyme activity like phosphatases (Breitwieser et al., 2016). Breitweiser et al. highlighted that scallops were more sensitive bioindicators than mussels and oysters, as they were the only ones having a marked enzymatic response (SOD, glutathion S-transférase and laccase) to trace elements in the same environment (Breitwieser et al., 2018). Two other studies also showed that the genetic diversity of variegated scallops was significantly reduced when trace elements were present in the environment, which further reinforces the relevance of this model for biomonitoring purposes (Breitwieser et al., 2016;Breitwieser et al., 2018).

However, all the studies presented above are experiments conducted in situ and the relationship between the organism and the pollution is carried out for all the trace elements present on the site. These studies did not discriminate the effect of one trace element in relation to another and, to our knowledge, no study to date has shown the effect of copper on the biomonitoring model, the variegated scallop. In addition, complete molecular mechanism of copper-induced toxicity in bivalves is far from being well known, although previous studies have started to elucidate it through metabolomics approach. These studies have shown that copper induces responses in energy metabolism, glycerophospholipid metabolism, oxidative stress, osmoregulation and apoptosis mechanisms in bivalves such as mussels (Perna canaliculus), Manila clams (Ruditapes philippinarum) and estuarine oysters (Crassostrea hongkongensis) for concentrations of 1 g/L (3 h copper-exposure on haemocytes), 40 μg/L (96 h copper-exposure) and 50 μg/L (2-6 weeks copper exposure) respectively (Zhang et al., 2011;Chang and Wang, 2018;Nguyen, 2018). These responses are related to the modulation of metabolites involved in energy storage (α, β-glucose, ATP/ADP and glycogen), the transsulfuration pathway (cysteine and methionine), the glutathione metabolic pathway (cysteine, glutamic acid and glutathion) and in the Krebs cycle (succinate, citrate and α-ketoglutarate) (Zhang et al., 2011;Chang and Wang, 2018;Nguyen, 2018). All these studies highlight the fact that, due to the low fraction of metabolites identified, similar studies seem necessary to further investigate and clarify the effects of copper on the metabolism of bivalves.

The aim of the present study is to have a deeper insight of the effect of copper, at the concentration maximally found in the environment of Europe's largest marina (82 μg/L), on the metabolic pathways of a model organism that strongly bioaccumulates trace elements: Mimachlamys varia (Linnaeus, 1758).

In order to focus only on the effect of copper, a laboratory experiment was conducted on 78 scallops. These scallops were collected from a site considered as a reference site in previous studies, due to the low presence of trace elements (Breitwieser et al., 2016;Breitwieser et al., 2017). Half of the scallops collected were exposed (48 h) to a copper dose of 82 μg/L and the others were used as controls. Efficient extraction method followed by comparative metabolomic profiling of gill samples allowed determining how the metabolic profile of scallop gills is modified, in response to copper exposure. More generally, untargeted metabolomics approach is used to measure the widest range of metabolites present in an extracted sample, without prior knowledge of the metabolome. It can reveal new, non-targeted and early detected dysregulated features. Thus, in the present paper, an optimized triple extraction method followed by an untargeted metabolomics approach using ultra-high performance liquid chromatography coupled to high resolution mass spectrometry (UHPLC-HRMS) was chosen, as it offers a high level of sensitivity to highlight the impacts of short-term exposure to copper. After a complete processing of analytical data and statistical analysis of results using multivariate techniques, we could clearly separate scallops with no metal inputs and those exposed to copper and identify about thirty copper-modulated metabolites.

III.I.II. Materials and Methods

III.I.II.I. Experimental Design and Sample Preparation

The experimental design is based on an experiment conducted by Ory and collaborators (Ory et al., 2021). For the present study, 78 scallops (size between 4-6 cm) were collected at La Pointe du Grouin in Loix en Ré along the French Atlantic coast (Ré Island, France). This site is considered as a reference site in other studies due to the low presence of trace elements (Breitwieser et al., 2016;Breitwieser et al., 2017). A genetic approach was applied in a previous study to validate the identity of the species collected at this reference site (Breitwieser et al., 2018). This study also confirmed that the scallop M. varia along the French Atlantic and English Channel coasts is not genetically subdivided. Consequently, the scallops found at the refence site are comparable to those found in the port of Les Minimes (Breitwieser et al., 2018). The scallops were then acclimated during 4 weeks before the experimentation. The physico-chemical parameters of the water were: pH 8.0, temperature 10 °C, salinity 33 g/kg seawater, nitrite, nitrate and ammonia <0.025 mg/L. These parameters were monitored every day and kept constant by a biweekly water renewal. Shellfish Diet 1800 ® (Reed Mariculture, Campbell, CA, USA) was supplied ad libitum three times a week. Scallops were distributed in 6 aquaria of 18 L. Three aquaria randomly selected were contaminated with a solution of CuSO4 (nominal copper concentration 82 μg/L). After 48 h exposure, all 39 scallops from each condition were collected. A 48-h exposure time was established in order to observe the effects of copper after the longest possible exposure, but before lethal effects occur. In a pre-test study, high mortality in scallops was observed after 72 h of exposure to copper at the same concentration (82 μg/L, maximal concentration measured in study site), while the controls were still alive (personal observation). Thus, to study the effects of copper (82 μg/L) on the metabolism of scallops one day before lethal effects occur, we chose an exposure time of 48 h. This choice is reinforced by a study showing that copper can have lethal effects in some bivalve species after 48 h of exposure to lower concentrations than in the present study (Mesquita et al., 2019).

Each sample was prepared from the gills of 3 scallops, which were dissected, dried and snapfrozen in liquid nitrogen as in the publication by Ory and collaborators (Ory et al., 2021). Thus, a total of 13 control and 13 copper-exposed samples were obtained. Gills in bivalves such as scallops were enlarged during evolution and are much more extensive than needed for respiration. They form the main interface between the organism and the surrounding water and have become therefore a key organ for food absorption. Given the high water filtration rates of bivalves, gills constitute also a significant pathway of incorporation of pollutants and among them metals via seawater (Ravera, 2001). Making a logical extension to this, it has been shown that gills would have high defense ability against contaminants, which are characterized by induction of pollutant biotransformation and antioxidant-related enzymes and metallothioneins (Trevisan et al., 2016). Consequently, gills play a central role in scenarios of acute exposure to metals, by integrating both absorption and metabolism.

The samples were then crushed on ice and adjusted to 1 g. To extract a maximum of compound, each sample was subjected to a triple acetone/acetone/methanol extraction as previously described (Ory et al., 2019;Mondeguer et al., 2015). The three solvent supernatants from each sample were then pooled. To remove residual impurities, they were centrifuged at 3000× g for 5 min. This total supernatant was recovered and dried under a stream of nitrogen as previously described (Ory et al., 2019;Mondeguer et al., 2015). The dry extract was finally resuspended in 2 mL of 20/80 methanol/water and filtered at 0.2 μm (using low protein binding filter) before MS analyses (Ory et al., 2019;Mondeguer et al., 2015). The methanol and acetone used were of HPLC grade purity (CARLO ERBA Reagents, Val-de-Reuil, France).

III.I.II.II. UHPLC/QToF MS Analysis of Samples

An ultra-high performance liquid chromatography ("Acquity UPLC H-class", Waters, Milford, CT, USA) coupled to high resolution mass spectrometry equipped with an electrospray ionization source was used to analyze the samples ("XEVO-G2-S Q-TOF", Waters, Manchester, England). 5 μL of the samples were injected in a column "Acquity UPLC HSST3" (Waters) (2.1 × 150 mm, 1.7 μm), and the products were eluted at a flow rate of 200 μL/min using a gradient composed of solvents A (water/formic acid 100/0.001 (v:v)) and B (acetonitrile/formic acid 100/0.001 (v:v)), according to the following procedure: 0-3 min, 100% A; 3-8 min 0-50% B ; 8-13 min 50% B; 13-20 min 50-95% B; 20-30 min, 95% B, 30-31 min 95-0% B, 31-36 min 100% B. The analyses were performed in positive and negative ionization mode with MS function in a centroid mode. For the two ionization mode the MS parameters was applied in the ESI source were: source temperature 120 °C, desolvation temperature 500 °C, gas flow-rate of the cone 50 L/h, desolvation gas flow-rate 300 L/h, and capillary voltage was 3 kV (+) and 2.5 kV (-) and sampling cone 35 V. The instrument was adjusted for the acquisition on a 50-2100 m/z interval, with a scan time of 0.5 s. A 20 to 40 V ramp was used as collision energy for the high energy mode of MS E (Waters). This MS E approach consists in MS and MS/MS data acquisitions in a single same run. This is achieved by rapidly alternating between two functions i.e., the first, acquired at low energy provides exact mass precursor ion spectra; the second, at elevated energy provides high energy exact mass of the fragment ions. Fragment ion spectra are assigned to their associated precursor ion peaks so that all the information necessary to identify each compound of interest is collated and available. Software algorithms that profile each chromatographic peak and determine their retention times accomplish this. Precursors and fragment spectra are then aligned according to retention times and linked together. The Leucine Enkephalin (M = 555.62 Da, 1 ng/μL) was used as a lock-mass and the mass spectrometer was calibrated using 0.5 mM sodium formate solution.

The samples were analysed randomly to avoid the effect of possible analytical drift. Analytical repeatability was guaranteed by quality control samples (QC) that were injected every 5 measurements. The QCs were obtained from the pooling of all samples. Blanks prepared with the last extraction solvent were injected at the beginning and end of the sample sequence to subtract components from the extraction solvent.

III.I.II.III. Statistical Analysis

The data were processed as ion peak intensity using the Workflow4Metabolomics (W4M) platform (http://workflow4metabolomics.org, accessed on 10 December 2021) according to the method described by Ory and collaborators (Ory et al., 2019). All the parameters used for the treatment are available at this link:

https://workflow4metabolomics.usegalaxy.fr/u/vhamani/h/imported-test-batch-cuivrengatif (accessed on 10 December 2021).

Analytical drift was corrected on the pools, using a Loess regression model (Van Der Kloet et al., 2009). Repeatability was assessed through the coefficient of variation (CV) of the QCs. Metabolites with a CV > 0.3 were removed from the analyses.

Principal component analysis (PCA) was used to detect natural clustering between samples and to detect outliers. Outlier samples were removed to strengthen the model (Thévenot et al., 2015). Partial least squares-discriminant analysis (PLS-DA) was performed on the log-transformed and Pareto normalized data. The selection of metabolites was based on the importance of their contribution as a predictor variable in the PLS-DA model. A data with variable in projection (VIP) > 1 can be considered as a metabolite having a significant contribution to the PLS-DA model. The predictive performance and reliability of PLS-DA models was tested with premutation (n = 100) and cross-validation (10-fold) tests.

To statistically prove the intensity difference of each metabolite between samples, t-tests were performed using the software R (Version 3.6.3 "Holding the Windsock") with a rejection threshold of 5%. The homoscedasticity of the data and the normality of their distribution was checked beforehand by Shapiro and Bartlett tests.

Total ion current chromatograms for the leucine standard (E), for the leucine in QC sample (F), for the aspartic acid standard (K) and for the aspartic acid in QC sample (L). * Peaks of interest.

Finally, we used the classification of Shymanski et al., to support the identification of the metabolites (Schymanski et al., 2014). This method assigns a score to each metabolite based on the degree of confidence in its identification (Schymanski et al., 2014): -Score 1, identification using a standard (same retention times, m/z and fragments).

-Score 2a, annotation using fragmentation data from databases such as HMDB, LipidMaps, Metlin, with a spectrum-structure match unambiguous.

-Score 2b, the fragments obtained match completely with the proposed structure, which excludes other possibilities, but the data are not completely available in the databases.

-Score 3, proposed annotation of one or more isomeric molecules without the possibility of distinguishing between them because few or no fragments were obtained, or the fragments were common to the different positional isomers. Polysaccharides with different structures cannot be distinguished because they have the same formula and identical fragment ions. Thus, polysaccharides have been grouped under generic names corresponding to the number of monosaccharides that compose them.

III.I.III. Results

III.I.III.I. LC/MS Data Processing and Analyses

XCMS preprocess from Workflow4Metabolomics platform (W4M) resulted in the detection of 21,483 and 35,880 m/z features for negative and positive ionization modes, respectively. Data process implying blank removal, loess batch correction of analytical drift and removal of metabolites with Coefficient of Variation (CV) > 0.3 in Quality Control samples (QC = pool of all samples) led to 1925 and 5997 ions in negative and positive ionization modes, respectively. Multivariate analyses were performed on these latter datasets. Principal Component Analyses (PCA) highlighted not only the natural structure of samples but also potential sample outliers (Figure 1). On the score plot, the PCA showed the sample distribution based on the qualitative and quantitative metabolites composition. Variable metabolite intensities induced a clear clustering into two sample groups according to the copper contamination, in negative as well as in positive ionization mode. Indeed, metabolite composition contributed to the well separated structure of samples between control and copper exposed individuals, mainly along the first axis (t1) for positive ionization mode and along the second axis (t2) for negative mode. The first two axes (t1 and t2) accounted for 11-17% and 9-10% of the total variability for positive and negative modes, respectively. Outlier detection relies on the score distance represented by Hotelling T2 threshold and on orthogonal distance. These two parameters showed that three reference samples (two T2 and one orthogonal distance) in negative mode and two reference samples (one T2 and one orthogonal distance) in positive mode were outliers. These samples were then removed before Partial Least Square-Discriminant Analysis (PLS-DA), because of their high level in one or both distances.

PCA analysis allowed detecting a clear natural and distinguished clustering between control and copper-exposed samples, justifying PLS-DA model reliability. This is a supervised method building a model that force the distinction between two firstly defined groups. PLS-DA also provides results of variable responsible for forced clustering. The relevance and performance of the supervised built model was proven with PLS-DA parameters of data consistency (R 2 ) and prediction performance (Q2). R 2 (cumulative) reached 0.99 for both ionization modes and Q2 (cumulative) reached 0.84 and 0.89 for positive and negative modes, respectively. Permutation test (n = 100) and cross-validation test provided p-values < 0.01 confirming the consistency of the data and the reliability of the predicted models. Thus, a separation between the two groups was significantly demonstrated. Among variables structuring the sample distribution of PLS-DA model, Variable Importance in Projection (VIP) > 1 defined the ones with the significant contribution to the model. We kept metabolites with VIP > 1 to rebuild new successive PLS-DA models, until reaching the best predictive model and select the most important metabolites explaining the two-group clustering. In positive mode, two supplementary models were built, keeping 1587 and 487 metabolites with VIP > 1 and Q2 reaching 0.97. In negative mode, only one new model was needed to obtain the best predictive model (492 metabolites with VIP > 1 and Q2 = 0.95).

III.I.III.II. Metabolite Modulation

Among ions significantly modified under copper exposure, a total of 28 metabolites were annotated with a score of less than or equal to 3 in Shymanski scale (Table 1). Two of them have a confirmed structure (score 1), 15 a probable structure (12 score 2a and 3 score 2b) and 11 are potential candidates (score 3) (Table 1). They were all significantly different between copper-exposed and control samples, mainly because they were selected by their variable importance in projection (VIP) after successive PLS-DA modeling. Among them, 14 ions were annotated in negative ionization mode, 12 in positive ionization mode and two were annotated in both ionization modes (Table 1). They belong to different biochemical classes: 3 are carbohydrates, 10 are peptides or amino acids (AAC), 13 are lipids and one is a nucleotide (Figure 2). Interestingly, most of them were upregulated in copper-exposed samples compared to the control samples, and only 4 out of 28 were down-regulated (three amino acids and one lipid) (Figure 2). The highest magnitude of modulation after copper-exposure was 31-fold relative spectral intensity for N5-Acetyl-N2-gamma-L-glutamyl-Lornithine (up-regulated) and 13-fold relative spectral intensity for oxidized gluthatione (downregulated).

belonging to all families of biochemical compounds. These variations reflect potential effects on several of the biological processes discussed below, such as energy metabolism, oxygen transport, inflammation, defence against oxidative stress, lipid metabolism, osmoregulation, reproduction, peptide and nucleotide metabolism.

III.I.IV.I. Energy Metabolism and Oxygen Transport

It is commonly accepted that exposure to pollutants leads to an additional energy cost for marine organisms, which must expend energy to implement cellular protective and detoxification mechanisms (Sokolova et al., 2012). Moreover, toxic metals such as cadmium, copper, zinc and mercury have been shown to reduce both mitochondrial efficiency and coupling and increase proton leakage in marine organisms (Sokolova et al., 2012).

In response to this additional need for ATP, these organisms are able to switch between different metabolic processes involved in energy acquisition and conversion, in particular towards anaerobic pathways (Sokolova et al., 2012). So, the first arising question is whether recourse to the latter pathways is observed here. The aspartate-succinate pathway with succinate and alanine as end products is one of the four main anaerobic pathways used by marine bivalves (Ory et al., 2019). Therefore, if anaerobic metabolism occurs, a decrease in aspartate is expected. Such a decrease is indeed observed in this case, which would therefore confirm the use of anaerobic metabolism by scallops exposed to Cu. Cao and collaborators also observed a decrease in several amino acids including aspartate, when studying copper-induced metabolic variation in oysters (Cao and Wand, 2017). They attributed this phenomenon to a mobilization of amino acids to produce energy for maintaining function of pathways in these Cu-exposed organisms. On the contrary, Zhang and collaborators found an increase of aspartate level in gill tissues of Cu-exposed clams after exposures for 24 h at 10 or 40 μg/L Cu 2+ (Zhang et al., 2011). This was interpreted as a mean for marine molluscs of balancing their intracellular osmolarity with the environment, with high intracellular concentrations of free amino acids.

In the present study, the increase of four oligosaccharides (tri-, tetra-, penta-and hexasaccharides) in Cu-exposed scallops was found and may be related to a disturbance in the catabolism of glycogen. In marine bivalves, energy reserves are mainly constituted by glycogen and to a lesser extent by lipids. Glycogen is the storage form of glucose and plays a central role in the energy supply for both maintenance metabolism and gametogenesis (Bayne et al., 1982;Ruiz et al., 1992).

Glucose supply from glycogen requires synchronous activities of two different enzymes: glycogen phosphorylase and the bifunctional glycogen debranching enzyme. Glycogen phosphorylase cleaves the α-1,4 linkage from the non-reducing end of the glycogen to remove glucose 1-phosphate. Further, when four glucose residues remain before the branching point, the bifunctional debranching enzyme goes into action. This enzyme exhibits both glycosyltransferase and amylo-1,6-glucosidase activities on a single polypeptide chain (Nakayama et al., 2001). Using the transferase activity, the debranching enzyme transfers the three glucose residues from the four-residue glycogen branch to a nearby branch. This leaves one glucose unit joined to the glucose chain branch point through an α-1,6glycosidic linkage.

After that, through the glucosidase activity, the debranching enzyme cleaves the α-1,6 linkage to release a free glucose from the branch point. Glycogen phosphorylase is then able to continue the cleavage of glucose residues from this linearized glycogen chain, producing glucose 1-phosphate. This last sugar is then converted to glucose-6-phosphate and enters glycolysis and tricarboxylic acid cycle (Bollen et al., 1998). These two enzymes responsible for glycogen breakdown have been isolated in clams (Hata et al., 1987;Smits et al., 2020). One hypothesis that can be put forward to explain the accumulation of tri-, tetra-, penta-and hexa-saccharides upon copper exposure is that the glycogen debranching enzyme may undergo partial inactivation by copper. Such an inactivating effect of copper has been described in mussels for the hexokinase enzyme (Canesi et al., 1998). The results of in vivo experiments, after 3 days exposure to Cu 2+ at 40 μg/L, indicated that the inhibition of hexokinase would be caused, on the one hand, by a direct binding of the metal to the sulfhydryl groups of the protein, and on the other hand, more indirectly, by a decrease in the level of reduced glutathione (GSH) and consequent imbalance between pro-oxidant and antioxidant cellular processes. Indeed, GSH is used by metal exposed organisms to protect themselves against their cytotoxicity (Le Saux et al., 2020).

To our knowledge the susceptibility of the bivalve glycogen debranching enzyme to copper has not been studied but should be examined to confirm the hypothesis expressed above. An early study shows that the rabbit glycogen debranching enzyme could be inactivated by oxidation of its sulfhydryl groups promoted by the oxidized form of GSH (Cappel et al., 1986).

A variation of two fatty acid derivatives was found here: a down-regulation of adipoyl-CoA and an up-regulation of 3-hydroxyoctadecenoylcarnitine. We already observed variations of carnitine combined to fatty acids levels in previous studies about the effect of emersion periods and Zn exposure on the variegated scallop (Ory et al., 2019;Ory et al., 2021). The fatty acid concerned here (3hydroxyoctadecenoic) is a long one, which has to be combined with carnitine to enter the mitochondria, where it undergoes beta-oxidation for energy production. So, its increase reflects a disturbance in the oxidation of the corresponding long-chain fatty acids upon Cu exposure. However, as mentioned by the Connor and collaborators, metabolism of acylcarnitines is not only related to the transport of fatty acids, but also plays a key role, among others, in maintaining the homeostasis of the mitochondrial acyl-CoA/CoA ratio (Connor and Gracey, 2012;Gracey and Connor, 2016). Moreover, here, an additional effect related to fatty acid metabolism is observed with the decrease in the level of adipoyl-CoA. So, it seems that a more general disturbance of fatty acids metabolism occurs in presence of Cu, with potential mitochondrial dysfunction.

In mollusks, oxygen transport is provided by haemocyanin, a multimeric glycoprotein containing a type-3 copper (Kato et al., 2018). This respiratory protein was reported to decrease in crustaceans in response to exposition to polluted environment including copper. The hypothesis was that detoxification of contaminants may interfere with normal copper metabolism in the blue crab and may lead to a decrease in the synthesis of haemocyanin (Engel et al., 1993). As branched chain amino acids like leucine are involved in haemocyanin synthesis and transportation (Ferreira et al., 2016), the increased level of leucine found in the present study may be linked to a decrease of the respiratory protein upon copper exposure. This trend was observed by Cao and collaborators when studying the combined effect of salinity and copper exposure in oysters (Cao and Wang, 2017): An increased level of leucine was observed in 15 g/kg seawater plus Cu compared with 10 g/kg plus Cu waters.

III.I.IV.II. Inflammation, Oxidative Stress Defence and Lipid Metabolism

Lipids have a variety of biological roles as fuel molecules or energy store (Berg et al., 2002). They are also essential constituents of biological membranes that can regulate their functions (Spector and Yorek, 1985;Yèagle,1989;Yang et al., 2018). Previous studies showed that copper exposure induced disturbances in the metabolism of lipids in bivalves (Zhou et al., 2021;Fokina et al., 2013).

The diglyceride (9M5/9D3/0:0) or (11M3/9D3/0:0) or (9D3/11M3/0:0) or (9D3/9M5/0:0) upregulated 5 times under exposure to 82 μg/L of copper for 48 h consists in two fatty acid chains covalently bond to a glycerol molecule through ester linkages. This molecule is an intermediate in the biosynthesis of phosphatidylcholine or phosphatidylethanolamine (Soudant et al., 1995;Tabakaeva and Tabakaev, 2016) These phospholipids are among the most abundant in the soft tissues of bivalves, in contrast to phosphatidylserine, which is a quantitatively minor membrane phospholipid (Tabakaeva and Tabakaev, 2016). In our study, the compound putatively identified as phosphatidylserine was upregulated by a factor 3 in copper-exposed samples. The increase of this compound in the presence of copper was also reported in bivalve mollusk Anadara broughtonii (Tabakaeva and Tabakaev, 2016). During the early stages of apoptosis, the externalization of phosphatidylserine to the outside of cells is considered as a recognition signal, by which apoptotic cells are eliminated by phagocytes (Canesi et al., 2015). The externalization of phosphatidylserine is, in this respect, used as an indicator of apoptosis in a study on the mussel Mytilus galloprovincialis (Canesi et al., 2015). Thus, this increase in phosphatidylserine and diglycerides reflects a membrane modification that could result from an apoptotic process allowing the organism to eliminate cells impacted by copper or containing copper.

The compound putatively identified as leukotriene, up-regulated in the present study by a factor 2 in presence of Cu, could be leukotriene C4, a cysteinyl leukotriene or 11-trans-leukotriene C4, a leukotriene derivative. Leukotrienes are a family of potent inflammatory mediators and natural lipids that are oxygenated metabolites of arachidonic acid (Di Gennaro and Haeggström, 2012).

Biosynthesis of the leukotrienes involves the action of a lipoxygenase on arachidonate to yield an intermediate, which is then dehydrated to the leukotriene A4. Leukotriene A4 can be hydrolyzed to the leukotriene B4 or it can be conjugated with glutathione (GSH) to produce the leukotriene C4 (Di Gennaro and Haeggström, 2012). In case of tissue damage, release of leukotriene C4 proinflammatory mediator might be involved in apoptosis mechanisms via oxidative stress (Di Gennaro and Haeggström, 2012). This supports the previously stated hypothesis that the organism appears to eliminate cells impacted by copper or containing copper cells by an apoptotic process.

In the present study, an increase of phosphatidic acid level in gills of copper-exposed bivalves was observed. Phosphatidic acid is an important component in phospholipid synthesis. More precisely, it is a precursor for both cytidine diphosphate diacylglycerol and diacylglycerol. Cytidine diphosphate diacylglycerol is used to make phosphatidylinositol, phosphatidylglycerol, and cardiolipin (Yang et al., 2018). Thus, phosphatidic acid is indirectly an essential component of membranes from a structural and functional point of view (Tabakaeva and Tabakaev, 2016). Phosphatidic acid plays a key role in the regulation of intracellular membrane transport through poorly understood mechanisms. Both phosphatidic acid and lysophosphatidic acid may influence biophysical properties of the membrane (Kooijman et al., 2003). The regulation of phosphatidic acid could be correlated with the membranous modification generated by the mechanisms of apoptosis or endocytosis stated above. This would support this hypothesis.

As mentioned above, phosphatidic acid is a substrate for the enzyme cytidine diphosphate diacylglycerol-synthase to produce an endoplasmic reticulum pool of cytidine diphosphate diacylglycerol (Yang et al., 2018), another metabolite up-regulated in the present study after copper exposure. Cytidine diphosphate diacylglycerol is a critical intermediate in the synthesis of both lipids, phosphatidylinositol and phosphatidylglycerol/cardiolipin (Nigou and Besra 2002;Blunsom 2020). Both molecules, found in bivalves (Tabakaeva and Tabakaev, 2016), have specialized roles in cells and are synthetized in different organelles.

N-palmitoyltaurine was found to be up-regulated by a factor 3 in Cu-exposed scallops. This compound is part of N-acyl amides, a group of endogenous lipids, characterized by a fatty acyl group linked to a primary amine metabolite by an amide bond. This type of compounds has been found in all organisms from bacteria to mammals for decades. N-acyltaurine were identified as cell-signaling molecules, but many other roles remain to be elucidated (Waluk et al., 2012).

The lysophospholipids compounds putatively identified as lysophosphatidylcholine and lysophosphatidylethanolamine were up-regulated by a factor 3 in gills of scallops upon exposure to 82 μg/L of copper for 48 h. Lysophospholipids are usually the result of phospholipase A-type enzymatic activity on regular phospholipids such as phosphatidylcholine or phosphatidic acid, although they can also be generated by the acylation of glycerophospholipids or the phosphorylation of monoacylglycerols. Phospholipases A are present in bivalves. For example, in Sajiki and Taguchi's study, the major metabolites from phosphatidylcholine in oyster and scallop were lysophosphatidylcholine and free fatty acid (Sajiki and Taguchi, 1995). Lysophosphatitylcholine is a precursor of lysophosphatidic acid, another lysophospholipid that has important signaling functions, especially in inflammation (Frisca et al., 2012). Lipidomic analysis by Chan and Wang conducted in digestive gland of oyster Crassostrea hongkongensis exposed to Cu showed different responses depending on the exposure dose (10 and 50 μg/L for 1, 2 and 4 weeks) (Chan and Wang 2018). This study suggest that exposure induced subcellular compartmentalization, modulation of inflammatory responses and phospholipid remodeling with rapid elevation in glycerophospholipids like phosphatidylcholine and phosphatidylethanolamine to protect the vital metabolic function of the organ.

Ceramide phosphoethanolamine (d15:2(4E,6E)/20:0(2OH)) putatively identified in our study was found to be up-regulated by a factor 4 under copper exposure. This compound, a sphingomyelin analog, is a major sphingolipid in invertebrates (Panevska et al., 2019). Ceramide phosphoethanolamine biosynthetic mechanisms differ from sphingomyelin ones, due to the invertebrate specific ceramide phosphoethanolamine synthase. For example, ceramide phosphoethanolamine appears to have a role in early development of Drosophila and in axonal ensheathment by disrupting the tight packing of lipid membranes (Kunduri et al., 2018).

Metals, and in particular copper, are able to induce oxidative stress in bivalves. Cu 2+ generates free radicals through the Fenton and Haber-Weis reaction (Le Saux et al., 2020). Cu 2+ -exposed haemocytes showed a remarkable increase in reactive oxygen species production, which induced oxidative stress in mussel Perna canaliculus (Nguyen et al., 2018). This was accompanied by a decrease in GSH. This compound is an important antioxidant, able to react with oxidants like H2O2, with conversion of two GSH molecules into its oxidized form (GSSG). Surprinsingly in our case, GSSG was found to be down-regulated in gills of scallops upon Cu exposure. These results are in accordance with a study conducted in 2000 on oysters which indicated that the copper-induced decrease in glutathione content was mainly related to a stimulation of GST activity, which was transient in the gills (Conners et al., 2000).

S-(Formylmethyl)glutathione is also modulated by copper. This ubiquitous oligopeptide is described in the literature but its role in scallop metabolism remains to be determined (Paul, 1991).

III.I.IV.III. Osmoregulation, Reproduction

Prostaglandins (PGs) are an important group of bioactive lipid compounds, involved in a great variety of physiopathological processes, like for instance inflammation, signaling or reproduction and furthermore in the control of gametogenesis, ion transport, and defence in marine invertebrates (Di Costanzo, 2019). In the present study, we found that three compounds, putatively identified as PGs or PG-glutathione complexes, were modulated in the gills of scallops exposed to 82 μg/L of copper for 48 h. A metabolite annotated as PG D1, E1, F2 or H1 or as 8-isoPG F2 or E1 showed an up-regulation (x3), a compound putatively identified as S-(PGA1)-glutathione or S-(9-deoxy-12-PGD2)-glutathione or S-(11-OH-9-deoxy-9,12-PGD2)-glutathione was down-regulated (x6) and another compound putatively identified as S-(9-deoxy-delta9,12-PGD2)-glutathione or S-(PGJ2)-glutathione or S-(PGA2)-glutathione was up-modulated (x2). These variations potentially correspond to disturbance of biological functions such as reproduction, ion transport and defence caused by copper in scallops. PGE2 was shown to be involved in sodium transport regulation in gills of the freshwater mussel Ligumia subrostrata and in clams (Saintsing and Dietz, 1983) and it was shown that hyposmotic stress significantly increased PG synthesis in the marine bivalve Modiolus demissus (Freas and Grollman, 1980). This is the second time that PG-glutathione conjugates are described in clams, showing that these compounds are indeed present in bivalves and that they are affected by metals (Ory et al., 2021).

III.I.IV.IV. Peptide and Nucleotide Metabolism

In the present study, exposure to 82 μg/L of copper for 48 h led to the modulation of four dipeptides (Val-Asp, HydroxyPro-Tyr, Pro-Arg and N5-Acetyl-N2-gamma-L-glutamyl-L-ornithine), one oligopeptide (glycylalanylprolylmethionylphenylalanylvalinamide) and one amino acid (N-Acetyl-L-glutamate 5semialdehyde). Except for HydroxyPro-Tyr, these peptides were up-regulated. Dumas et al. also showed an increase of peptides, in the presence of pharmaceutical pollutants, but without finding an explanation of why these particular peptides were modulated (Dumas et al., 2020). Impact of pollution on nucleotide metabolism of marine mollusk or fish has often been mentioned (Lankadurai et al., 2013;Watanabe et al. 2015;Dumas et al., 2020;Ory et al., 2021) Nucleotides are the building blocks of DNA and RNA and the metabolic relationships between nucleotides and many metabolic pathways are strong, which makes it difficult to interpret their levels of variation. In the present study, an increase of 2-Hydroxyadenine (Isoguanine) level was found and may be, for example, linked with ATP alteration (Kamiya and kasai, 1995;Zhou et al., 2021).

III.I.V. Conclusions

This study constitutes a broad survey on the metabolites impacted by copper exposure in scallops, at environmental concentration (82 μg/L). We used an optimized triple extraction method and as analytical technique, ultra-high performance liquid chromatography coupled to high resolution mass spectrometry (UHPLC-HRMS), to detect as many metabolites as possible, without a priori. However, given the variety of chemical classes and physical properties that characterize metabolites, it is clear that not all the different chemical classes of metabolites could be covered in a single analytical method. The significant varying metabolites between non-exposed and exposed organisms have been isolated using multivariate statistics and among them, nearly 30 have been identified or putatively identified. The result is that we have a partial view of copper-induced metabolic shifts. Under these conditions, we can only put forward hypotheses on the metabolic pathways affected, which remain to be confirmed. Furthermore, at this stage, it is not possible to establish connections between the different metabolic pathways, nor to prioritize the effects and to elucidate the complete molecular mechanism of copper toxicity, the complexity of which is already highlighted by our results.

Besides these limitations of an untargeted metabolomics approach, this study demonstrates some of the strengths of using this method: (i) the detection of 'distress signals' at the molecular level, faster than in organism/population/ecosystem level biomarkers (ii) the identification of metabolic changes that would be missed by other 'omics' techniques, as protein and mRNA levels in the cell do not necessarily translate into metabolite changes (iii) the detection of unexpected varying metabolites, showing that short exposure to copper at environmental condition leads to significant changes in the metabolism of scallops, some of which are signs of cellular damage.

Further studies are needed to formally identify the key metabolic pathways involved in copper toxicity. Tools are available which attempt to confirm assertion made for altered pathways through (i) subsequent focus on key pathways of interest with a targeted metabolomics analysis, (ii) an enrichment analysis, (iii) the building of networks to help interpret the data, (iv) isotopic labelling a substrate and following this label through various metabolic pathways.

III.II.I. Introduction

Marine ecosystems are the final receptacle of contaminants released to the environment, especially in seaports and other industrialized or strongly anthropised coastal areas. Boat harbors, for instance, may be hotspots of contaminant accumulation (Johnston et al., 2011;Bighiu et al., 2017). Indeed, they are likely to receive both a cumulative load of pollutants from upstream point and nonpoint sources from watershed, and many pollutants generated at the marina itself. In addition, the construction of a marina generally creates a condition of reduced water circulation and protection from wave action. The result is an area with limited natural water circulation and exchange. The marina of La Rochelle, located in the south-west of France, perfectly illustrates this phenomenon with its complex geometry and infrastructure, especially since its expansion in 2014 (Huguet et al., 2019). Over time, this reduced circulation and increased pollutant generation can increase pollutant concentrations in the water column, sediments, and aquatic organisms. This often results in greater impacts in the area concerned on ecological communities (Sim et al., 2015). Because of their environmental persistence, heavy metals are one of the major harmful toxic pollutants for the marine environment (Stankovic et al., 2014) and especially in harbors and marina (Galkus et al., 2012;Bighiu et al., 2017). The major proportion of these trace elements is trapped in coastal sediments where they can be continuously released into the water column and incorporated into food webs. The availability of trace elements to aquatic species is of prime concern both in terms of the prediction of the effects of metal pollution on ecosystems and in terms of public health when bioaccumulated in edible animals.

In the following study, we focused attention on Zn pollution, at a concentration such as the maximum concentration that can be reached in the marina of La Rochelle. Zinc is found at 157 μg/L in the water of the Marillac area, which is one of the four docks that make up the marina of les Minimes (CREOCEAN, 2018). It may arise from nonpoint sources from watershed: rainwater runoff sources (outdoor zinc or galvanized surfaces, tire wear debris, etc.), zinc-containing paints, anti-corrosion additives for water-containing equipment, fireworks, motor oil/ lubricating oils additives, industrial air emissions, industrial runoff, zinc minerals or wastes in construction materials, fertilizer and agricultural micronutrient products (California Stormwater Quality Association (CASQA, 2015). It also has its origin in the boat components and their maintenance: zinc anodes used to deter corrosion of metal hulls and engine parts, zinc constituent of motor oil and tires, antifouling paints (Eklund and Eklund, 2014).

Among the marine organisms most affected by metal pollution are bivalve mollusks, given their filter-feeding attitude, which leads to a strong accumulation of the pollutants. In order to investigate the un-known toxicological effects and mechanisms of metals on bivalves, environmental metabolomics is commonly applied for several years now (for reviews see: Booth et al., 2011;Viant and Sommer, 2012;Lankadurai et al., 2013). As examples of recent metabolomics application in the case of a metal contamination of bivalves, Aru et al. (2016) investigated the effects of short-term lead and zinc exposure upon the metabolic profiles of clams Ruditapes decussatus and Ruditapes philippinarum. Nguyen et al. (2018) applied an integrated approach that combines flow cytometry and metabolomics to characterize cellular and molecular mechanisms of copper immunotoxicity in mussel (Perna canaliculus). Wu et al. (2017) found that mussel response to cadmium was dependent on life cycle stage. Many other current applications of metabolomics to study the effects of metals or other water contaminants on marine organisms have been reported in many studies (for a review see Pomfret et al., 2020).

Here, we used the marine bivalve Mimachlamys varia, in the family Pectinidae, commonly known as the variegated scallop, as a model organism. Due to its relative abundance along the Atlantic coasts, its sedentary nature and also because this species has been shown to have a very elevated pollutants incorporation and retention capacity, it has been proposed as a potential indicator species for the marine bio-monitoring (Metian et al., 2009a(Metian et al., , 2009b;;Milinkovitch et al., 2015;Breitwieser et al., 2018a). In particular, it is relatively easy to sample in the marina of La Rochelle, where it has been used for ecotoxicological studies (Breitwieser et al., 2018b). Furthermore, it is a commercially harvested species also captured for leisure activities, directly on the shore or by snorkeling and it represents therefore a definite economic value.

Previously, we performed a first metabolomics study on M. varia that highlighted a complex metabolic reprogramming that occurs during tidal cycles after an emersion period of 2 h and upon reimmersion (Ory et al., 2019). It appeared that metabolites depend on the moment of the tidal cycle as well as on the ambient environment (oxygenation, salinity and temperature conditions, seasonality, etc.). In order to minimise the effects of all these important interplaying environmental factors and understand the underlying mechanisms affecting M. varia exposed to zinc, we grew scallops in aquaria under controlled and continuously immersed conditions and we exposed the animals to zinc concentration equal to that found in La Rochelle marina. A comparative metabolomics study was performed in gills samples, using UHPLC/QToF mass spectrometry, in order to provide an overview of the relationship between zinc exposure and metabolome changes. Gills were preferred over other tissues, as they have been shown to be, along with the mantle and digestive gland, the main storage organs for metals in oysters (Wang et al., 2018). In addition, gills are generally considered as the main entry of dissolved metals in marine filter-feeder organisms (Marigomez et al., 2002).

III.II.II. Materials and methods

III.II.II.I. Animals and experimental design

Scallops, Mimachlamys varia, (shell length from 3 to 5 cm) were collected from La Pointe du Grouin to Loix en Ré (Ré island, France) and acclimated one month in the laboratory in filtered through a 50 μm nylon filter and sterilised seawater. The physicochemical parameters of the water were controlled every two days and were kept constant by a biweekly water renewal (pH 8.0, temperature 10 •C, salinity 33 g.kg -1 seawater, nitrite, nitrate, and ammonia <0.025 mg.L -1 ). Food as liquid algal culture (Shellfish Diet 1800®, Reed Mariculture, Campbell, CA, USA) was distributed three times per week, at a rate of 0.02 mL per individual. Mortality of less than 3% was observed in acclimation tanks.

For this experiment, 36 scallops were randomly distributed in six 18 litres aquaria. Three randomly selected aquaria were contaminated with a ZnCl2 solution (nominal zinc concentration 150 μg.L-1). The other three aquaria received the same amount of seawater.

After 48 h of exposure, the six scallops remaining in each aquarium were sampled. The gill tissues of each individual were dissected, drained on absorbent paper and put in cryovial on ice. Gill tissues from three individuals were grouped, snap-frozen in liquid nitrogen and stored in a freezer at -80 • C. From this sampling, six exposed samples and six controls were obtained. These control samples were used as a reference for the analyses.

III.II.II.II. Sample preparation for metabolomics study

Sample preparation was performed according to a previously described method (Ory et al., 2019), inspired by a metabolomics study in Phycotoxins laboratory (Ifremer, Nantes, France) (Mondeguer et al., 2015). In summary, samples were thawed, homogenized by manual grinding and then crushed with a homogenizer. These three last operations were performed on ice. They were then adjusted to 1 g and stored at -80 • C before extraction procedure. This last protocol included a triple solvent extraction by successively using acetone twice and methanol. The three pooled supernatants were recovered and dried with a stream of nitrogen, before resuspension with 2 mL methanol/water 20/ 80 (v/v), storage at -80 • C, filtration with 0.2 μm filters and LC/MS analysis.

II.II.II.III. UHPLC/QToF MS analysis of metabolites

The analysis of metabolites in gills was performed by ultra-high-performance liquid chromatography coupled to high resolution mass spectrometry, according to a previously described method (Ory et al., 2019), with the same analytical equipment. 5 μL of the samples were injected in a column "Acquity UPLC HSST3" (Waters) (2.1 × 150 mm, 1.7 μm), and the products were eluted at a flow rate of 300 μL. min -1 using a gradient composed of solvents A (water/formic acid 100/0.001 (v/v)) and B (acetonitrile/formic acid 100/0.001 (v/v)). The gradient used was the same as described previously (Ory et al., 2019). The ana-lyses were performed in positive and negative ionisation mode with MSE function in a centroid mode. The MS parameters applied in the ESI source for the two ionisation modes were the same as described previously (Ory et al., 2019), except that desolvation gas flowrate was 300 L. h-1 and capillary voltage was 3 kV (+) and 2.5 kV (-) and sampling cone 35 V. The instrument was adjusted for the acquisition on a 50-2100 m/z interval, with a scan time of 0.5 s. A 20 to 40 V ramp was used as collision energy for the high energy mode of MSE. The mass spectrometer was calibrated before analysis using 0.5 mM sodium formate solution and the Leucine Enkephalin (M = 555.62 Da, 1 ng. μL -1 ) was used as a lock-mass.

Compound identification was performed as explained below.

III.II.II.IV. Quality control

A pool sample was prepared by combining 100 μL of each gills tissue extract. This mixture was divided into ten vials that were used as quality-control samples (QCs). They were regularly distributed and injected throughout the sample list to ensure analytical repeatability. Samples of gill tissue extracts were measured in randomised order. Blanks were prepared with the last extraction solvent and injected at the beginning and at the end of the sample sequence, to allow the subsequent subtraction of contaminants or components coming from the extraction solvent.

III.II.II.V. Chemicals

Acetonitrile, Methanol, Acetone with HPLC grade purity were from Carlo Erba. Water was prepared using a Milli-Q reagent water system. Succinate and L-phenylalanine were purchased from Sigma-Aldrich (now part of Merck).

III.II.II.VI. Statistical analysis

Metabolites data were obtained and treated as ion peak intensity as previously described (Ory et al., 2019). Data were processed on the online and freely available Workflow4Metabolomics (W4M) platform (http://workflow4metabolomics.org) for pretreatments and multivariate analyses processing as previously described (Ory et al., 2019). Pretreatments included batch correction and removing metabolites with coefficients of variation (CV) > 0.4 in the QC samples. Quality metrics tool (supplied by W4M Core Development Team) provided visualising the data matrices, batch correction efficiency and supplied a rapid highlight of potential sample outliers.

Log-transformation normalized the data and Pareto scaling was applied before the multivariate analysis process. The data were analyzed with unsupervised (Principal Component Analysis, PCA) and supervised (Partial Least Square Discriminant Analysis, PLS-DA) methods. This last method is a multivariate regression and prediction based on the separation between two classes: reference and Zn-exposed samples after a 48 h exposure. It allowed the selection of metabolites involved in class separation in order to identify metabolites affected by Zn exposure. Metabolites responsible for classification between groups were selected according to their contribution as variable in the component prediction in PLS-DA model, described as Variable Importance in Projection parameter (VIP), considering only variables with VIP values higher than 1 indicative of significant differences between groups.

Predictability performance was evaluated for each built PLS-DA model. To assess the statistical significance, t-tests were performed on each metabolite intensities difference between reference and Zn exposed samples, after normality and homoscedasticity were previously checked. Otherwise, Mann-Whitney tests were performed.

III.II.II.VII. Identification and relative level of metabolites

The identification of metabolites was performed by using the human metabolome database (http://www.hmdb.ca) and the METLIN database (https://metlin.scripps.edu/landing_page.php?pgcontent=mainPage) and also for lipids and lipidderivatives with the online lipid database: (http://www.lipidmaps.org/tools/ms/LMSD_search_mass_options.php). A research was performed with the mass value of metabolites and a limit with a mass error lower 5 ppm. Moreover, for succinate and L-phenyl-alanine, analytical standards were used with the LC/MS method to verify this identification. Metabolites were finally expressed in relative abundance, which was calculated for each metabolite by dividing the abundance in each sample by the median abundance across all the samples.

III.II.III. Results

III.II.III.I. Data processing

Mass spectrometry untreated analyses detected 20,946 m/z features for negative ionisation mode results in LC/MS and 44,256 for positive ionisation mode. These large sets of data obtained for metabolomics profiling were preprocessed applying a Lowess regression model fitting with the pool values as batch correction (Van Der Kloet et al., 2009).

After preprocessing and removal of metabolites with CV > 0.4 in QC samples, the database of metabolites counted for 1556 and 3581 com-pounds detected with negative and positive ionisation modes in LC/MS respectively.

III.II.III.II. PCA analysis

PCA was performed as a first method to confirm differences in metabolite levels between reference animals and animals exposed to zinc and detect eventual outlier samples. The score plots of PCA analysis are shown in Fig. 1. Each symbol represented an individual sample, and the dot scattering indicated similarities or differences in metabolic compositions between samples. PCA performed with data sets from both reference and exposed individuals showed that two groups were well separated according to Zn exposure for the negative mode but fairly well separated for the positive mode, due to a high dispersion of Zn-exposed samples along the 2nd axis. Thus, the intensities of the compounds, considered as variables, contributed to the separate structure observed between reference and exposed individuals. The two first axes accounted for 31%-12% and 24%-14% of the total variability among samples for negative and positive data sets respectively. Reference samples and samples exposed to Zn were grouped and distinguished mainly along the second axis (t2) for both ionization conditions. The model fitted the data well. However, too many variables were considered to highlight a specific contribution to the total variability within both data sets.

Hotelling's T 2 statistic tested the presence of outliers measuring the variation within the PCA model. Samples with large Hotelling T 2 had an unusual variation inside the model. In this case, they were not representative of the modeled data and can be considered as outliers if p-value <0.05. The PCA results showed one outlier sample in the negative mode of data sets (Zn48-2). This outlier sample was removed from sample matrix data set to perform PLS-DA.

III.II.III.IV. Metabolite modulation

Mass-matching analysis using the different online metabolome databases mentioned above or comparison with standards allowed putative annotation of eleven metabolites showing a significant difference between reference and Zn exposed samples (Table 1). Interestingly, all of them were down-modulated when going to references to Zn exposed samples. The relative abundance of all these metabolites decreased under zinc exposure by more than 30% (Fig. 2): L-phenylalanine (-39.02%, p = 0.05), L-kynurenine (-70.31%, p = 0.0038), picolinic acid (-61.93%, p = 0.013), neuroprostane 1 (-58.61%, p = 0.027), neuroprostane 2 (identified as 14hydroperoxy-H4-neuroprostane or 11-hydroperoxy-H4-neuroprostane or 10-hydroperoxy-H4neuroprostane) (-40.22%, p = 0.05), neuroprostane 3 (256 candidates corresponding to neuroprostanes on 266 entries on lipid maps databank for this m/z) (-52.28%, p = 0.05), succinate (-42%, p = 0.05), S-(PGA2)-glutathione or S-(PGJ2)-glutathione (-64.07%, p = 0.012), xanthine (-46.65%, p = 0.018), hexanoylcarnitine (-36.81%, p = 0.044), dodecenoylcarnitine (-49.12%, p = 0.0005).

III.II.IV. Discussion

Scallops exposed for 48 h to a nominal zinc concentration of 150 μg/L in laboratory conditions undergo alterations of their metabolism. These alterations correspond to metabolism of two amino acids (e.g.L-phenylalanine and L-tryptophan), bioactive lipid compounds (glutathione conjugated prostaglandin and neuroprostanes), purine metabolism (e.g. xanthine), tricarboxylic acid (TCA) cycle intermediates (succinate) and metabolism of fatty acids (hexanoylcarnitine and dodecenoylcarnitine). These variations could reflect potential effects on several of the biological processes discussed below, such as energy metabolism, including means to face increased energy demand and potential mitochondrial dysfunction, osmoregulation, oxidative stress defense and purine and tryptophan metabolism as discussed below.

It should be mentioned that the decrease in phenylalanine could also result from disturbed food intake under stress induction.

III.II.IV.I. Energy and fatty acid metabolism

In the present study the decrease of four metabolites (L-phenylala-nine, hexanoylcarnitine, trans-2-dodecenoylcarnitine and succinate) for Zn exposed scallops, may be related with energy metabolism.

The decrease of phenylalanine may reflect its consumption as substrate for energy metabolism, in place of carbohydrates or lipids, which are used in normal circumstances. Indeed, phenylalanine is an amino acid being both glucogenic and ketogenic and it can be consumed under energy deficient conditions in aquatic invertebrates (Sokolova et al., 2012). In case of Zn exposure, this energy deficiency may arise from an elevated basal metabolic demand due to the need to develop protective mechanisms for the cells, such as overproduction of metallothioneins, glutathione, molecular chaperones, antioxidants pathways (Cherkasov, 2006;Ivanina et al., 2008;Sokolova and Lannig, 2008). Moreover, toxic metals such as cadmium, copper, zinc and mercury have been shown to reduce mitochondrial efficiency and coupling and elevated proton leak in marine organisms (Sokolova et al., 2012). In the same vein, after 9 days of exposure with nominal Zn concentration of 30 μg/L, oysters gills were analyzed by proteomic analysis and it was concluded that Zn affected the TCA cycle by influencing the expressions of Fe-containing proteins and disrupted the electron transport chain by inhibiting com-plex I-IV related protein expressions (Meng et al., 2017). It should be mentioned that other stress factors such as hypoxia, the presence of other pollutants or high temperature could concomitantly modify the effect of zinc on the metabolism of bivalves. Recently Belivermis et al. (2020) showed that hypoxia diminished the Ag and Zn uptake in mussels and induced significantly greater abundance of several amino acids, amino sulfonic acids, dicarboxylic acids, carbohydrates and other metabolites compared to Zn exposed mussels in normoxia. Sokolov et al. (2019) observed a decrease of protein synthesis during hypoxia in intertidal oysters Crassostrea gigas and interpreted this as an energy-saving mechanism.

Two different acylcarnitine, hexanoylcarnitine and trans-2-dodecenoylcarnitine, were found to be down-regulated in presence of zinc. The first derivative of carnitine (hexanoylcarnitine) is a medium-chain acylcarnitine, whereas the second one (trans-2-dodecenoylcarni-tine) is a long-chain acylcarnitine. Long chain fatty acids have to be combined with carnitine to enter the mitochondria, where they undergo beta-oxidation for energy production. In contrast, the medium-chain fatty acids can enter the mitochondrial membrane directly for beta-oxidation without the need of carnitinemediated transport. Therefore, in our case, the defect of trans-2-dodecenoylcarnitine mainly affects the oxidation of the corresponding long-chain fatty acids. However, the metabolism of acylcarnitines is not only related to the transport of fatty acids, but also plays a key role in maintaining the homeostasis of the mitochondrial acyl-CoA/CoA ratio (Connor and Gracey, 2012;Gracey and Connor, 2016) and in other physiological processes such asperoxidation of fatty acids. Therefore, the observed change in acylcarnitine profile in presence of zinc may be related more generally with potential mitochondrial dysfunction and abnormal fatty acid metabolism.

Lastly, succinate was found to decrease upon Zn exposure. It is a metabolite intermediate of the TCA cycle, which is oxidized into fumarate by the iron-sulfur enzyme succinate dehydrogenase (SDH). Zn affects the TCA cycle by influencing the expressions of Fe-containing proteins (Pagani et al., 2007) and it is therefore so not surprising to observe that succinate is impacted by Zn in our study. What is more surprising is that the succinate appears in the present study to be down-regulated after Zn exposure. Indeed, in several previous studies, an accumulation of succinate was observed after Zn exposure: in the gills of Pacific oyster (Crassostrea gigas) exposed to excess Zn solution (30 μg/L) for 9 days (Meng et al., 2017), in the digestive gland of Ruditapes philippinarum exposed to ZnCl 2 (nominal concentrations: 20, 50, 100 and 150 μg/L) for 48 h (Aru et al., 2016) and in adductor muscles of the pedigree White clam of Ruditapes philippinarum after exposure with Zn 2+ (50 μg/L) for 48 h (Wu et al., 2011). This accumulation of succinate was interpreted as molecular sign of the shift in cellular metabolism to anaerobiosis. It was explained in detail by proteomic analysis, by a decrease in SDH expression and a simultaneously increase in enzyme succinyl-CoA synthetase (SCS) expression, which allows succinate biosynthesis in the TCA cycle, under Zn exposure of oysters (Meng et al., 2017).

Nevertheless, in the same study, fumarase (FUM), another Fe-S enzyme that converts fumarate to Lmalate in the TCA cycle, showed significantly increased levels of expression at the same time. This was interpreted as a compensation mechanism for ensuring that the TCA cycle remains active when exposed to metals (Meng et al., 2017). This indicates that Fe-S enzymes of the TCA cycles can be either up-or down-regulated upon Zn exposure and that defense strategy against Zn toxicity exists in bivalves, as it is the case with bacteria exposed to metals such as Al that interfere with Fe metabolism (Chenier et al., 2008).

In another study, two pedigrees (White and Zebra) of clam Ruditapes philippinarum were exposed with Zn 2+ (50 μg/L) during 48 h and the metabolomics results showed differences in digestive gland between White and Zebra clam samples in succinate levels: in Zebra clam, succinate was increased, whereas it was decreased in White clam after Zn exposure (Ji et al., 2015). In conclusion, it seems clear that Zn affects the TCA cycle metabolites, through its effect on Fe-S enzymes involved in the cycle. Concerning the level of succinate, it may be increased or decreased upon Zn exposure, depending on the species, with respect to over-or under-expression of the different Fe-S enzymes of the TCA cycle. However, succinate has multiple roles in cell metabolism and its decrease may be linked among others with formation and elimination of reactive oxygen species, as discussed below.

III.II.IV.II. Osmoregulation

Down-modulation of L-phenylalanine on the one hand and of prostaglandin-glutathione and neuroprostanes on the other hand, in Zn exposed scallops may be related to osmoregulation phenomena.

Indeed, L-phenylalanine is a catecholamine precursor and its lower level may lead to a decrease in dopamine. Dopamine and serotonin are neurotransmitters involved in the modulation of

Na

+ and K + transport in gills of crustaceans (Mo et al., 1998) and in lateral cilia in gills of bivalves (Carroll and Catapane, 2007). The down-modulation of dopa-mine may thus have a repercussion on osmoregulation of cells submitted to Zn exposure. A similar relationship between L-phenylalanine decrease and osmoregulation was previously suggested (Aru et al., 2016). These authors observed a down-modulation of phenylalanine in presence of ZnCl 2 (20, 50, 100 and 150 μg/L) under laboratory conditions after 48 h exposure for the clam Ruditapes decussatus, associated with a significant increment in organic osmolyte production (hypotaurine and homarine) and a decrease of the content of free amino acid. Prostaglandins (PGs) are an important group of bioactive lipid compounds in living organisms; they are involved in mammals in a great variety of physiopathological processes like for instance inflammation, signaling or reproduction. These molecules play similar roles in marine invertebrates, being involved in the control of gametogenesis, ion transport, and defense. These molecules also represent very important lipid mediators in marine invertebrates (Di Costanzo et al., 2019). PGs biosynthesis starts with arachidonic acid, a polyunsaturated fatty acid (PUFA), that is oxidized by enzymes such as cyclooxygenase or lip-oxygenase to give precursors, which are then further transformed by a large number of possible enzymes, giving rise to the formation of different families of PGs, like PG J2 and PGA2. These last PGs may undergo addition reactions with glutathione (GSH) to give new reactive compounds in humans (Murphy and Zarini, 2002). In the present study, among the metabolites showing a down regulation after 48 h Zn expo-sure, a compound putatively identified as S-(PGA2)-glutathione or S-(PGJ2)-glutathione was obtained. This would indicate that these types of conjugates are also present in bivalves and are impacted by exposure to Zn.

Isoprostanes (IsoPs) and the IsoP-like molecules are PG-like com-pounds formed in vivo via the nonenzymatic free radical-initiated per-oxidation of a number of different PUFAs. Among them, neuroprostanes (MPs) are generated from the PUFA docosahexaenoic acid (DHA) (Milne et al., 2011). PGs, IsoPs and IsoP-like molecules have been identified recently in mollusks (Chakraborty et al., 2014;Bonnefille et al., 2018), which is not surprising given that PUFAs are essential molecules for the survival of bivalves (Da Costa et al., 2015) and that they are highly susceptible to oxidation because of the large number of their double bonds.

The role of PGs, IsoPs and Iso-P like molecules in invertebrates has not yet been fully elucidated. Some studies show that they have a role in osmoregulation: PGE2 was shown to be involved in Na transport regulation in gills of the freshwater mussel Ligumia subrostrata and also in clams (Saintsing and Dietz, 1983) and it was shown that hyposmotic stress significantly increased prostaglandin synthesis in the marine bivalve Modiolus demissus (Freas and Grollman, 1980). In the present case, a down-modulation of three compounds identified as neuro-prostanes was obtained after Zn exposure and this may be linked also with osmoregulation. In fish, prostaglandins were shown to be involved in Clsecretion (Avella et al., 1999) and effluent exposure resulted also in widespread reduction (between 50% and 90%) in PG profiles obtained through metabolomics in fish tissues and plasma (David et al., 2017).

III.II.IV.III. Oxidative stress defense

Besides their possible role in the above mentioned osmoregulation, IsoPs and Iso-P like molecules have become biomarkers of choice in human for assessing endogenous oxidative stress linked with many pathological disorders, because they are chemically stable (Milne et al., 2008). Oxidative stress is characterised by an imbalance between cellular antioxidant defenses and overproduction of free radicals, particularly reactive species of oxygen (ROS). Lipids are readily attacked by free radicals, resulting in the formation of a number of peroxidation products. In bivalves, like in other animals, there is a close relationship between environmental stress and the rate of cellular ROS generation and consequently lipid peroxidation reactions (Regoli and Giuliani, 2014). In our case, the modification of the Iso-P like molecules profile could therefore be linked to an increased oxidative stress in the presence of Zn.

Another down-modulated metabolite under Zn exposure that may be linked with oxidative stress defense is succinate. The roles of succinate in mitochondrial ROS formation and elimination are numerous and complex (Tretter et al., 2016). It was shown that succinate exerted an inhibitory effect on lipid peroxidation in mitochondria. This protective role of succinate against oxidation was attributed to the maintenance of a pool of reduced coenzyme Q. Succinate was oxidized by the membrane-bound succinate dehydrogenase and the enzyme activity was only moderately sensitive to oxidants, therefore it was more efficient in maintaining reduced coenzyme Q, thus maintaining membrane integrity.

Other metals and in particular copper are able to induce oxidative stress in bivalves. Cu 2+ -exposed haemocytes showed a remarkable in-crease in ROS production, which induced oxidative stress in mussel (Perna canaliculus) (Nguyen et al., 2018). This was accompanied by a decrease in GSH. This compound is an important antioxidant, able to react with electrophilic oxidants (e.g., H2O2) resulting in conversion of two GSH molecules into its oxidized form (GSSG). Two other molecules decrease simultaneously upon Cu 2+ exposure: cysteine, which is involved in the GSH metabolic pathway and methionine, which takes place in the transsulfuration pathway, a source of cysteine for GSH. These concomitant phenomena were identified as important signatures of oxidative stress (Nguyen et al., 2018).

III.II.IV.IV. Purine metabolism

A lower level of xanthine in presence of Zn suggests a disordered nucleotide metabolism. Indeed, in the catabolism of purine nucleotides, adenosine monophosphate (AMP) and guanosine monophosphate (GMP) both lead to xanthine (Van Waarde, 1988). AMP is degraded to inosine and then by phosphorolysis to hypoxanthine. In presence of xanthine oxidase (XOD), xanthine is formed from oxidation of hypo-xanthine. GMP is degraded to guanosine and then by phosphorolysis to guanine, which is transformed to xanthine by guanine deaminase. This makes the metabolic interrelationships between nucleotides and purine base nucleosides, and finally xanthine, very strong (Harkness, 1988). Therefore, we can consider that xanthine is at the center of the interplay between ATP and GTP metabolism. Since the nucleotides ATP and GTP are the energy carriers molecules in cells, it can be hypothesized that zinc would induce an increased demand for energy by the cells.

Previously, a decrease of inosine (between -30 and -80%) and hypoxanthine (between -40 and -50%) was observed in whole body of zebrafish, after exposure to ZnCl 2 at different concentrations (10, 100, 500 and 1000 μg/L for 72 h). It was interpreted as an impairment of the purine metabolism caused by exposure to Zn. As it was combined with an ATP level increased, it was hypothesized that Zn would induce an increased energy demand to fulfil essential maintenance costs and ensure organism survival (e.g. cellular protective mechanisms, detoxification) (Sokolova et al., 2012;Kim et al., 2016).

III.II.IV.V. Tryptophan metabolism

In humans, L-tryptophan is metabolized by two main pathways: the serotonin pathway (around 1% of L-tryptophan metabolism) and the kynurenine pathway (around 95% of L-tryptophan metabolism). In the kynurenine pathway, L-tryptophan gives one of three main end products: kynurenic acid, picolinic acid and NAD. This pathway begins with the oxidative cleavage of L-tryptophan by either one of the two enzymes indoleamine 2,3-dioxygenase (IDO) or tryptophan 2,3-dioxygenase also called tryptophan pyrolase (TDO) to produce L-formylkynurenine, which is then converted to Lkynurenine by a formamidase. L-kynurenine is a branch point and can be converted to the following: 1) kynurenic acid by kynurenine aminotransferases; 2) 3-hydroxykyruni-nine by kynurenine 3monooxygenase; or 3) anthranilic acid. 3-Hydrox-ykyruninine further undergoes enzymatic or chemical transformations to give either picolinic acid or NAD (Grant et al., 2009). The kynurenine metabolism was shown to be highly conserved throughout evolution and the enzyme IDO was discovered in mammals, lower vertebrates, several invertebrates, fungi and a number of bacterial species (Cervenka et al., 2017).

In the present study, a down-regulation of both picolinic acid and kynurenine was observed after Zn exposure, showing an impact of this metal on tryptophan metabolism. This trend was also observed in another study with the marine bivalve Mytilus galloprovincialis, when exposed to a wastewater treatment plants effluent extract: both L-for-mylkynurenine and L-kynurenine were found to be down-regulated (respectively -55%, p ≤ 0.05 and -63%, p ≤ 0.05) compared to non-exposed animals thanks to a non-targeted metabolomics study (Dumas et al., 2020).

In another study using proteomic analysis with the pacific oyster Crassostrea gigas the enzyme kynurenine formamidase was found to be down-regulated under aerial exposure (Zhang et al., 2015), which again corresponds to an impairment of the tryptophan metabolism. This was accompanied by the suppression of many physiological activities and this was interpreted as a means of redistributing available resources to fuel stress responses (Zhang et al., 2015).

III.II.V. Conclusion

In the present study, we chose the variegated scallop Mimachlamys varia, for assessing zinc contamination effects on their metabolism, at a concentration such as the one the metal can reach in La Rochelle marina. An untargeted UHPLC/QToF tandem mass spectrometry metabolomics approach was chosen, as it offers a high level of sensitivity to highlight impacts due to short-time metal exposure. Metabolite profiling of gills tissues could clearly separate scallops with no metal inputs and those exposed to 48 h zinc exposure, under laboratory conditions. Among the high quantity of modulated metabolites, only a few of them were identified, because of the current lack of knowledge on scallop metabolism. They include amino acids or their metabolites, bioactive lipid compounds, including four metabolites never before identified in bi-valves, metabolites of purine or the TCA cycle and carnitine conjugates of fatty acids. These molecules reflect potential zinc effects on several of the biological processes, such as energy metabolism, osmoregulation, defense against oxidative stress, metabolism of purine and tryptophan.

This study demonstrates once again that metabolomics approach, when used in untargeted mode is able to reveal novel and unanticipated physiological perturbations, without a priori knowledge of the metabolome. This is valuable in the present case where a poorly studied animal model is used. The limitations of the technique come from the fact that there are a large number of unknown metabolites that remain unannotated in the databases, so that some metabolite features cannot be attributed to a molecular structure. The development of new methods dedicated to the identification of metabolites on the one hand and to the search for the connectivity of metabolic pathways on the other hand, combined with the enrichment of databases, will make it possible in the future to carry out more and more advanced impact analyses.

Moreover, further study is needed to assess the effect of other trace elements present in the marine environment and better understand the combined effects of pollutants. La Rochelle marina sets up multiple actions to ensure a sustainable development of coastal activities while preserving the aquatic environment. These actions, framed by the "Ports Propres" AFAQ certification (AFNOR: Association française de normalisation), are based on criteria approved at the European level by the CWA 16987 agreement of the "Clean Harbour Guidelines". Among them, some aim to develop approaches to highlight the physiological modifications of marine organisms impacted by environmental variation. Our results show that metabolomics is a powerful method that can brings out small environmental variations, such as zinc concentration, through metabolic changes in scallops.

Conclusion du chapitre III

Pour des raisons de santé publique et environnementale, les éléments traces métalliques tels que le cuivre et le zinc font l'objet d'une surveillance accrue dans l'environnement. Les ports par l'activité anthropique qu'ils abritent et leur localisation aux abords des côtes sont particulièrement soumis à la présence de ces éléments. Les études présentées dans ce chapitre ont montré les effets de ces deux éléments traces sur le métabolisme d'un organisme modèle vivant dans le milieu portuaire, le pétoncle (Mimachlamys varia).

Ces études ont montré qu'une exposition courte (48h) à des doses comme celle que l'on peut rencontrer dans le port de plaisance de La Rochelle (82 μg/L de cuivre et 150 μg/L de zinc), pouvaient moduler la présence de nombreux métabolites chez le pétoncle (Figure 18). Ces modulations reflètent l'action de ces deux composés sur différentes voies métaboliques impliquées dans de nombreuses fonctions biologiques, telles que l'osmorégulation, le stress oxydatif et le métabolisme énergétique. Le cuivre impacterait également la reproduction et serait impliqué dans des phénomènes d'apoptose. Cependant, et ce notamment à cause du manque de données sur la physiologie de l'organisme, seul une partie des voies métaboliques modulées par le cuivre et le zinc ont pu être identifiés. Des études complémentaires ciblées, se concentrant sur l'étude de voies métaboliques ou sur des fonctions physiologiques particulières (marquage isotopique, analyse d'enrichissement, étude de la respiration mitochondriale, par exemple), permettraient d'étayer et de compléter ces travaux.

Ces travaux ont également permis de montrer que la métabolomique non ciblée est un outil de recherche puissant, car elle permet d'étudier l'effet de facteurs environnementaux sur tous les composants (métabolites) de la cellule sans a priori. Ceci permet d'avoir une idée globale et précise de l'effet de ces facteurs sur le métabolisme des organismes. Cet outil est d'autant plus intéressant qu'il permet d'étudier des organismes dont la physiologie est encore peu documentée, comme c'est le cas dans notre étude.

Le cuivre et le zinc ne sont pas les seuls contaminants présents dans la colonne d'eau, leurs concentrations peuvent varier et les substances peuvent avoir des effets différents et parfois même antagoniste s'ils sont présents ensemble (effet cocktail) [START_REF] Delfosse | L'association fait le poison-Nouveau regard sur l'effet cocktail des xénobiotiques et les interactions médicamenteuses[END_REF]. De nombreuses recherches sont donc nécessaires pour connaitre la totalité des effets des contaminants sur les organismes vivants en milieu portuaire. Les travaux de ce chapitre apportent des éléments nouveaux sur les effets de deux éléments traces communs et présentent des solutions puissantes pour explorer et étudier les effets des facteurs environnementaux ; ce qui est un atout non négligeable dans cet environnement variable et complexe.

Les facteurs environnementaux et les organismes sont en interaction, il ne faut donc pas oublier que les organismes aussi peuvent influencer la présence et les caractéristiques des variables environnementales. Les huîtres sont à ce titre utilisées pour limiter la présence de contaminant dans le port de New-York au États-Unis (Kim et al., 2017;McCann and May, 2018)). Mais d'autres facteurs peuvent être modulés par la présence de ces éléments comme le montre le chapitre suivant.

Chapitre IV

Rôle des organismes filtreurs dans le comportement des vases en milieu portuaire

Les espaces portuaires sont confrontées à de nombreux défis. L'un des plus connus est l'envasement, une problématique à la fois économique et environnementale qui est au coeur des préoccupations actuelles. De nombreuses études ont été réalisées sur les facteurs physiques qui conditionnent l'envasement en zone portuaire. Cependant, peu s'intéressent aux rôles des facteurs biotiques dans la formation de la vase. Pourtant, les bivalves et les tuniciers, très présents dans l'environnement portuaire (voir chapitre II), pourraient y jouer un rôle (Weise et al., 2009 ;Walker et al., 2014 ;Wang et al., 2018).

Les objectifs de ce chapitre sont de mettre en évidence le rôle de ces organismes dans les processus d'envasement des espaces portuaires et d'identifier les facteurs qui influencent la quantité et la composition de leurs rejets.

Pour étudier le rôle des filtreurs dans les processus d'envasement, une analyse expérimentale a été réalisée dans le port de plaisance de La Rochelle. Cette analyse a consisté à récupérer et à étudier les bioproduits des filtreurs à l'aide de pièges à sédiments fixés sous les pontons. Afin de comprendre ce qui influence la quantité de bioproduits formés, les données recueillies ont été mises en relation avec la distribution des différents taxons ainsi qu'avec les données météorologiques et hydrodynamiques disponibles.

Une expérience de laboratoire a également été mise en place pour étudier le rôle précis de chaque espèce dans la composition des vases. L'étude a consisté en une analyse quantitative et qualitative des bioproduits des trois espèces de bivalves les plus abondantes du port de plaisance de La Rochelle dans six conditions de nourrissage. Ces conditions ont été choisies pour d'être les plus représentatives possibles des différents apports sédimentaires du port de plaisance de La Rochelle. L'étude qualitative a été effectuée par l'analyse des teneurs en glucides et en protéines des bioproduits. Ces deux composés étant en grande partie responsables de la structure et de la cohésion des agrégats (Lucas et al., 2003 ;Andersen et al., 2010, McKew et al., 2011).

Ce chapitre est décomposé en deux parties, l'une décrivant les résultats de l'analyse in situ et l'autre les résultats de l'analyse en laboratoire. Ces parties donnent lieu à des articles scientifiques pour Estuarine, Costal and Shelf Science, soumis dans le cas de l'étude in situ et préparé pour l'étude en laboratoire, elles sont présentées comme telles. salinity etc. (Langendoen, 1992;Van Maren et al., 2009;Van Rijn, 2016;Huguet et al., 2020). Numerous studies have been carried out on the physical factors that condition siltation in port areas. However, few are interested in the role of biotic factors in siltation processes. To our knowledge, between 2000 and 2020 only 4 articles are referred to it (research conducted on 680 articles on 15 April 2021, by combining on Scopus the key words: Mud, Siltation and Sediment with Port, Marina and Harbor). And among these 4 studies none addresses the role of macro-organisms in the formation of mud. However, research in other contexts shows that organisms, abundant under pontoons, such as bivalves and tunicates (Connell, 2000) could play an important role in the siltation process (Giles et al., 2006;Forrest et al., 2007;McKindsey et al., 2009;Wang et al., 2018).

These organisms all belong to the filter feeders' group: they are suspension feeders. Sediments sucked in by the filter feeders are aggregated during digestion in the feces or upstream, by the mucus, in the pseudo-feces then released (Beninger et al., 1999;Ward and Shumway, 2004). These rejections are called bioproducts. Filter feeders' bioproducts play an important role in the amount of mud; the small particles are aggregated into larger flocs that will sediment more efficiently (Giles et al., 2006;McKindsey et al., 2009;Wang et al., 2018). A study carried on mussel farm showed that the presence of mussels led to an increase in sedimentation two at five times higher (Weise et al., 2009). McKindsey et al. (2009) highlight that tunicates present on mussel lines tend to double the sedimentation rate. These bioproducts will also influence settling velocity (Walker et al., 2014;McKindsey et al., 2009); the agglomerates formed by these bioproducts are heavier and sink more rapidly through the water column. This change in speed also impacts the spatial distribution of mud (McKindsey et al., 2009). Sediments reach the bottom faster, which reduces their propagation distances (McKindsey et al., 2009).

These bioproducts have also an impact on the structure and composition of the mud (McKindsey et al., 2011;Walker et al., 2014;Wang et al., 2018). A study carried out on mud collected near mussel farms shows that the rate of erosion is higher in the presence of mussels; this would be linked in particular to changes in the composition of these mud (Walker et al., 2014).

The amount of bioproducts produced depends on the species (Fiala-Médioni, 1974;Hawkins et al., 1998;Ward and Shumway, 2004;McKindsey et al., 2009) and is related to the filtration rate (Hawkins et al., 1998;Ward and Shumway, 2004). The filtration rate varies according to the organism's metabolism, which is furthermore conditioned by environmental factors such as sediment supply, amount of organic matter, season, temperature or salinity (Ward and Shumway, 2004;Riisgård et al., 2014;Zuñiga et al., 2014, Ehrich andHarris, 2015).

Filter feeders appear, in some contexts, predominant in siltation processes. It is therefore important not to neglect their role in siltation of port areas. The aims of this study are to highlight the role of filter feeders in the siltation process in port areas and to understand the factors that influence their production in bioproducts. An experimental analysis was carried out in La Rochelle marina. It consisted in collecting and analyzing the bioproducts of the filter feeders using sediment traps fixed under the pontoons. The study was performed over a period of two months, at two distinct seasons, in order to know precisely the evolution of this production.

La Rochelle marina is the largest marina in Europe with its 70 hectares. Its maintenance requires the dredging of approximately 200.000 m 3 of mud per year (Direction départementale des Territoires et de la Mer de la Charente-Maritime, 2018). This makes it an ideal study site for studying the role of filter feeders in the siltation process in port areas. Moreover, it is divided into four basins with distinct filter feeders' communities and environmental conditions, which allows a detailed study of the environmental factors that influence the production of bioproducts.

IV.I.II. Materials and methods

IV.I.II.I. Study site

La Rochelle marina is located along the French Atlantic coast, in the central part of the Bay of Biscay (Fig. 1). This port was created in 1972 and is one of the largest marinas in the world, with some 5.000 moorings. The hydro-sedimentary dynamics of this port are described by Huguet et al. (2020). Five sampling points were selected in areas with different hydro-sedimentary profiles (Fig. 1) (Huguet et al., 2020):

-Pontoon 13 is characterized by strong tidal currents and significant siltation. Far behind the breakwater it is protected from winds and waves.

-Pontoon 43 is the most distant from the marina openings. At the back of the basin, the hydrodynamics are low and the siltation is constant and low.

-Pontoon 51 is located close to the channel but is protected by a breakwater. Hydrodynamics and siltation are significant.

-Pontoon 61 is close to an opening to the sea. It is also characterized by significant siltation and hydrodynamics are strongly influenced by the winds.

-The Capitainerie pontoon is in the center of the channel. Hydrodynamics are the strongest at this level. Siltation is constant and significant. During the two sampling periods, multiparameter YSI 6600 V2 probes are positioned under pontoons 43 and 51. A same probe is also placed under pontoon 13 during the summer. It provide temperature, oxygen, salinity and turbidity data. Meteorological and hydrodynamics data are also collected for all the campaigns (Table .1).

Table.1. Environmental variables of the study area and their sources.

During the second sampling period, an analysis of the sestonic charge is carried out to estimate the organic and mineral matter available for the filter feeders. For this purpose, at the port entrance, the day before each sampling a water sample is taken just under the pontoon with a horizontal Niskin bottle. The water is filtered on a 0.7μm gf/f filter and the collected sediments are analyzed according to the same protocol as for the sediment traps. This sampling is used to calibrate probes and models.

IV.I.II.IV. Data analysis

The production of bioproducts is studied at different scales. It is carried out by pontoon and between pontoons, but also between the campaigns and the seasons. The bioproduction will be analyzed as a whole through the dry matter produced and its composition through the percentage of organic matter. The results of the campaign 6 will not be presented here because the field conditions did not allow us to recover all the traps correctly.

All the statistical tests have been carried out using the software R (Version 3.6.3 "Holding the Windsock") with a rejection threshold of 5%. The data do not comply with any of the conditions of application of the parametric tests. The Wilcoxon-Mann-Whitney test is used for simple comparisons. For multiple comparisons, the Kruskal Wallis test and the Wilcoxon Pairwise post-hoc test are used.

The Pearson correlation test is used with a rejection threshold (r) of 0.5 to estimate the relationships between the average dry matter rate produced and environmental conditions.

IV.I.III. Results

IV.I.III.I. Preamble

For each season and for each pontoon the amount of dry matter in the controls is significantly lower than in the replicas. The average amount of total dry matter per trap is 9.45±10.6g for replicas and 1.81±2.85g for controls in winter; and 6.60±6.97g for replicas and 0.902±0.787g for controls in summer. The controls being organism-free, this allows us to verify that what we observe in the replica traps is indeed mainly related to bioproduction.

For both seasons, production is homogeneous within each pontoon. This allows us to compare the pontoons with each other.

All data presented hereafter will be expressed as the amount of matter produced by the organisms per square meter, i.e., the average material masses of the controls per pontoon are subtracted from those of each sample.

IV.I.III.II. Study of bioproduction

The amount of dry matter produced is different between pontoons in winter (chi-squared = 80.72, df = 4, p-value < 2.2e -16 ) and in summer (chi-squared = 118.29, df = 4, p-value < 2.2e -16 ).

For both seasons, the average amount of dry matter produced by the Capitainerie pontoon is significantly higher than that of the other pontoons; whereas, conversely, that of pontoon 43 is significantly lower (Fig. 4 A,B). The Captainerie pontoon produces on average 8 times more than pontoon 43 in winter and almost 10 times more in summer (Fig. 4 A andB).

For all the pontoons, the average dry matter production is different between winter campaigns (chi-squared = 87.65, df = 6, p-value < 2.2e -16 ) and between summer campaigns (chi-squared = 66.46, df = 7, p-value = 7.619e -12 ) (Fig. 4 C andD). However, this difference seems to be more pronounced for the winter season; A weekly cyclicity seems to be established with an alternating increase and decrease in average production (Fig. 4 C andD).

The average dry matter production is not different between the 2 seasons, either for the pontoons as a whole (W = 40431, p = 0.054) or per pontoon.

The amount of organic matter found in bioproducts is quite similar between pontoons (Fig. 4 A andB). In winter, they fluctuate from 11.97±2.65% for pontoon 61 to 15.97±4.09% for pontoon 43. In summer, they fluctuate from 15.53±6.2% for pontoon 61 to 19.32±6.33% for pontoon 13. For all pontoons, the amount of organic matter found in bioproducts is higher in summer than in winter (W = 12023, p-value < 2.2e -16 ). It is respectively 17.4±5.62% and 13.8±3.43%. The variation within a season is relatively low (Fig. 4 C and D), with organic matter amounts between 12.89±1.44% and 15.92±4.57% in winter campaigns and between 13.34±4.53% and 19,67±8,69% in summer campaigns. In red, the average dry matter produced per pontoon and their standard deviation.

For both seasons and for each species, production is not related to the size of the individuals (r ∈ [-0.5> < 0.5]).

For each species, the size of the individuals is not significantly different between seasons (Table .2), but the number of juveniles, all species combined, is almost 20 times higher in summer (W=56.5, p=0.02).

IV.I.III.III.II Abiotic factors

In winter, for all the pontoons bioproduction is positively correlated with the sediment concentration and the tidal range (r > 0.5) (Fig. 6 and Fig. 7). A marked weekly alternation of sediment flow is visible and seems to correspond to the observed production patterns (Fig. 6 and Fig. 7). The concentration of sediment is not uniformly distributed between the pontoons and as for the production, it is the Capitainerie pontoon that seems to be the most supplied and the 43 pontoon the least (Fig. 6). For the Capitainerie pontoon, which is the most exposed pontoon, production is also correlated with wind direction (t= 4.16, df = 40, r= 0.55).

For pontoon 43 the production is also related to other factors such as salinity (t= 3.95, df = 19, r= 0.67), the amount of dissolved oxygen (t= -4.40, df = 19, r= -0.71) and the wave height (t= 5.28, df = 48, r= 0.60).

In summer, production does not seem to be correlated with the selected factors (r ∈ [-0.5> < 0.5]). Except for the pontoon Capitainerie where production is correlated with sediment concentration and tidal range (t= 5.46, df = 54, r= 0.59 // t= 4.71, df = 54, r= 0.54) (Appendix.1).

IV.I.IV. Discussion

Filter feeders are all too often forgotten in sedimentary processes. In La Rochelle marina, if we extrapolate to the 15 km of pontoons that make up this port, filter feeders release nearly 3.2 tones of bioproducts per day (130 g/m 2 /d of dry matter). The distribution of these rejects is heterogeneous, both spatially and temporally. The factors influencing these distributions can be classified into two categories: organisms on the one hand and sediment availability on the other.

IV.I.IV.I. Filter feeders' contribution

The filter feeder populations are heterogeneously distributed in La Rochelle marina and the areas abundant in oyster and mussels seem to be the areas where bioproduction is the most pronounced. Thus, the hypothesis that bioproduction is species-dependent seems relevant. In this sense, a study by McKindsey et al. (2009) shows that sedimentation rates are influenced by the species present; sedimentation rates are doubled from 3.9g/d to 7.2g/d when tunicates are present on mussels (McKindsey et al., 2009). This study highlights the fact that it is interesting to investigate bioproduction not only on a species-by-species basis but also at community scale. However, given the small number of replicates available and the complexity of the filter feeder communities present under the pontoons we chose to look only at which species seemed to be most correlated with bioproduction and not at species associations.

The maximum filtration rate (found in literature) of a mussel (Mytilus edulis) is almost twice that of an oyster (Crassostrea gigas), respectively 0.014 m 3 /g/h (Riva and Massé 1983) and 0.007 m 3 /g/h (Ehrich and Harris 2015). Thus, it is expected that mussels will capture and release more sediment than oysters. This hypothesis is in accordance with the results of the present study which shows that the correlation between mussel presence and bioproduction is stronger than the correlation between oyster presence and bioproduction. This hypothesis also supports the fact that bioproduction is species dependent.

The amount of bioproduct formed is directly related to the filtration rate (Hawkins et al., 1998;Ward and Shumway, 2004) and the filtration rate is itself dependent on the metabolism of the organism which is in turn modulated by environmental conditions (Riisgård et al., 2014;Zuñiga et al., 2014;Ehrich and Harris, 2015). In the present study, for one of the pontoons the rate of bioproduct formed was related to salinity and oxygen levels. Oxygen is a basic requirement for metabolism so the fact that production rates are inversely correlated with oxygen levels seems coherent. Oxygen content is also used as a factor limiting the filtration rate in oysters in some models (Cerco and Noel, 2005). Salinity is also a factor affecting filtration rate Riisgård et al. (2014) show that filtration rate in two mussel species is closely related to salinity. A review written by Ehrich and Harris (2015) shows that salinity also has an impact on the filtration rate of oysters; in fact, several studies confirm our observations by showing that an increase in salinity will increase the filtration rate and vice versa (Powell et al., 1992;Cerco and Noel, 2005;Fulford et al., 2007). Lavaud and his collaborators go even further and show that changes in salinity have an impact on the filtration rate of oysters and that this disturbance of the filtration rate can even affect the growth and reproduction of organisms (Lavaud et al., 2017).

Studies on pearl oysters (Pinctada margaritifera) and mussels (Mytilus edulis) show that the rate of filtration and clearance are size dependent (Pouvreau et al., 1999;Jacobs et al., 2015). This result could explain the fact that bioproduction is correlated with the amount of oysters in winter but not in summer. Indeed, if we only look at the number of oysters, we can see that some areas rich in oysters are not very productive. But if we look at the size of the oysters in parallel, we notice that it is mainly small oysters that are located in areas that are not very productive in summer. This is probably linked to the hazard of recruitment; oyster larvae settle where they find support, but this is not necessarily the most suitable place for their survival. Long-term monitoring would provide a better understanding of the evolution of the communities and their relationship with bioproduction.

For each species and for each pontoon, the amount of matter produced is not dependent on the number of individuals present under the pontoons. If we take the example of mussels, we can see that they are 10 times more present in summer than in winter, yet the production is the same between the two seasons. Size is an important factor as we have seen previously and in summer the number of juveniles is important. However, mussels live for several years, so we expect to find a large proportion of the mussels present in winter in summer. This tends to show that production is not limited by the number of individuals but by another factor: the sediment availability?

IV.I.IV.II. The sedimentary contribution

The availability of sediments is the limiting factor for this bioproduction. For organisms to produce bioproducts, they must have a sedimentary input. Filter feeders do not create material, they remobilize it.

In the present study, it is shown that these sediment inputs are spatially and temporally heterogeneous and that filter feeder bioproducts are closely correlated with sediment availability. Indeed, if we look at the bioproduction on a seasonal scale, we notice that although the average quantity is relatively similar, the weekly distribution pattern is more marked in winter than in summer, which can be explained by the fact that the sediment concentration is more constant in summer. Similarly, the pontoon that produces the least (pontoon 43) is the pontoon that has the least sediment input and the pontoon that produces the most (Capitainerie pontoon) is the pontoon with the most input. Several studies show that the filtration rate of oysters and mussels is strongly influenced by this sediment input (Ward and Shumway, 2004;Ehrich and Harris 2015). For these two species, the filtration rate tends to increase up to a threshold with the sestonic charge (Ward and Shumway, 2004;Ehrich and Harris 2015) and is also modulated according to the size of the particles (Benniger et al., 1999;Ward and Shumway, 2004) and the organic input (Hawkins et al., 1998;Jacobs et al., 2015). This saturation and sorting phenomena are regulated by several mechanisms well documented in the literature (Ward and Shumway, 2004;Ehrich and Harris 2015;Jacobs et al., 2015). In the present study, the temporal step used for sampling and the lack of details on the quality of the available seston do not allow us to determine if these mechanisms are regularly used by the filter feeders.

If we look at the composition of the bioproducts, we can see that they contain a higher proportion of organic matter in summer than in winter. This result is in accordance with a study carried out in the Iberian Peninsula on mussels (Mytilus galloprovincialis) (Zuñiga et al., 2014). This difference would be related to the presence of plankton, which is more abundant and of higher nutritional quality in summer than in winter (Zuñiga et al., 2014).

Sediment concentation is conditioned by many environmental factors. On the Atlantic coast, one of the main factors related to sediment concentration is the tide (Van Rijn, 2016;Huguet et al., 2020). This explains the close correlation between the tidal range and the production rate. Huguet et al. (2020) show that wind and waves are also significant factors to be considered when studying the sediment concentration. This could explain the correlation between wind direction and bioproduction rate in the Capitainerie pontoon and between wave height and production in pontoon 43. The Capitainerie pontoon is in the fairway and is probably the most exposed to the wind, which could explain why it is the only one to be directly influenced by this factor. Pontoon 43 is the least productive pontoon, but it is also the pontoon whose production is the least variable, so it may be that small variations, such as the contribution made by the waves, are more easily observed.

IV.I.V. Conclusion

Understanding the factors that govern the production and the behavior of mud is a major issue in ports. In these hyper-anthropic environments where life seems to have no place, the roles of the organisms that live there are often ignored. However, significant communities grow, out of sight, protected by the pontoons and some, as highlighted here, play an important role in siltation processes: the filter feeders. These organisms are able to trap and remobilize a large amount of sediment: approximately 3.2 tons per day if we extrapolate our results to the scale of the port.

The study shows that production is modulated by many factors such as species, salinity, oxygen etc. However, in addition to their important capacities to collect and remobilize sediments, filter feeders also modify the physico-chemical properties of sediments (Walker et al., 2014;McLean et al., 2018;Wang et al., 2018). Thus, it is legitimate to ask what the future of these rejects is. How and in what way are they transformed? How will they react in the water column? Will they influence benthic communities, as shown in a study conducted on mussels in Quebec (Callier et al., 2009)? This study and all the questions it raise (and the list is not exhaustive) show us that the involvement of organisms such as filter feeders in the hydro-sedimentation and siltation processes must not be ignored.

IV.II. Role of three filter feeder species on marina's siltation processes under controlled conditions.

Vincent HAMANI a* , Isabelle BRENON a , Océane LEBON a , Zoulikha REZZOUG b , Laurence MURILLO a .

a UMR 7266 LIENSs, CNRS-La Rochelle Université, 2 Rue Olympe de Gouges, 17000, La Rochelle, France.

Abstract

Ports are among the most common urban developments and face many issues. One of the best known is siltation, which is both an environmental and an economic issue at the heart of current concerns. While the abiotic factors causing siltation such as tidal range, waves or meteorological conditions are well documented in the literature, this is not the case for the biotic factors. In this study, we investigated the role of three species of filter feeders particularly common in Europe's largest marina (the blue mussel Mytilus edulis, the variegated scallop Mimachlamys varia and European flat oyster Crassostrea gigas) in the behavior of the mud through a qualitative and quantitative analysis of their bioproducts. The quantity and composition of the sediments available for the organisms being the predominant factor in the production of bioproducts and to be as representative as possible of the sedimentary inputs of the port, six feeding protocols were used. The qualitative study was carried out by analyzing the carbohydrate and protein content of the bioproducts; these two compounds being responsible for the structure and cohesion of the aggregates. The qualitative analysis of the bioproducts, based on the determination of protein and carbohydrate concentrations, showed that these concentrations were lower in oysters than in mussels and scallops. This suggests that the mud produced under oyster communities would be more erodible than that produced under mussel or scallop communities. Oysters, with comparable dry mass, would also tend to release less bioproducts than the other two species studied. These results are nevertheless to be weighed by the fact that significant differences in terms of rejection and quantity of carbohydrate and protein are observed according to the environmental conditions. Key words: Port area, Siltation, Mud, Filter feeder, Bivalve, Carbohydrate, Protein, Organic matter.

IV.II.I. Introduction

Often ignored in sedimentary processes, organisms such as bivalves play a significant role in the formation of mud. They are filter feeders (suspensivorous) i.e. they suck in and filter the water in their environment to extract their food, mainly phytoplankton (Gosling, 2015;Holland, 2016). This feeding behavior leads them to interact with the sediments present in the water column. Indeed, the sediments present in the water column are sucked up by the filter feeders during feeding and are then grouped together during digestion in the feces or upstream, through the mucus, in the pseudofeces and are released in the form of bioproducts (Beninger et al., 1999;Ward and Shumway, 2004). These bioproducts will settle and contribute to the composition of the mud.

Several studies show that these organisms can have a significant impact on the amount of mud formed (Verwey, 1952;McKindsey et al., 2009;Weise et al., 2009, Hamani et al. 2021). To our knowledge, Verwey (1952) carried out the first quantification of bio-deposition by filter feeders. He estimated that about 275,000 tonnes of dry bioproducts were deposited annually in the Wadden Saea (Netherlands) by Cerastoderma edule and Mytilus edulis. Later studies in mussel farms showed that the presence of mussels led to a two-to-five-fold increase in sedimentation (Weise et al., 2009). This increase in the sedimentation rate at mussel farms is thought to be related to the fact that the agglomerates formed by the organisms' rejects are heavier and sink more rapidly in the water column (Walker et al., 2014;McKindsey et al., 2009).

The amount of bioproducts produced depends on the species (Fiala-Médioni, 1974;Hawkins et al., 1998;Ward and Shumway, 2004;McKindsey et al., 2009), the sediment concentration in the water column (Hamani et al., 2021), and is related to the filtration rate (Hawkins et al., 1998;Ward and Shumway, 2004). The filtration rate varies according to the metabolism of the organism, which is further conditioned by environmental factors such as season, temperature, salinity etc. (Ward and Shumway, 2004;Riisgård et al., 2014;Zuñiga et al., 2014, Ehrich andHarris, 2015). Bivalve bioproducts also have an impact on the structure and composition of the mud (McKindsey et al., 2011;Walker et al., 2014;Wang et al., 2018). Walker et al (2014) collected muds near mussel farms and show that the rate of erosion is higher in the presence of mussels; this is thought to be related to changes in the composition of these muds.

Siltation in a port area is a major concern for many ports that need to understand and manage it to allow safe navigation for boats. The role of bivalves in the siltation of this environment is little known, yet they are omnipresent on artificial harbour structures such as pontoons or pilings (Connell and Glasby, 1999;Connel, 2000;Holloway & Connel, 2002). The objective of the present study is to investigate, under conditions like those of Europe's leading marina (La Rochelle marina), the role of three bivalves Mytilus edulis (Linnaeus, 1758), Crassostrea gigas (Thunberg, 1793) and Mimachlamys varia (Linnaeus, 1758) in the constitution of the mud.

To focus on interspecific differences and to control environmental parameters, this study was conducted in the laboratory.

A previous study found that the predominant factor in bioproduct production was the concentration in the water column, i.e. the amount of sediment available to the organisms (Hamani et al. 2021). The present work was conducted under different feeding conditions. To be as representative as possible of the sediment inputs of La Rochelle marina, six feeding protocols were used. These protocols varying the total amount of sediment in a first step and the organic part of this sediment in a second step.

The study consisted of a quantitative and qualitative analysis of the bioproducts of the three most abundant bivalve species in La Rochelle marina under six feeding conditions.

The qualitative study was carried out by analysing the carbohydrate and protein content of the bioproducts. These two compounds are largely responsible for the structure and cohesion of the aggregates (Andersen et al., 2010;McKew et al., 2011;Malarkey et al., 2015;Kameda et Yohei, 2021).

IV.II.II. Material and methods

IV.II.II.I. Study site and species of interest

La Rochelle marina (France) is located in the central part of the Bay of Biscay, in the Pertuis d'Antioche. Created in 1972, it is the largest marina on the Atlantic coast since its expansion in 2014. Like many ports on the Atlantic coast, it is particularly affected by silting. La Rochelle marina has been the subject of several studies aimed at finding solutions to reduce and understand what causes this

IV.II.II.III. Feeding and sampling protocols

The sediment concentration and the organic matter rate are variable in La Rochelle marina, to have an accurate approach, these two variables were considered in the feeding protocol.

The sediment concentration values are obtained from the hydro-sediment model (Huguet et al., 2020). Three concentrations values (minimum, medium and maximum) were chosen to represent the different conditions in La Rochelle marina (Table 1).

The organic matter rate values (21%, 71%) are derived from a sampling campaign carried out in summer 2020 with a horizontal Niskin bottle. These percentages represent the average and maximum organic matter content in the water one meter below the pontoons. The minimum amount of organic matter measured in La Rochelle marina was 0%, in order not to damage the health of the organisms, this concentration is not studied. This value is obtained by considering the different tidal cycles; thus 104 samples were collected i.e. one every hour for 13 hours once a week for two months. The sampled water (2 liters) was filtered through a 0.7 μm gf/f filter and the collected sediments were dried at 60°C for 72 hours and weighed to obtain the total dry mass of each sample. An ignition loss was carried out for 5 hours at 550°C to obtain the mineral part. The organic part was calculated by subtracting the mineral part from the total dry mass.

In the feed solution, the mineral part was obtained by burnt sediment from the marina (550°c for 5h) and the organic part by Shellfish Diet 1800 Ó (SD 1800) a mixture of five marine microalgae, Isochrysis sp., Pavlova sp., Tetraselmis sp., Thalassiosira weissflogii and Thalassiosira pseudonana. The quantities of organic matter have been previously determined in grams of dry matter, they had to be converted into mL of solution (the dry weight of SD1800 is 8%, and 1 mL of SD 1800 is equal to 979.3 mg). Finally, the amounts of mineral and organic matter (in g and mL/L seawater, respectively) were adjusted to the volume of the aquaria (multiplied by 17L). The six different feeding protocols are presented in Table 1.

Table 1. Estimated sediment concentrations and amounts of organic matter in La Rochelle marina; and the corresponding volumes of organic matter and amounts of mineral matter used in the feeding protocols. Feeding and sampling protocols were established after optimizing feeding and sampling frequency. To maximize food consumption, the animals were fed every hour over 12-hour periods, using peristaltic pumps. Beyond this frequency, during the tests, food deposits were observed in the cages. A fasting period of three days is applied between each change of feeding protocol to avoid affecting the next protocol. Bioproduct samples were taken every day to preserve them. The test cases showed a decrease in the quantity and quality of bioproducts after 24 hours in the aquarium. For sampling, the bioproduct cages were carefully removed from the aquaria and the bioproducts were collected with a spatula and placed in a 2 mL microtube. Once collected, the samples were stored in a freezer (-20°). 288 samples were collected, i.e., 4 samples per aquarium and per condition.

Sediment

IV.II.II.IV. Samples analysis

Sample analysis is based on the adaptation of protocols allowing to qualify the stability of sediment layers or flocs structured by biofilms (Takahashi et al., 2009;Lavergne, 2014). The extracellular polymeric substances, mainly carbohydrate and protein, secreted by the microphytobenthos can bind cohesive and non-cohesive sediment particles, thus increasing the stability of the sediment (Sutherland et al., 1998;McKew et al., 2011, Malarkey et al., 2015;Kameda and Yohei, 2021). Studies have shown a strong inverse correlation between erodibility and the carbohydrate content of sediments (Lucas et al., 2003;Andersen et al., 2010). As these same compounds are abundant in bioproducts, their quantification allows to study what structures them. Takahashi et al (2009) proposed a protein and carbohydrate extraction protocol. Proteins and carbohydrates are present in two types, bounded and unbounded, in the samples. The bounded fraction corresponds to the fraction that can only be obtained by chemical action. While the unbounded or colloidal fraction corresponds to the part present in the soluble part of the sample.

IV.II.II.IV.I. Extraction

Although the colloidal and bound parts are treated separately, the results are expressed as total protein and carbohydrate concentration, i.e., the sum of the colloidal and bound concentrations.

The extractions were performed on 500 mL of sample, previously thawed and homogenized with a vortex. The colloidal part was obtained by centrifugation (3500 g for 10 minutes at 4°C). The colloidal part is contained in the supernatant obtained. The bounded part is extracted from the pellet using Dowex â ion exchange resin. In a first step, the resin and pellet solution were agitated at 40 oscillations per minute for 1 hour at 4°C. The solution was then centrifuged (3500 g for 10 minutes at 4°C). The bounded part is contained in the resulting supernatant.

IV.II.II.IV.II. Protein Assay

Protein assays were performed using the BCA assay in 96-well plates (Smith et al., 1985). One plate was used per day of sampling (i.e., 12 samples corresponding to the 12 aquariums). On each plate was a 12-point Bovine Serum Albumin (BSA) calibration range from 0 to 1.2 g/L, three replicates for the colloidal part and three replicates for the bound part for each sample. Seawater filtered to 0.22 micron was used to dilute the standards and samples. When performing the bicinchoninic acid (BCA1 Kit sigma) assay and associated protocol, 200 µL of a dye reagent (bicinchoninic acid, sodium carbonate, sodium tartrate and sodium bicarbonate in 0,1 NaOH mixed with Copper (II) Sulfate Pentahydrate 4% Solution), was added to 25 µL of sample in each well. The plate was incubated at 37 °C for 30 min in a thermal shaker, after which the absorbance of the solutions was evaluated at 562 nm. Protein concentrations were calculated using the average of the absorbance values of the three replicates and the calibration curve (with a correlation coefficient R 2 > 0.98).

IV.II.II.IV.III. Carbohydrate Assay

Carbohydrates assays were performed in 96-well-plates using the Dubois method (Dubois et al., 1956). In haemolysis tubes, 100 µL of 5 % phenol and 500 µL of 98 % sulphuric acid were added to 100 µL of sample. In haemolysis tubes, 100 µL of 5% phenol and 500 µL of 98% sulphuric acid were added to 100 µL of sample. After 30 minutes of incubation in the dark at room temperature, 200 µL of each tube was dispensed in triplicate into the plate wells. The plate was then read at 485 nm. Several calibration ranges at 12 points from 0 to 1 g/L of glucose were performed. Carbohydrate concentrations were calculated using the average of the absorbance values of the three replicates and the calibration curve (with a correlation coefficient R 2 > 0.96). Seawater filtered to 0.22 micron was used to dilute the standards and samples.

IV.II.II.IV.IV. Bioproducts quantification

Once the 500 µL of samples had been taken to determine protein and carbohydrate concentrations, the remaining volume of each sample was measured and are dried at 60°C for 72 hours, then weighed to obtain the total dry mass of each sample. An ignition loss is carried out for 5 -Under %OMmax conditions, oyster bioproducts were more concentrated in organic matter under maximum sediment concentration conditions than under medium sediment concentration conditions (post-hoc t-test, p-value = 0.007), i.e. 70% and 60% respectively (Fig. 2B, Table 2). Fig. 2. Mineral/organic matter ratios in oyster bioproducts according to the sediment concentration (minimum, medium and maximum). Under environmental conditions, medium organic matter (A) and maximum (B).

IV.II.III.I.II. Interspecies comparisons of bioproduct production and associated organic matter content under different environmental conditions of organic matter and sediment concentrations

The amounts of bioproducts produced were not significantly different between species for all sediment concentration conditions at %OMmed (Kruskal-Wallis, p-value > 0.05) (Table 2). At %OMmax oysters produced lower average amounts of bioproducts than scallops (Wilcoxon post-hoc test, pvalue = 1e-05) and mussels (Wilcoxon post-hoc, p-value = 6e-04) (Table 2). The average amounts of bioproducts released at %OMmax by scallops, mussels and oysters are 0.059±0.009g, 0.054±0.009g and 0.048±0.007g dry matter, respectively.

The rates of organic matter in bioproducts were different between scallops and oysters at %OMmed, minimum sediment concentration condition (Wilcoxon post-hoc test, p-value = 0.009).

Oysters had a higher proportion of organic matter in bioproducts than scallops, 66% and 52% respectively (Table 2). At %OMmax, organic matter levels were higher in oyster bioproducts at minimum and maximum sediment concentration conditions than in scallop (respectively, post-hoc ttest, p-value = 0.042; post-hoc t-test, p-value = 0.05) and mussel (respectively; post-hoc t-test, p-value = 0.025; post-hoc t-test, p-value = 0.004) bioproducts (Table 2, Fig. 3). No significant difference in total protein concentrations was found between the three species at %OMmed (Kruskal-Wallis, p-value > 0.05) (Table 3).

At %OMmax and maximum sediment concentration condition oyster bioproducts had lower total protein concentrations than scallop (Wilcoxon post-hoc test, p-value < 0.05) and mussel bioproducts (Wilcoxon post-hoc test, p-value < 0.05), respectively 405.92±249.21, 1660.01±804.39 and 1622.01±542.32 g/g dry matter. No significant difference was observed at %OMmax, minimum and medium sediment concentration conditions (Kruskal-Wallis, p-value > 0.05) (Fig 4 andTable 3). At %OMmed several significant differences in total carbohydrate concentrations in bioproducts were identified: -In oysters (Kruskal-Wallis, chi-square = 6.88, df = 2, p-value = 0.032) where total carbohydrate concentrations in bioproducts were lower under minimum sediment concentration conditions than under maximum sediment concentration conditions (Wilcoxon post-hoc test, p-value = 0.03) (Table 4).

-In scallops (Kruskal-Wallis, chi-square = 11.79, df = 2, p-value = 0.003) where total carbohydrate concentrations of bioproducts were higher under medium sediment concentration conditions than under minimum sediment concentration conditions (Wilcoxon post-hoc test, p-value = 0.009) and maximum sediment concentration conditions (Wilcoxon post-hoc test, p-value = 0.02) (Table 4).

-In mussels (Kruskal-Wallis, chi-square = 9.338, df = 2, p-value = 0.009), where total carbohydrate concentrations of bioproducts were lower under minimum sediment concentration condition than under maximum sediment concentration conditions (Wilcoxon post-hoc test, p-value = 0. 014) and medium sediment concentration conditions (Wilcoxon post-hoc test, p-value = 0.029) (Table 4).

At %OMmax, for all three species, total carbohydrate concentrations were significantly higher at the maximum sediment concentration conditions (ANOVA and Post-hoc t-test, p-value < 0.05), (Fig. 5,Table 4).

IV.II.III.III.II.II. Interspecies comparisons of total carbohydrate content under different environmental conditions of organic matter and sediment concentrations

No significant differences in total carbohydrate concentrations of bioproducts were found between the three species at %OMmed (ANOVA, p-value > 0.05) (Table 4)

At %OMmax oyster bioproducts had lower total carbohydrate concentrations than mussels and scallops for all sediment concentration conditions (Kruskal-Wallis and Wilcoxon post-hoc test, pvalue < 0.05) (Fig 6 ,Table 4) Fig. 6. Average total carbohydrate concentrations of bioproducts and associated standard deviation (in microgram carbohydrate per gram dry matter) by species under maximum environmental organic matter and minimum (A), medium (B) and maximum (C) sediment concentration conditions. * Statistically significant differences.

IV.II.IV. Discussion

Bivalves such as mussels, oysters and scallops are particularly present in port areas (Hamani et al., study in progress). These filter feeders, through their feeding behavior, have a strong interaction with the sediments present in the water column; the sediments are sucked up during feeding and the non-assimilated part, the bioproducts, is released into the environment. These bioproducts are aggregates of sediments, trapped in mucus or digestion products. These aggregates are denser than the sediments present in the water column and tend to settle more rapidly, thus impacting the distribution of the surrounding mud (Walker et al., 2014;McKindsey et al., 2009). This change in composition and shape also alter the cohesion of the surrounding mud (Walker et al., 2014).

The present study proposes to further understand the role of bivalves in mud composition by investigating their effects on the quantity and quality of mud produced by integrating the study of the overriding environmental factors in the marina (concentration and sediment composition) and an interspecific comparison.

IV.II.IV.I. Sampling and analysis

The analysis of the samples is based on the adaptation of protocols for qualifying the stability of sediment layers or flocs structured by biofilms (Takahashi et al., 2009;Lavergne et al., 2017). As protein and sugar concentrations are closely related to the cohesion of the sediments, their study allows us to determine the structure and texture of the mud and to analyse precisely what causes it (Malarkey et al., 2015;Kameda and Yohei, 2021). Kameda and Yohei (2021) show for example that a small amount of extracellular polymeric substances (corresponding to sugars and proteins), about 0.1% of the total weight, is sufficient to increase the internal cohesion of seabed sediments. Nevertheless, it would be interesting to qualify these changes using methods such as rheology, to understand precisely what these compositional changes entail in terms of sediment cohesion.

The main advantage of the method is that it allows the study of a large number of samples. This facilitates the analysis when several environmental factors are to be studied, as it is the case in our study.

IV.II.IV.II. Quantitative analysis and composition of bioproduction

Under the conditions considered, production is not statistically influenced by the feeding protocol. However, interspecific statistical differences are observed at maximum environmental organic matter content and not at medium environmental organic matter content. These incoherent results reveal the fact that production rates are highly variable by species and condition.

Disregarding the sediment concentration and the environmental organic matter conditions, the average production rate of oysters is significantly lower than mussels and scallops with respectively 0.045±0.008, 0.054±0.011, 0.055±0.017 gram of dry matter per day per aquarium. This result suggests that the quantities of bioproducts rejected and by extension the quantities of mud produced are directly influenced by the species present in the environment. This is in agreement with a study conducted in situ in the marina of La Rochelle which suggested a similar correlation between the rate of bioproducts collected and the presence of oysters and mussels (Hamani et al., 2021). The amount of bioproducts formed is directly related to the filtration rate (Hawkins et al., 1998;Ward and Shumway, 2004). The maximum filtration rate (found in the literature) of a mussel (Mytilus edulis) is almost twice that of an oyster (Crassostrea gigas), respectively 0.014 m3/g/h (Riva and Massé 1983) and 0.007 m3/g/h (Ehrich and Harris 2015). Mussels are expected to capture and release more sediment than oysters. This hypothesis is in agreement with the results of the present study and suggests that under the experimental conditions chosen, some of the food provided is not absorbed by the oysters. As the food supplied is very small, it does not remain trapped in the sampling nets (as observed in the control aquariums), and it is therefore difficult to quantify the proportion that the organisms effectively assimilate.

Although belonging to the same family, these organisms have different metabolisms and physiology (Gosling, 2015). It is therefore also possible that the fraction assimilated by oysters for their physiological needs is higher than that of the other two species.

In oysters, the rate of organic matter in bioproducts is influenced by environmental organic matter conditions and sediment concentration. The organic matter content is also significantly higher in oyster bioproducts than in scallops and mussels for high environmental organic matter conditions at minimum and maximum sediment concentrations.

These results show that the composition of bioproducts is variable between species and can be influenced by environmental factors such as feeding, as is the case for oysters under the controlled conditions.

These changes in the organic matter ratio can influence the size of the flocs formed and the associated sedimentation processes. Mietta et al. (2009) and Shakeel et al. (2021) show that sediments with a higher organic matter content generate larger flocs and larger flocs tend to settle faster and more efficiently (Fan et al., 2020). Thus, under the mentioned conditions, flocs related to oyster bioproducts would be larger than those of mussels and scallops and could settle more efficiently. However, additional analyses, such as fall velocity or structure analyses are needed to validate these results as floc sizes and settling velocities are influenced by many factors (Mietta et al. 2009;Moruzzi et al., 2020;Shakeel et al. 2021).

IV.II.IV.III. Protein and carbohydrate production in relation to environmental conditions and species

Sugar and protein production are dependent on environmental conditions and seem to be mainly related to the organic matter content of the environment. Indeed, under average environmental organic matter conditions (21%), the quantities of proteins and sugars formed in the bioproducts are identical for each species and for each sediment concentration. In contrast, under maximum environmental organic matter conditions (71%), significant differences are observed between species and between different sediment concentration conditions. This result suggests that the sediments and therefore the mud produced by the organisms will have different structures depending on the organic content of the environment.

It is difficult to interpret the differences in production under maximum organic matter conditions as they are so diverse depending on the species and sediment concentration. However, under conditions of maximum organic matter, oyster bioproducts had both significantly lower protein and carbohydrate concentrations than those observed in scallops and mussels. As these two compounds are closely related to sediment cohesion, mussel and scallop bioproducts, under high organic matter conditions, should result in more cohesive and less erodible sediments and muds than oysters (Malarkey et al., 2015;Kameda and Yohei, 2021).

IV.II.V. Conclusion

This study, conducted in laboratory, focuses on the role of three bivalves, commonly found in harbors, in the constitution of mud. Siltation is a major concern in harbors where the mud must be regularly dredged to avoid disturbing navigation

The results of the study suggest that the mud is impacted by both the species present in the environment and the environmental conditions to which the organisms are subjected. Indeed, among the three species studied, the oysters showed significant differences in terms of the quantity and quality of discharges produced. These differences suggest that the discharges produced by oysters are less abundant and less resistant to erosion than those of mussels or scallops. However, these discards are clearly modulated by the presence of organic matter in the environment.

Bivalve bioproducts are not the only constituents of muds and many factors can influence the organisms or bioproducts before they become part of the mud composition (temperature, pH, salinity etc.) (Mietta et al. 2009;Zuñiga et al., 2014;Ehrich and Harris, 2015;Shakeel et al. 2021). In addition, the mud containing these bioproducts is subject to distinct factors, such as the fact that its composition influences the benthic communities that live there (Callier et al., 2009). Thus, further studies are needed to understand the full implication of bivalve releases into the mud. However, the results of this study already highlight that the contribution of bivalves to mud formation should not be neglected.

Conclusion du chapitre IV

La compréhension des facteurs qui régissent la production et la composition des vases est un enjeu majeur pour les ports. Dans ces environnements hyper-anthropiques où la vie semble ne pas avoir sa place, les rôles des organismes dans les processus d'envasement est souvent ignorés. Pourtant, des communautés importantes se développent, à l'abri des regards, protégées par les pontons et certaines, comme mises en évidence ici, joue un rôle important dans les processus d'envasement : les filtreurs.

L'étude in situ a permis de montrer que la quantité totale de matière sèche (bioproduits) produite par les filtreurs est constante entre les saisons et est d'environ 140 g/m 2 /jour. A l'échelle du port de plaisance de La Rochelle, cela représenterait une production totale journalière de 3,2 tonnes (Figure 19). Cependant, il existe une variation de la quantité de matière sèche produite entre les pontons et entre les campagnes. Ceci est étroitement corrélé aux concentrations sédimentaires du port mais est également influencé par des facteurs tels que la salinité, l'oxygène, et le type d'espèce présentes.

L'étude en laboratoire à validée le fait que les vases formées sont impactées à la fois par les espèces présentes dans le milieu, leur type et aussi par les conditions environnementales auxquelles les organismes sont soumis (Figure 19).

Ces études ont permis de montrer qu'en plus de leurs importantes capacités à collecter et remobiliser les sédiments, les filtreurs en modifient les propriétés physico-chimiques. Cela est espècedépendant et est fortement modulé par la présence de matière organique dans l'environnement (Figure 19).

Parmi les trois espèces étudiées (l'huître Crassostrea gigas, la moule Mytilus edulis et le pétoncle Mimachlamys varia) l'huître a montré des différences significatives en termes de quantité et de qualité des rejets produits. Ces différences suggèrent que les rejets produits par les huîtres sont moins abondants et moins riche en protéines et en carbohydrates ; ce qui les rendrait moins résistants à l'érosion que ceux des moules ou des pétoncles.

Il est légitime de se demander quel est l'avenir de ces rejets. Comment et de quelle manière sont-ils transformés ? Comment vont-ils réagir dans la colonne d'eau ? Influenceront-ils différemment les communautés benthiques, comme le montre une étude menée sur des moules au Québec (Callier et al., 2009) ? Les résultats des études présentées ici et toutes les questions qu'elles soulèvent (et la liste n'est pas exhaustive) nous montrent que l'implication d'organismes tels que les filtreurs dans les processus d'hydro-sédimentation et d'envasement ne doit pas être ignorée.

Chapitre V Conclusion et perspectives

V.I. Conclusion générale

L'objectif de cette thèse est d'étudier ce socio-écosystème particulier qu'est l'environnement portuaire à travers un groupe clé : les filtreurs (bivalves et tuniciers). Ce travail se décompose en trois axes qui visent à déterminer la distribution de ces organismes dans le port de plaisance de la Rochelle (les Minimes) ; à étudier l'effet des deux contaminants, d'origine anthropique, communs dans cet environnement (le cuivre et le zinc) sur leur métabolisme ; et à étudier leur rôle dans le comportement des vases.

L'étude de la distribution et de l'abondance, par analyse photographique, des bivalves et des tuniciers du port de plaisance de la Rochelle a permis de montrer l'étendue de leurs communautés (Figure 20). L'environnement portuaire est dominé par la présence des Tuniciers si l'on ne considère que le nombre des individus. Cette prédominance peut s'expliquer par leur faible sensibilité aux polluants anthropiques et leur grande capacité d'adaptation (Chebbi, 2010, Bouchard et Bochard-Madrelle, 2018). La distribution des populations de bivalves et des tuniciers est très hétérogène dans le port de plaisance de la Rochelle, ce qui rend son étude difficile. Bien qu'aucune corrélation n'ait pu être mise en évidence, il semblerait que l'hydrodynamisme soit en partie responsable de leur répartition. Le bassin Tamaris étant à la fois le bassin comportant le plus fort hydrodynamisme (Huguet, 2020) et la plus grande densité d'organisme tout taxon confondu.

Deux recensements (2019-2020) ont pu être effectués pour cette étude. Le second a été effectué dans un contexte particulier puisqu'il a eu lieu un mois après la crise sanitaire engendrée par la Covid-19. Durant cette crise sanitaire, un confinement total, incluant une interdiction de navigation, a été appliqué, réduisant fortement la pression anthropique dans le port. Les résultats du second recensement montrent une augmentation significative du nombre de bivalves et notamment des pétoncles (Mimachlamys varia) ce qui pourrait refléter l'impact de la pression anthropique dans leur distribution. D'autant que, comme abordé dans le chapitre III, les pétoncles sont sensibles aux pressions anthropiques comme les éléments traces par exemple (Hamani et al., 2021 ;Ory et al., 2021).

En parallèle de ces travaux, une méthode d'identification des organismes par intelligence artificielle (IA) a été éprouvée. Cette méthode pourrait accélérer et simplifier les analyses (Gonzalez-Rivero et al., 2020). Les résultats obtenus sont encourageants car la méthode permet d'ores et déjà d'identifier deux des quatre taxons d'intérêts avec des taux de détections supérieurs à 80% et une robustesse des identifications de 98,8% pour les Ascidiacea et 86,4% pour les Mytilidae. L'IA « apprend » à reconnaitre les individus à la manière d'un cerveau humain et devrait donc améliorer ses résultats avec le nombre de données croissant et pour répondre à nos besoins d'analyse pour du suivi à long terme.

Les travaux portant sur les effets d'une exposition aigue (48h) à des contaminants tels que le cuivre et le zinc sur le métabolisme des pétoncles ont permis de mettre en évidence les effets basaux de ces contaminants anthropiques sur des organismes vivants en milieu portuaire. Ces études ont été effectuées à des concentrations identiques à celles rencontrées au maximum dans le port de plaisance de la Rochelle (2018), à savoir 82 μg/L pour le cuivre et 150 μg/L pour le zinc. Elles mettent en évidence l'action de ces deux composés sur différentes voies métaboliques impliquées dans de nombreuses fonctions biologiques, telles que l'osmorégulation, le stress oxydatif et le métabolisme énergétique. Le cuivre impacterait également des voies métaboliques liées à la reproduction et à des phénomènes d'apoptose (Figure 20).

Dans chacune de ces études, plusieurs dizaines de métabolites ont été modulés significativement par la présence des contaminants. Cependant seule une petite fraction, 28 pour le cuivre et 11 pour le zinc, a pu être identifiée. Cela s'explique notamment par le manque de données existant sur la physiologie de ces organismes et laisse présager du fait que les voies métaboliques impactées par ces contaminants sont plus nombreuses que celles déterminées.

L'influence des organismes filtreurs dans la composition des vases a été étudiée à travers deux analyses complémentaires. L'une in situ a permis de montrer leur importante capacité à capter et à remobiliser les sédiments présents dans la colonne d'eau, mais aussi de déterminer les facteurs environnementaux influençant cette production (Figure 20). La seconde, en laboratoire, a permis de discriminer le rôle des trois espèces de bivalves les plus communes du port des minimes (Mimachlamys varia, Crassostrea gigas et Mytilus edulis) dans la composition des vases en termes de qualité et de quantité ; dans différentes conditions environnementales limitantes déterminées par la première étude.

L'étude in situ a montré que la quantité totale de matière sèche (bioproduits) produite par les filtreurs est d'environ 3,2 tonnes par jour à l'échelle du port des Minimes (Figure 20). Cette production est variable à l'échelle des pontons et des campagnes d'échantillonnages et est étroitement corrélée aux concentrations sédimentaires du port. Elle peut être également influencée par des facteurs tels que la salinité, l'oxygène, et le type d'espèces présentes.

Les concentrations sédimentaires étant directement reliés au taux de matières organiques et minérales disponibles pour les organismes, l'étude en laboratoire a été effectuée en considérant les variabilités de matières organiques et minérales présentes dans l'environnement du port des Minimes. Ce travail a validé le fait que les vases formées sont impactées à la fois par les espèces présentes et par les conditions hydrosédimentaires auxquelles les organismes sont soumis.

Parmi les trois espèces étudiées en laboratoire, l'huître (Crassostrea gigas) a montré des différences significatives en termes de quantité et de qualité de produits rejetés. Ces différences suggèrent que les rejets produits par les huîtres sont moins abondants et moins riches en protéines et en carbohydrates ; ce qui les rendrait moins résistants à l'érosion que ceux des moules ou des pétoncles (Malarkey et al., 2015 ;Kameda and Yohei, 2021). Dans certaines conditions leurs rejets sont également plus riches en matière organique ce qui pourrait influencer la taille des flocs et les processus de sédimentation associés (Mietta et al. 2009, Shakeel et al. 2021).

Ces deux études montrent qu'en plus de leurs importantes capacités à collecter et remobiliser les sédiments, les filtreurs en modifient les propriétés physico-chimiques. Cela est espèce-dépendant et est fortement modulé par les facteurs hydrosédimentaires de l'environnement (Figure 20).

V.II. Perspectives

Les bivalves sont sessiles au stade adulte et ont une durée de vie de plusieurs années, les changements interannuels de population sont donc liés, à leur survie et au recrutement, mais pas aux mouvements des populations. Les juvéniles sont difficiles à identifier sur les images et sont donc négligés lors des analyses. Ainsi des suivis sur plusieurs années sont nécessaires pour comprendre ce qui contraint les populations. Ces suivis devront être mis en relation avec des variables pouvant impacter le recrutement ou la survie tels que l'hydrodynamisme, les bruits sous-marins, les conditions trophiques, la température et la présence de contaminants (Martel, 1993 ;[START_REF] Toupoint | Le succès de recrutement de la moule bleue: influence de la qualité de la ressource trophique[END_REF]Stanière et al., 2015 ;[START_REF] Jolivet | Validation of trophic and anthropic underwater noise as settlement trigger in blue mussels[END_REF][START_REF] Mesquita | Fatty acids profiles modifications in the bivalves Cerastoderma edule and Scrobicularia plana in response to copper sulphate[END_REF].

Le suivi des contaminants dans l'eau et les organismes semble d'autant plus pertinent que les études présentées dans le chapitre III montrent un effet du cuivre et du zinc sur plusieurs voies métaboliques de ces organismes et notamment sur des voies en relation avec la reproduction. Ce suivi permettrait également de voir si les quantités observées dans l'environnement sont influencées par la présence des organismes (Kim et al., 2017 ;McCann, 2018 ;Vozzo et al., 2021).

La présence des bivalves et des tuniciers modifie les communautés présentes dans l'environnement, en augmentant la richesse spécifique par exemple [START_REF] Borthagaray | Mussels as ecosystem engineers: their contribution to species richness in a rocky littoral community[END_REF]Bradford et al., 2020 ;Strain et al., 2020). Afin d'améliorer la compréhension que l'on a de l'écosystème portuaire il serait intéressant de voir comment se structurent ces interactions. Par exemple, savoir si les espèces associées sont influencées par la présence d'un bivalve plutôt qu'un autre ou par certaines communautés particulières.

Les différences entre les tailles des organismes n'étant pas significativement différentes entre les bassins, la présente étude ne s'est concentrée que sur le nombre d'individus présents et non sur la biomasse. Cependant, l'étude de la biomasse à d'autres échelles pourrait apporter des indications sur la capacité trophique de la zone et donnerait des indications sur les facteurs pouvant limiter la présence des organismes [START_REF] Héral | Approche de la capacité trophique d'un écosystème[END_REF]. Cette étude n'est cependant pas envisageable par l'analyse d'image, les photographies ne permettant qu'une analyse en deux dimensions ce qui est limitant pour étudier des communautés aussi entremêlées que celles rencontrées sous les pontons. Pour les moules, par exemple, seule la partie apicale où se situe les branchies est visible généralement, le reste étant logé entre d'autres organismes.

Contrairement aux autres organismes étudiés, les Ascidies ont une durée de vie de 3 mois à plusieurs années (Holland, 2016), une analyse à une échelle de temps plus fine est nécessaire si l'on veut comprendre les facteurs qui conditionnent leurs présences. Cependant, une fois encore cela n'est pas envisageable par analyse photographique, les eaux du port des Minimes étant trop turbides, 8 à 10 mois de l'année.

Lors des travaux effectués sur les effets des contaminants sur le métabolisme des organismes filtreurs, seuls deux éléments traces ont pu être étudiés, à une concentration bien spécifique et pendant un temps d'exposition déterminé. Cependant le cuivre et le zinc ne sont pas les seuls contaminants présents dans la colonne d'eau. Les études effectuées par les autorités du port de Minimes montrent la présence d'au moins huit éléments traces (CREOCEAN, 2018). La présence de ces éléments est extrêmement labile et est conditionnée tant par les rejets anthropiques, que par le comportement des éléments trace eux même [START_REF] Bussy | Mobilité des métaux dans un système fluvial urbain[END_REF] ; d'autant plus que les métaux ne restent pas sous forme dissoute, ils ont tendance à précipiter et à se fixer sur d'autres éléments [START_REF] Bussy | Mobilité des métaux dans un système fluvial urbain[END_REF]. Dans un premier temps il semble important d'analyser l'évolution in situ de ces contaminants afin de retracer au mieux la pression qu'ils exercent sur les organismes. Ensuite, afin de comprendre plus précisément l'influence de ces contaminants sur des organismes tels que les pétoncles, il serait intéressant de multiplier les études ; soit en changeant de contaminant, soit en étudiant l'effet d'un élément donné à différentes concentrations et à différents temps d'exposition, soit en regardant les effets combinés de ces contaminants. En effet, dans l'environnement portuaire, les organismes sont souvent exposés à plusieurs contaminants en même temps. Des études montrent que ces cocktails de contaminant peuvent avoir des effets additionnels, synergiques et même antagonistes [START_REF] Lawes | Contaminant cocktails: Interactive effects of fertiliser and copper paint on marine invertebrate recruitment and mortality[END_REF][START_REF] Dytrtová | Triazoles and aromatase: The impact of copper cocktails[END_REF]. Ils ne sont pas à négliger si l'on veut comprendre précisément ce que subissent les organismes dans l'environnent portuaire. Les conditions environnementales telles que la température et la salinité peuvent aussi s'ajouter aux effets des contaminants [START_REF] Deruytter | Salinity and dissolved organic carbon both affect copper toxicity in mussel larvae: Copper speciation or competition cannot explain everything[END_REF]Gamain et al., 2019). [START_REF] Deruytter | Salinity and dissolved organic carbon both affect copper toxicity in mussel larvae: Copper speciation or competition cannot explain everything[END_REF] montrent par exemple qu'une augmentation de la salinité peut entrainer une augmentation de la toxicité du cuivre sur les larves de moule (Mytilus galloprovincialis). Le port étant un milieu très complexe et très dynamique, il est bien entendu peu probable de pouvoir appréhender l'ensemble des interactions entre les organismes et les contaminants tant elles sont nombreuses.

Afin d'aller plus loin dans l'étude des interactions entre les contaminants et les organismes filtreurs, il serait intéressant d'inverser les rôles et de voir quelle est l'influence de ces organismes sur ces éléments. D'une part, comme souligné ci-dessus afin de voir si leur capacité à les bioaccumuler, pourrait significativement influencer leur présence dans la colonne d'eau (McCann, 2018). Une expérience menée dans le port de New-York propose à ce titre d'utiliser les huîtres pour diminuer la charge de contaminant dans les milieux portuaires (Kim et al., 2017 ;Vozzo et al., 2021). D'autre part, les organismes filtreurs jouent un rôle dans la composition des vases (Voir chapitre IV), il serait intéressant de comprendre si la présence des éléments traces dans les sédiments peut être influencée par la présence de ces organismes. Une étude menée sur les moule zébrées (Dreissena polymorpha) a mis en évidence le fait que leur présence a conduit à doubler le taux des éléments traces tels que le cuivre, le zinc et le nickel dans les sols [START_REF] Klerks | Effects of the exotic zebra mussel (Dreissena polymorpha) on metal cycling in Lake Erie[END_REF]. Cela peut s'expliquer par le fait qu'ils concentrent dans leur bioproduits les métaux présents dans la colonne d'eau, mais également par le fait que leur présence augmente le taux de sédimentation [START_REF] Klerks | Effects of the exotic zebra mussel (Dreissena polymorpha) on metal cycling in Lake Erie[END_REF].

Les travaux effectués pour étudier le rôle des organismes filtreurs dans la composition des vases ont mis en évidence le fait que ces organismes sont en interaction avec une part importante de sédiment ; en les aspirant lors de la prise alimentaire et en les rejetant sous forme de bioproduits. Cependant avant que ces bioproduits ne fassent partie intégrante de la vase ils sont expulsés dans la colonne d'eau où ils vont subir l'effet d'un bon nombre de variables environnementales. Ces rejets vont plus ou moins floculer et s'agréger avec d'autres particules, ce qui va changer leur composition mais aussi leur déplacement dans la colonne d'eau (Jarvis et al., 2005 ;[START_REF] Liu | Comprehensive review of floc growth and structure using electrocoagulation: characterization, measurement, and influencing factors[END_REF]. A contrario, ils vont aussi subir les effets des variables hydrodynamiques et se fragmenter (Jarvis et al., 2005 ;[START_REF] Liu | Comprehensive review of floc growth and structure using electrocoagulation: characterization, measurement, and influencing factors[END_REF]. Ces comportements sont contraints par des variables comme le pH, la température, la salinité, la présence de microalgues, les flux d'eau. (Xiao et al., 2007 ;[START_REF] Verney | Flocculation potential of estuarine particles: The importance of environmental factors and of the spatial and seasonal variability of suspended particulate matter[END_REF]Mietta et al., 2009 ;[START_REF] Kumar | Floc properties and settling velocity of San Jacinto estuary mud under variable shear and salinity conditions[END_REF]. L'étude de leur comportement en relation avec les variables du port de plaisance de la Rochelle est donc nécessaire pour comprendre pleinement comment les bioproduits vont évoluer avant de faire partie de la composition des vases.

Le comportement de ces bioproduits dans la colonne d'eau va également être influencé par leur structure et leur composition de base. Plusieurs études (Mietta et al., 2009 ;[START_REF] Larsen | Morphologic and transport properties of natural organic floc[END_REF] montrent par exemple que les flocs contenant une part plus élevée de matière organique, comme ceux produits (dans des conditions contraintes en laboratoire) par les huîtres de notre étude, seraient plus volumineux. Ces flocs de grandes tailles seraient également plus résistants à la fragmentation en raison de la présence de matière organique [START_REF] Eisma | Terrigenous Late Quaternary Sediment Components North and South of the Scotland-Greenland Ridge and in the Norwegian Sea[END_REF]Jarvis et al., 2005). Cette grande taille les conduirait aussi à sédimenter plus rapidement (Fan et al., 2020) ; d'autant que les flocs chargés en matière organique, ont tendance à s'agréger, formant ainsi des macroflocs qui se déposent encore plus rapidement [START_REF] Kranck | Macroflocs: production of marine snow in the laboratory[END_REF][START_REF] Kranck | The role of flocculation in the filtering of particulate matter in estuaries[END_REF]. Les deux études que nous avons effectuées nous donnent déjà des pistes sur leur composition (part de matière organique et minérale), mais des études plus poussées sur leur structure (taille, densité, composition minérale et organique) compléteraient nos données et nous informeraient sur le comportement qu'auront ces produits dans la colonne d'eau.

Plus la particule sédimente rapidement, plus elle se mélange aux vases du milieu. Une analyse de la vitesse de chute de ces particules, associée aux études de comportement énoncées ci-dessus, permettrait d'indiquer si les vases formées sous les pontons sont reliées directement au rejet des individus présents sur ces mêmes pontons ou si elles sont constituées d'un mélange de tous les rejets du bassin par exemple.

L'étude des bioproduits en laboratoire a permis de connaître la composition en carbohydrate et en protéine de nos bioproduits. Une étude In situ de ces compositions dans les pièges à sédiment (voir chapitre IV.I) et dans les vases présentes sous les pontons, mises en relation avec la distribution des organismes (Voir chapitre II) nous permettrait de voir si certaines espèces jouent un rôle plus important que d'autres dans l'environnement, ou si c'est l'influence de la communauté tout entière qui prédomine.

L'étude menée en laboratoire donne aussi une indication du comportement structural des bioproduits. Une étude de la rhéologie de ces rejets apporterait des indications supplémentaires sur ce que cela implique réellement en termes de cohésion et de texture des sédiments. Ces informations permettraient notamment d'optimiser les travaux d'entretien liés au désenvasement du port. En effet, les moyens employés pour éliminer les vases sont directement relié au comportement rhéologie de celle-ci. Par exemple dans le port des Minimes les vases les plus fluides sont remises en suspension et les plus cohésives sont draguées.

Enfin, si l'on veut avoir une compréhension complète du rôle des organismes filtreurs dans l'envasement, il faut tenir compte du comportement des vases contenant leurs bioproduits. En effet, au même titre que les flocs, les vases vont avoir des comportements différents et être sujettes à des phénomènes, de déformation, de compaction et d'érosion différents en fonction des variables environnementales et de leurs compositions (Migniot ,1968 ;Shakeel et al., 2021).

Pour aller encore plus loin, il serait intéressant d'étudier l'implication de ces bioproduits dans la mise en place des communautés benthiques (Callier et al., 2009 ;McKindsey, 2011). D'autant que ces communautés impactent également le comportement des vases par des phénomènes de bioturbation [START_REF] Krantzberg | The influence of bioturbation on physical, chemical and biological parameters in aquatic environments: a review[END_REF][START_REF] Mermillod-Blondin | The functional significance of bioturbation and biodeposition on biogeochemical processes at the water-sediment interface in freshwater and marine ecosystems[END_REF]Sarker et al., 2020).

V.II. Conclusion personnelle

Ce vaste projet pluridisciplinaire, qui vise à étudier un socio-écosystème à travers un groupe très spécifique, devrait permettre d'avoir une nouvelle compréhension de ces milieux fortement anthropisés, qui font maintenant partie du panel des écosystèmes qui dessinent nos côtes. Ce projet a émergé d'un désir d'apporter un regard nouveau sur un milieu que l'on méconsidère souvent, et a pour vocation d'essayer de lui redonner une place plus environnementale qu'utilitaire. Le choix des variables utilisées est discutable car leur intérêt est anthropocentré, ce qui pourrait paraître contradictoire avec l'approche choisie. Cependant, elles permettent, selon moi, à l'inverse d'appuyer sur le fait que l'Homme fait partie inhérente de cet écosystème. Il le façonne en créant des niches pour des organismes tels que les filtreurs, en y apportant des éléments traces, etc., et l'écosystème le contraint à son tour, comme nous l'avons vu avec la problématique de l'envasement.

Dans ces travaux, j'ai souhaité garder une approche factuelle, fondamentale et non dirigée. Je n'apporte pas de jugement de valeur et place l'Homme et ses actions au rang de variables ni plus ni moins. De même, les fonctions écosystémiques explicitées permettent simplement de souligner les interactions entre les filtreurs et leur environnement. Ce travail n'a pas pour vocation d'apporter des solutions concrètes à des problématiques tels que l'envasement ou les contaminations anthropiques mais cherchent à donner des pistes de compréhension à partir de connaissances académiques.

Vers une meilleure compréhension des écosystèmes portuaires : interactions entre les organismes filtreurs et leur environnement.

L'hyper-anthropisation, en particulier le long de nos côtes, a profondément modifié l'environnement. De plus en plus de structures, telles que les ports, forment des écosystèmes à part entière. Parmi la multitude d'espèces qui peuplent le port, un groupe semble particulièrement intéressant à étudier : les Filtreurs (bivalves et tuniciers). Ces organismes, par leurs modes de vie, ont une forte interaction avec l'environnement portuaire. En effet, en restant fixés sur les structures, ils subissent sans cesse les facteurs environnementaux qui caractérisent le port et leur mode d'alimentation, la filtration, les amène à être en contact avec une grande quantité d'eau et donc avec les éléments qui s'y trouvent. L'objectif de ce travail de thèse est d'étudier ce socioécosystème particulier qu'est l'environnement portuaire à travers ce groupe clé : les filtreurs. Ce travail par une approche pluridisciplinaire a permis :

-d'étudier et de cartographier les communautés de filtreurs présents dans le port de plaisance de la Rochelle ; montrant ainsi la complexité de leur communauté et le fait qu'elles seraient impactées par des facteurs anthropiques et hydrosédimentaires.

-d'analyser l'effet de deux contaminants très présents en milieu portuaire, le cuivre et le zinc, sur un organisme filtreur modèle : le pétoncle (Mimachlamys varia) ; et de montrer leur impact sur plusieurs voies métaboliques impliquées dans de nombreuses fonctions biologiques, telles que l'osmorégulation, le stress oxydatif, métabolisme énergétique, la reproduction et des phénomènes d'apoptose.

-de mettre en évidence le fait que les filtreurs interviennent dans la composition des vases en remobilisant les sédiments présents dans la colonne d'eau et en modifiant leurs propriétés physico-chimiques ; que cela est espèce-dépendant et fortement modulé par les conditions environnementales telles que le taux de matière organique.

-de développer plusieurs méthodes d'échantillonnage et d'analyse novatrice nécessaires pour appréhender cet environnement particulier.

Mots clés : Écosystème portuaire, filtreur, bivalves, tuniciers, bio-indicateur, espèces ingénieurs, vases.

A Better understanding of port ecosystems: interactions between filter-feeder organisms and their environment.

The hyper-anthropization, particularly along our coasts, has profoundly modified the environment. New structures, such as harbors, emerging, forming "true" ecosystems. Among the multitude of species inhabiting the port, one group seems particularly interesting to study: the filter feeders (bivalves and tunicat). These organisms have a strong interaction with the port environment due to their behaviour. Indeed, by remaining anchored to the structures, they are constantly subjected to the environmental factors that characterize the port and their feeding behavior, the filtration, leads them to be in contact with a large quantity of water and therefore with the elements that are in it. The objective of this thesis is to study this particular socio-ecosystem that is the port environment through this key group: the filter feeders. Through a multidisciplinary approach, this work, has allowed :

-to study and map the communities of filter feeders present in the marina of La Rochelle; showing the complexity of their community and the fact that they are impacted by anthropogenic and hydrosedimentary factors.

-to analyze the effect of two common contaminants in the port environment, copper and zinc, on the metabolism of a model filter-feeder organism: the scallop (Mimachlamys varia); and to show that they impacted several metabolic pathways involved in numerous biological functions, such as osmoregulation, oxidative stress, energetic metabolism, reproduction and apoptosis.

-to highlight the fact that filter feeders are involved in the composition of the mud by remobilizing the sediments present in the water column and by modifying their physico-chemical properties; and that is species dependent and is strongly modulated by environmental conditions such as the level of organic matter.

-to develop several innovative sampling and analysis methods needed to understand this particular environment.

Key words: Port ecosystem, filter feeder, bivalves, tunicates, bio-indicator, engineer species, mud

Figure 1 .

 1 Figure 1. Représentation d'un écosystème : biocénose, biotope et leurs interactions. (Créé avec Biorender.com) ................................................................................................................. Figure 2. Différents types d'interactions écologiques basés sur les effets bénéfiques, néfastes ou neutres sur les partenaires en interaction (Le Roux et al. 2020). ........................................ Figure 3. Les principaux facteurs anthropiques influençant le milieu marin (modifié par Amara, 2010 d'après Groom et al., 2006). ...............................................................................Figure 4. Vue aérienne du port de plaisance de la Rochelle (France). ..................................... Figure 5. Localisation géographique de la zone d'étude, le port des Minimes à La Rochelle (France). .................................................................................................................................... Figure 6. Sources de zinc pouvant affecter les eaux de ruissellement (California Stormwater Quality Association, 2014). ....................................................................................................... Figure 7. Profil bathymétrique du port de plaisance de La Rochelle en mai 2019 (Port de plaisance de La Rochelle, 2021) ................................................................................................ Figure 8. Modélisation de la vitesse moyenne en profondeur (m/s) générée, en présence de ponton, par un courant de flot (A), à marée haute (B), par un courant de jusant (C), à marée basse (D) (D'après Huguet, 2019). ............................................................................................ Figure 9. Concentrations journalières moyennes de sédiments dans le port de plaisance de la Rochelle au cours du cycle morte eau/ vive eau en janvier 2019. .......................................... Figure 10. Carte du Pertuis Charentais est des fleuves s'y déversant (www.hydro.eaufrance.fr). ..................................................................................................... Figure 11. Photographie in situ des trois espèces de bivalves les plus communes du port de plaisance de la Rochelle. ......................................................................................................... Figure 12. Anatomie de la moule et fonctionnement de la prise alimentaire ( ã Thierry Guyot). ................................................................................................................................................ Figure 13. Photographie in situ des trois espèces d'ascidie les plus communes du port de plaisance de la Rochelle. ......................................................................................................... Figure 14. Anatomie d'une ascidie. O : siphon inhalant, Br : branchie, MD : estomac, Kl : cloaque, A : siphon exhalant, Af : anus, G : système nerveux, GD : glande génitale, Gg : canal excréteur, Sf : stolon (https://doris.ffessm.fr/). ..................................................................... Figure 15. Représentation graphique des objectifs de travail. ............................................... Figure 16. Photographies prises sous les pontons du port de plaisance de la Rochelle (France). .................................................................................................................................. Figure 17. Étude, par analyse d'image, des communautés de bivalves et de tunicier dans le port de plaisance de La Rochelle. ........................................................................................... Figure 18. Étude par une analyse métabolomique non ciblée des effets du cuivre et du zinc, à des concentrations similaires à celles trouvées dans le port de La Rochelle, sur le métabolisme du pétoncle (Mimachlamys varia). ................................................................... Figure 19. Étude du rôle des organismes filtreurs dans la compostions des vases en milieu portuaire. Selon une analyse In situ et une analyse en laboratoire. .....................................Figure 20. Vers une meilleure compréhension des écosystèmes portuaires : interactions entre les organismes filtreurs et leur environnement. Résumé graphique des principaux résultats de l'étude. ..............................................................................................................

Figure 4 .

 4 Figure 1. Représentation d'un écosystème : biocénose, biotope et leurs interactions. (Créé avec Biorender.com) ................................................................................................................. Figure 2. Différents types d'interactions écologiques basés sur les effets bénéfiques, néfastes ou neutres sur les partenaires en interaction (Le Roux et al. 2020). ........................................ Figure 3. Les principaux facteurs anthropiques influençant le milieu marin (modifié par Amara, 2010 d'après Groom et al., 2006). ...............................................................................Figure 4. Vue aérienne du port de plaisance de la Rochelle (France). ..................................... Figure 5. Localisation géographique de la zone d'étude, le port des Minimes à La Rochelle (France). .................................................................................................................................... Figure 6. Sources de zinc pouvant affecter les eaux de ruissellement (California Stormwater Quality Association, 2014). ....................................................................................................... Figure 7. Profil bathymétrique du port de plaisance de La Rochelle en mai 2019 (Port de plaisance de La Rochelle, 2021) ................................................................................................ Figure 8. Modélisation de la vitesse moyenne en profondeur (m/s) générée, en présence de ponton, par un courant de flot (A), à marée haute (B), par un courant de jusant (C), à marée basse (D) (D'après Huguet, 2019). ............................................................................................ Figure 9. Concentrations journalières moyennes de sédiments dans le port de plaisance de la Rochelle au cours du cycle morte eau/ vive eau en janvier 2019. .......................................... Figure 10. Carte du Pertuis Charentais est des fleuves s'y déversant (www.hydro.eaufrance.fr). ..................................................................................................... Figure 11. Photographie in situ des trois espèces de bivalves les plus communes du port de plaisance de la Rochelle. ......................................................................................................... Figure 12. Anatomie de la moule et fonctionnement de la prise alimentaire ( ã Thierry Guyot). ................................................................................................................................................ Figure 13. Photographie in situ des trois espèces d'ascidie les plus communes du port de plaisance de la Rochelle. ......................................................................................................... Figure 14. Anatomie d'une ascidie. O : siphon inhalant, Br : branchie, MD : estomac, Kl : cloaque, A : siphon exhalant, Af : anus, G : système nerveux, GD : glande génitale, Gg : canal excréteur, Sf : stolon (https://doris.ffessm.fr/). ..................................................................... Figure 15. Représentation graphique des objectifs de travail. ............................................... Figure 16. Photographies prises sous les pontons du port de plaisance de la Rochelle (France). .................................................................................................................................. Figure 17. Étude, par analyse d'image, des communautés de bivalves et de tunicier dans le port de plaisance de La Rochelle. ........................................................................................... Figure 18. Étude par une analyse métabolomique non ciblée des effets du cuivre et du zinc, à des concentrations similaires à celles trouvées dans le port de La Rochelle, sur le métabolisme du pétoncle (Mimachlamys varia). ................................................................... Figure 19. Étude du rôle des organismes filtreurs dans la compostions des vases en milieu portuaire. Selon une analyse In situ et une analyse en laboratoire. .....................................Figure 20. Vers une meilleure compréhension des écosystèmes portuaires : interactions entre les organismes filtreurs et leur environnement. Résumé graphique des principaux résultats de l'étude. ..............................................................................................................

Figure 20 .

 20 Figure 1. Représentation d'un écosystème : biocénose, biotope et leurs interactions. (Créé avec Biorender.com) ................................................................................................................. Figure 2. Différents types d'interactions écologiques basés sur les effets bénéfiques, néfastes ou neutres sur les partenaires en interaction (Le Roux et al. 2020). ........................................ Figure 3. Les principaux facteurs anthropiques influençant le milieu marin (modifié par Amara, 2010 d'après Groom et al., 2006). ...............................................................................Figure 4. Vue aérienne du port de plaisance de la Rochelle (France). ..................................... Figure 5. Localisation géographique de la zone d'étude, le port des Minimes à La Rochelle (France). .................................................................................................................................... Figure 6. Sources de zinc pouvant affecter les eaux de ruissellement (California Stormwater Quality Association, 2014). ....................................................................................................... Figure 7. Profil bathymétrique du port de plaisance de La Rochelle en mai 2019 (Port de plaisance de La Rochelle, 2021) ................................................................................................ Figure 8. Modélisation de la vitesse moyenne en profondeur (m/s) générée, en présence de ponton, par un courant de flot (A), à marée haute (B), par un courant de jusant (C), à marée basse (D) (D'après Huguet, 2019). ............................................................................................ Figure 9. Concentrations journalières moyennes de sédiments dans le port de plaisance de la Rochelle au cours du cycle morte eau/ vive eau en janvier 2019. .......................................... Figure 10. Carte du Pertuis Charentais est des fleuves s'y déversant (www.hydro.eaufrance.fr). ..................................................................................................... Figure 11. Photographie in situ des trois espèces de bivalves les plus communes du port de plaisance de la Rochelle. ......................................................................................................... Figure 12. Anatomie de la moule et fonctionnement de la prise alimentaire ( ã Thierry Guyot). ................................................................................................................................................ Figure 13. Photographie in situ des trois espèces d'ascidie les plus communes du port de plaisance de la Rochelle. ......................................................................................................... Figure 14. Anatomie d'une ascidie. O : siphon inhalant, Br : branchie, MD : estomac, Kl : cloaque, A : siphon exhalant, Af : anus, G : système nerveux, GD : glande génitale, Gg : canal excréteur, Sf : stolon (https://doris.ffessm.fr/). ..................................................................... Figure 15. Représentation graphique des objectifs de travail. ............................................... Figure 16. Photographies prises sous les pontons du port de plaisance de la Rochelle (France). .................................................................................................................................. Figure 17. Étude, par analyse d'image, des communautés de bivalves et de tunicier dans le port de plaisance de La Rochelle. ........................................................................................... Figure 18. Étude par une analyse métabolomique non ciblée des effets du cuivre et du zinc, à des concentrations similaires à celles trouvées dans le port de La Rochelle, sur le métabolisme du pétoncle (Mimachlamys varia). ................................................................... Figure 19. Étude du rôle des organismes filtreurs dans la compostions des vases en milieu portuaire. Selon une analyse In situ et une analyse en laboratoire. .....................................Figure 20. Vers une meilleure compréhension des écosystèmes portuaires : interactions entre les organismes filtreurs et leur environnement. Résumé graphique des principaux résultats de l'étude. ..............................................................................................................

Figure 2 .

 2 Figure 2. Différents types d'interactions écologiques basés sur les effets bénéfiques, néfastes ou neutres sur les partenaires en interaction (Le Roux et al. 2020).

Figure 3 .

 3 Figure 3. Les principaux facteurs anthropiques influençant le milieu marin (modifié par Amara, 2010 d'après[START_REF] Groom | Principles of conservation biology Ed[END_REF].

Figure 7 .

 7 Figure 7. Profil bathymétrique du port de plaisance de La Rochelle en mai 2019 (Port de plaisance de La Rochelle, 2021)

  ) : -Le bassin Tamaris est situé entre les deux ouvertures du port. L'hydrodynamisme et l'envasement y sont importants. Protégé de la houle et des vagues par un brise-lames, son hydrodynamisme est fortement influencé par les courants de marée et par les vents (situation la plus proche du large). -Le bassin des Lazaret est caractérisé par de forts courants de marée et un envasement important. Il est protégé des vents et des vagues par un brise lame. -L'hydrodynamisme du bassin Bout-blanc est principalement influencé par sa proximité avec le chenal et donc par les courants de marée. L'envasement et les concentrations de sédiments sont plus prononcés à l'Ouest du bassin, l'Est étant protégé par la côte. -Le bassin Marillac est le plus éloigné des ouvertures du port. L'hydrodynamisme et l'envasement sont faibles et constants au sud du bassin. Au nord, les flux provenant du chenal augmentent l'hydrodynamisme et l'envasement.

Figure 9 .

 9 Figure 9. Concentrations journalières moyennes de sédiments dans le port de plaisance de la Rochelle au cours du cycle morte eau/ vive eau en janvier 2019.

Figure 10 .

 10 Figure 10. Carte du Pertuis Charentais et des fleuves s'y déversant (www.hydro.eaufrance.fr).

Figure 11 .

 11 Figure 11. Photographie in situ des trois espèces de bivalves les plus communes du port de plaisance de la Rochelle.

Figure 13 .

 13 Figure 13. Photographie in situ des trois espèces d'ascidie les plus communes du port de plaisance de la Rochelle.

Figure 14 .

 14 Figure 14. Anatomie d'une ascidie. O : siphon inhalant, Br : branchie, MD : estomac, Kl : cloaque, A : siphon exhalant, Af : anus, G : système nerveux, GD : glande génitale, Gg : canal excréteur, Sf : stolon (https://doris.ffessm.fr/).

Figure 16 .

 16 Figure 16. Photographies prises sous les pontons du port de plaisance de la Rochelle (France).

Fig. 2 .

 2 Fig.2. Design of the sampling method.

  Photo shootCoaxial cable

Fig. 3 .

 3 Fig.3. Example of image analysed by operator, with the box corresponding to the different taxon identified.

Fig. 4 .

 4 Fig.4. Architecture of a "one-pass" network presented as Backbone, Neck and Dense Prediction (head). The input image is provided to the first layer of the backbone, and the head part returns the detections in the form of bounding boxes. (Source: Bochkovskiy et al., 2020).

Fig. 5 .

 5 Fig.5. Distribution and abundance maps of Mytilidae (A), ascidiacea (B), Ostreïdae (C) and Pectinidae (D) for the 2019 campaign in La Rochelle marina. Average densities (ind./m 2 ) are estimated for each 20m of pontoon.

Fig. 6 .

 6 Fig.6. Distribution and abundance maps of Mytilidae (A), ascidiacea (B), Ostreïdae (C) and Pectinidae (D) for the 2020 campaign in La Rochelle marina. Average densities (ind./m 2 ) are estimated for each 20m of pontoon.

Fig. 7 .

 7 Fig.7. Relative abundance maps of tunicates (ascidiacea) and bivalves (Mytilidae, Ostreïdae and Pectinidae) for each portion of the pontoons (20m) of La Rochelle marina in 2019 (A) and 2020 (C). Maps of relative abundance of bivalves (Mytilidae, Ostreïdae and Pectinidae) for each portion of the pontoons (20m) of the La Rochelle marina in 2019 (B) and in 2020 (D).

  La reconnaissance d'image par intelligence artificiel (IA), permettrait de simplifier et d'accélérer les analyses de données(Rivero et al. 2020). Cette méthode éprouvée dans ce chapitre montre que l'IA n'est pas encore totalement optimisée pour analyser des données comme les nôtres. L'apprentissage effectué sur deux des quatre taxons d'intérêt montre des taux de détections supérieurs à 80% et une robustesse des identifications de 98,8% pour les Ascidiacea et 86,4% pour les Mytilidae. Ces résultats pertinents et le fait que l'apprentissage par l'IA s'améliore avec un nombre de données croissant, laissent présager une évolution positive de la méthode pour répondre à nos besoins d'analyse pour du suivi à long terme.

Figure 17 .

 17 Figure 17. Étude, par analyse d'image, des communautés de bivalves et de tunicier dans le port de plaisance de La Rochelle.

Figure 1 .

 1 Figure 1. Score plots of PCA and PLS-DA for positive mode (LC-Positive), negative mode (LC-Negative) of liquid chromatography. The dotted ellipse represented the confidence limit (95%) of Hotelling's T2 statistic. The control samples and the Cu-exposed samples are visually grouped in green and red ellipses, respectively.

Fig. 2 .

 2 Fig. 2. Box plots of the relative abundance of the 11 identified metabolites in Mimachlamys varia gills showing a significant difference between reference and Zn-exposed samples. Green plots represent the reference samples, red plots represent the zinc exposed samples. The mean value is given by the dark diamond-shaped symbol. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article).

Figure 18 .

 18 Figure 18. Étude par une analyse métabolomique non ciblée des effets du cuivre et du zinc, à des concentrations similaires à celles trouvées dans le port de La Rochelle, sur le métabolisme du pétoncle (Mimachlamys varia).

Fig. 1 .

 1 Fig.1. Study area, La Rochelle marina (Les Minimes). Surrounded by red: the sampled pontoons.

Fig. 3 .

 3 Fig.3. Photographs of ascidians (A), scallops (B), mussels (C) and oysters (D) under pontoons.

Fig. 4 .

 4 Fig.4. Averages of dry matter produced and associated standard deviation in two different seasons, per pontoon (A and B) and per campaign (C and D). ***statistically distinct average. In red the average fraction of associated organic matter and its standard deviation.

Fig. 5 .

 5 Fig.5. Average number of individuals and associated standard deviation, per pontoon and per species.In red, the average dry matter produced per pontoon and their standard deviation.

Fig. 6 .

 6 Fig.6. Maps of average environmental sediment concentration and average daily bioproduction (in red) for the 7 winter campaigns. The intensity of the red is proportional to the amount of bioproducts formed.

Fig. 7 .

 7 Fig.7. Top (A), average of dry matter produced and associated standard deviation per winter campaign for each pontoon. Bottom (B), evolution over the winter campaigns of two abiotic factors: the tidal range (in black). and the average sedimentation concentration (in red).

Fig. 4 .

 4 Fig.4. Average total protein concentrations of bioproducts and associated standard deviation by species (in microgram of protein per gram of dry matter) t maximum environmental organic matter concentration and maximum sediment concentration conditions. * Statistically significant differences.

Fig. 5 .

 5 Fig.5. Average total carbohydrate concentrations of bioproducts and associated standard deviation (in micrograms of carbohydrate per gram of dry matter) under maximum environmental organic matter conditions in relation to sediment concentration condition (minimum, medium and maximum), for oysters (A), scallops (B) and mussels (C). * Statistically significant differences.

Table 1 .

 1 Amplitudes et phases des principales ondes de marées du pertuis charentais d'après[START_REF] Nicolle | Modélisation des marées et des surcotes dans les Pertuis Charentais[END_REF].

	Onde	Amplitude (m)	Phase (°)
	O1	0.07	345
	K1	0.07	100
	N2	0.37	110
	M2	1.76	131
	S2	0.58	157
	M4	0.27	74
	M6	0.04	48

Table 2 .

 2 Average number of individuals per square meter and standard deviation, by basin and by taxon. Estimates by photography for the 2019 and 2020 campaigns. Missing records are replaced by the sign NA (Not Applicable).

			2019	2020
			Estimation by	Estimation by
			photography	photography
			Number (/m 2 )	Number (/m 2 )
		Mytilidae	127.19±639.25	198.88±308.57
		Ascidiacea	9228.49±5678.06	949.50±752.02
	Tamaris	Ostreïdae Pectinidae	119.39±312.36 3.14±8.20	230.16±407.21 0.13±1.71
		Mytilidae	0.00±0.00	3.51±27.87
		Ascidiacea	401.47±376.24	792.74±974.05
	Bout Blanc	Ostreïdae Pectinidae	12.92±83.25 0.61±4.13	45.57±153.62 1.17±12.97
		Mytilidae	1.57±34.03	12.13±102.30
		Ascidiacea	1199.50±1288.31	288.41±315.90
	Marillac	Ostreïdae Pectinidae	22.24±110.06 0.29±2.59	43.16±103.78 7.27±46.61
		Mytilidae	NA	101.29±542.31
		Ascidiacea	NA	959.44±1055.4774
	Lazaret	Ostreïdae Pectinidae	NA NA	26.45±95.21 7.28±30.19

  . Influence of suspended mussel lines on sediment erosion and resuspension in Lagune de la Grande Entrée, Îles-de-la-Madeleine, Québec, Canada. Aquaculture. https://doi.org/10.1016/j.aquaculture.2014.07.006 Wang, F., Zhou, Y., Wang, P., Xu, S., Liu, P., 2018. Potential role of scallops Argopecten irradians in deposition of particulate nutrient and trace elements in a eutrophic estuary, northern China. Aquac. Environ. Interact. 10, 135-147. Zúñiga, D., Castro, C.G., Aguiar, E., Labarta, U., Figueiras, F.G., Fernández-Reiriz, M.J., 2014. Biodeposit contribution to natural sedimentation in a suspended Mytilus galloprovincialis Lmk mussel farm

	in	a	Galician	Ría	(NW	Iberian	Peninsula).	Aquaculture	432.
	https://doi.org/10.1016/j.aquaculture.2014.05.026

Table 1

 1 dentified metabolites varying after 48 h-zinc exposure.

  b UMR 7356 LaSIE, CNRS-La Rochelle Université, Avenue Michel Crépeau, 1700, La Rochelle, France.

	Corresponding author: vincent.hamani@univ-lr.fr, +33 5.46.45.83.14. 2 Rue Olympe de Gouges, 17000, La
	Rochelle, France.

*

Table 3 .

 3 Average amount of total protein present in bioproducts and associated standard deviation (in grams per gram of dry matter) for each species, under different environmental concentrations of organic matter and sediment.

		%OMmed			%OMmax
	Conc.min	Conc.med	Conc.max	Conc.min	Conc.med	Conc.max
	1190.38±	1386.75±	1059.39±	994.05±	942.74±	405.92±
	Oyster
	664.81 g/g	717.22 g/g	1024.97 g/g	575.25 g/g	1415.66 g/g	249.21 g/g
	1368.39±	1979.98±	1241.71±	1626.36±	936.69±	1622.01±
	Mussel
	733.56 g/g	720.21 g/g	866.21 g/g	1452.88 g/g	445.37 g/g	542.32 g/g
	1590.26±	2061.73±	1223.17±	1484.76±	1032.12±	1660.30±
	Scallop
	1216.63 g/g	1118.38 g/g	1283.72 g/g	550.21 g/g	1587.19 g/g	804.39 g/g

IV.II.III.III.I.

II. Interspecies comparisons of total protein content under different environmental conditions of organic matter and sediment concentrations

Table 4 .

 4 Average amount of total carbohydrate present in bioproducts and associated standard deviation (in grams per gram of dry matter) for each species, under different environmental concentrations of organic matter and sediment.

		%OMmed			%OMmax
	Conc.min	Conc.med	Conc.max	Conc.min	Conc.med	Conc.max
	605.53±	1310.98±	855.52±	922.24±	731.86±	1497.64±
	Oyster
	245.86 g/g	907.50 g/g	219.13 g/g	361.17 g/g	485.54 g/g	774.63 g/g
	654.16±	1378.06±	996.33±	1178.43±	1320.64±	2257.80±
	Mussel
	285.10 g/g	806.37 g/g	242.75 g/g	429.99 v	419.24 g/g	958.10 g/g
	928.80±	1536.39±	907.31±	1345.52±	1563.69±	2426.44±
	Scallop
	1187.66 g/g	707.86 g/g	261.67 g/g	438.89 g/g	1067.44 g/g	1001.38 g/g

Remerciements Acknowledgements .................................................................................................................................... References .................................................................................................................................................. Appendix .................................................................................................................................................... IV.II. ROLE OF THREE FILTER FEEDER SPECIES ON MARINA'S SILTATION PROCESSES UNDER CONTROLLED CONDITIONS. .............. Abstract ...................................................................................................................................................... IV.II.I. Introduction ..................................................................................................................................... IV.II.II. Material and methods .................................................................................................................... IV.II.II.I. Study site and species of interest .............................................................................................................. IV.II.II.II. Experimental design .................................................................................................................................. IV.II.II.III. Feeding and sampling protocols .............................................................................................................. IV.II.II.IV. Samples analysis ..................................................................................................................................... IV.II.II.IV.I. Extraction ......................................................................................................................................... IV.II.II.IV.II. Protein Assay ................................................................................................................................... IV.II.II.IV.III. Carbohydrate Assay ........................................................................................................................ IV.II.II.IV.IV. Bioproducts quantification ............................................................................................................. IV.II.II.V. Statistical analysis ..................................................................................................................................... IV.II.III. Results ............................................................................................................................................

IV.II.III.I. Quantitative analysis of bioproduction .................................................................................................... IV.II.III.I.I. Comparisons by species of bioproduct production and associated organic matter content under different environmental conditions of organic matter and sediment concentrations ...................................... IV.II.III.I.II. Interspecies comparisons of bioproduct production and associated organic matter content under different environmental conditions of organic matter and sediment concentrations ...................................... IV.II.III.III. Qualitative analysis of bioproduction ..................................................................................................... IV.II.III.III.I. Protein concentrations .................................................................................................................... IV.II.III.III.I.I. Comparisons by species of total protein content under different environmental conditions of organic matter concentrations and sediment concentrations .......................................................................... IV.II.III.III.I.II. Interspecies comparisons of total protein content under different environmental conditions of organic matter and sediment concentrations ................................................................................................... IV.II.III.III.II. Carbohydrate concentrations ......................................................................................................... IV.II.III.III.II.I. Comparisons by species of total carbohydrate content under different environmental conditions of organic matter and sediment concentrations ............................................................................................... IV.II.III.III.II.II. Interspecies comparisons of total carbohydrate content under different environmental conditions of organic matter and sediment concentrations ............................................................................. .II.IV. Discussion ......................................................................................................................................

IV

Acknowledgements

We gratefully thank the Marina of La Rochelle for their assistance in particularly for the data transmission and the "Musée Mer Marine Bordeaux" for the involvement in the V. HAMANI PhD. This work has also been supported by the French Ministry of Higher Education and Research, the European Regional Development Fund, the regional state plan and the National Centre for Scientific Research.

Acknowledgment

We gratefully thank the Marina of La Rochelle for their assistance in particularly for the data transmission and the "Musée Mer Marine Bordeaux" for the involvement in the V. HAMANI doctorate.

Acknowledgements

We gratefully thank E. Dubillot (from laboratory "Littoral Environ-nement et Soci ét és" (LIENSs), UMR 7266, CNRS-Universit é de La Rochelle, 2 rue Olympe de Gouges, F-17042 La Rochelle Cedex 01, France) for technical assistance. We also thank the Marina of La Rochelle for their assistance in particularly for the data transmission and the "Mus ée Mer Marine Bordeaux" for the involvement in the V. HAMANI PhD.

Funding sources

Funding for this work came from the following separate sources: (i) Contrat de Plan Etat-R égion FEDER and the CNRS ECONAT Axe 1 -Ressources Marines Littorales: qualit é et éco-valorisation and Axe 2 -Gestion Int égr ée des Zones Littorales et Portuaires (ii) French Ministry of Higher Education, Research and Innovation for doctoral grant of V. Hamani (Minist`ere de l'Enseignement sup érieur, de la Recherche et de l'Innovation, MESRI).

Acknowledgements

We gratefully thank the Marina of La Rochelle for their assistance in particularly for the data transmission and the "Musée Mer Marine Bordeaux" for the involvement in the V. HAMANI PhD. This work has also been supported from bodies such as the French Ministry of Higher Education and Research, the European Regional Development Fund, the regional state plan and the National Centre for Scientific Research.

Acknowledgements

We gratefully thank the Marina of La Rochelle for their assistance in particularly for the data transmission and the "Musée Mer Marine Bordeaux" for the involvement in the V. HAMANI PhD. This work has also been supported from bodies such as the French Ministry of Higher Education and Research, the European Regional Development Fund, the regional state plan, la Rochelle university and the National Centre for Scientific Research.

Cette thèse a été

Funding

Funding for this work came from the following separate sources: (i) Contrat de Plan Etat-Région FEDER and the CNRS ECONAT Axe 1-Ressources Marines Littorales: qualité et éco-valorisation and Axe 2-Gestion Intégrée des Zones Littorales et Portuaires (ii) French Ministry of Higher Education, Research and Innovation for doctoral grant of V. Hamani (Ministère de l'Enseignement supérieur, de la Recherche et de l'Innovation, MESRI).

Data Availability Statement

Data is contained within the article.

Chapitre III

Effet de facteurs prépondérants dans l'environnement portuaire, les éléments traces, sur le métabolisme des organismes filtreurs

Ce chapitre présente les résultats de nos recherches sur l'effet des deux éléments traces les plus présents dans le port de plaisance de La Rochelle, Le cuivre et le zinc, sur le métabolisme d'une espèce modèle, le pétoncle panaché (Mimachlamys varia).

Ce travail a été réalisé en laboratoire, sur des organismes exposés pendant 48h à des concentrations environnementales en cuivre et en zinc (respectivement 82 μg/L et 150 μg/L). Les analyses sont effectuées sur les tissus branchiaux, premiers lieux d'échange entre l'organisme et l'environnement.

Une approche métabolomique non ciblée par chromatographie liquide à ultra-haute performance et spectrométrie de masse à haute résolution (UHPLC-HRMS) a été choisie pour étudier l'effets des éléments traces sur le métabolisme des pétoncles. Cette méthode offre un haut niveau de sensibilité et permet d'étudier l'ensembles des voies métaboliques sans discrimination ; ce qui permet d'avoir une idée globale et précise de l'effet des éléments traces sur le métabolisme des organismes.

Ce chapitre est décomposé en deux parties : la première expose les résultats de l'analyse des effets de cuivre sur le métabolisme du pétoncle et la seconde les effets du zinc. Ces parties ayant données lieux à des publications scientifiques dans les journaux Metabolites et Comparative Biochemistry and Physiology, elles sont présentées comme telles.

Author Contributions

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Conflicts of Interest

The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

IV.I. The forgotten ones from the ports:

The filter feeders at the heart of siltation processes.

Abstract

Siltation is a major concern in the dynamic and complex ecosystems which are the ports. The mud must be regularly dredged to avoid disturbing navigation. The sediments are carried by the waters entering in the port and are partially trapped by the harbor structures. The siltation is conditioned by many environmental factors, which are well described in the literature: sediment inputs, internal and external hydrodynamics, weather etc. Numerous studies have been carried out on the physical factors that condition siltation in port areas. However, few are interested in the roles of biotic factors in the formation of mud. Though, research in other contexts shows that organisms abundant under pontoons, such as bivalves and tunicates play an important role in this siltation process. These organisms all belong to the filter feeders' group: they are suspension feeders. The sediments sucked in by the filter feeders are aggregated during digestion in the feces or upstream, by the mucus, in the pseudo-feces. These rejections, called bioproducts, settle more efficiently and are involved in the composition of mud. The aims of this study are to highlight the role of filter feeders in the siltation process in port areas and to understand the factors that influence their production in bioproducts. To investigate the role of the filter feeders in siltation processes, an experimental analysis was carried out in the largest marina in Europe (La Rochelle, France). It is divided into four basins with distinct filter feeders' communities and environmental conditions, which allows a detailed study of the environmental factors that influence the production in bioproducts. This analysis consisted in recovering and studying the bioproducts of the filter feeders using sediment traps fixed under the pontoons. To explore the evolution of this biological production sixteen campaigns were carried out from January to March 2020 and May to July 2020. The total amount of dry matter produced is constant between seasons and is approximately 130 g/m 2 /d. Marina-wide, this would represent a total daily production of 3.2 tons. However, this production varies spatially and temporally in relation with marina hydrodynamics and the organisms involved (species, metabolism, etc.). The latter are also influenced by factors such as salinity and dissolved oxygen.

Keywords: Siltation, Port, Mud, Filter feeders, Bivalves, Ascidians.

IV.I.I. Introduction

Ports are dynamic socio-ecosystems in perpetual evolution, tugged on the one hand by environmental conditions and on the other hand by anthropic developments. Sediments and their flow are at the heart of this turmoil. The sediments are carried by the waters entering in the port (Eysink, 1989;Van Rijn, 2016) and are partially trapped by port infrastructures (Van Maren et al., 2009;Van Rijn, 2016;Huguet et al., 2020). These sediments are part of the siltation process and must be regularly dredged to avoid disturbing navigation. This siltation is conditioned by many environmental factors, widely described in the literature: sediment inputs, internal and external hydrodynamics, weather,

IV.I.III.III. Factors influencing bioproduction

IV.I.III.III.I The filter feeders

For both seasons the production is not related to the number of organisms present under the pontoons (winter: t= 2.98, df= 58, r = 0.36; summer: t= 1.54, df= 58, r = 0.19). Indeed, the average production is similar in winter and summer, yet the number of individuals present under the pontoons is 4 times higher in summer (Fig. 5 and Table .2).

Table.2.

The average number of individuals and their size, as well as the average number of juveniles, collected under the pontoons for each season.

Production appears to be species dependent (Fig. 5). It is more important in areas where mussels are present in winter (t= 5.38, df= 13, r = 0.83) as well as in summer (t=2.57, df= 13, r = 0.58). Production is also correlated with the presence of oysters in winter (t= 2.34, df= 13, r = 0.54).

Appendix

Appendix.1. Maps of average environmental sediment concentration and average daily bioproduction (in red) for the summer campaigns. The intensity of the red is proportional to the amount of bioproducts formed.

hours at 550°C to obtain the mineral part. The organic part is calculated by subtracting the mineral part from the total dry mass. The amount of bioproducts released (in g dry matter per day), the mineral and organic part were determined keeping in mind the 500 µL previously pipetted for assays.

IV.II.II.V. Statistical analysis

All the statistical tests and graphs have been carried out using the R software (Version 3.6.0) (R Core Team, 2019). All values were averaged by aquarium replicates (3 per species) and sampling (4 per week for each aquarium). To highlight significant differences between the three species, ANOVA tests (or Kruskal-Wallis tests when the application conditions were not met) followed by post-hoc ttests (or Wilcoxon Pairwise post-hoc tests) were applied with rejection threshold (a) < 0.05.

IV.II.III. Results

IV.II.III.I. Quantitative analysis of bioproduction

IV.II.III.I.I. Comparisons by species of bioproduct production and associated organic matter content under different environmental conditions of organic matter and sediment concentrations

For each of the three species studied, the amount of bioproducts formed was not influenced by the feeding protocol (Kruskal-Wallis and ANOVA, p-value > 0.05) (Table 2).

Table 2. Average amount of dry matter produced with standard deviation (in g of dry matter per day and per tank) and the associated average and standard deviation ratio of organic matter, for each species, under different environmental concentrations of organic matter and sediment. Organic matter rates in mussel and scallop bioproducts were not significantly different between feeding conditions (ANOVA, p-value > 0.05) (Table 2). However, significantly different rates were observed in oysters:

-Under %OMmed conditions, oyster bioproducts were more concentrated in organic matter under minimum sediment concentration conditions than under medium sediment concentration conditions (post-hoc t-test, p-value = 0.039), i.e. 66% and 56% respectively (Fig. 2A, Table 2). For each of the three species studied, at %OMmed, total protein concentrations were not significantly influenced by sediment concentration conditions (Kruskal-Wallis and post-hoc p-values > 0.05) (Table 3). At %OMmax, a significant difference was revealed:

-In oysters (Kruskal-Wallis, chi-square = 6.794, df = 2, p-value = 0.033) where total protein concentrations of bioproducts were lower under maximum sediment concentration conditions than under minimum sediment concentration conditions (Wilcoxon post-hoc test, p-value = 0.021) (Table 3).

-In scallops (Kruskal-Wallis, chi-square = 11.812, df = 2, p-value = 0.003) where total protein concentrations of bioproducts were lower under medium sediment concentration conditions than under minimum sediment concentration conditions (Wilcoxon post-hoc test, p-value = 0.002) and under maximum sediment concentration conditions (Wilcoxon post-hoc test, p-value = 0.017), i.e., protein concentrations: minimum sediment concentration > maximum sediment concentration > medium sediment concentration (Table 3).

-In mussels (Kruskal-Wallis, chi-square = 8.362, df = 2, p-value = 0.015), total protein concentrations of bioproducts were lower under minimum sediment concentration conditions than under maximum sediment concentration conditions (Wilcoxon post-hoc test, p-value = 0.011) (Table 3).