Microfitoplancton y microfitobentos en sistemas litorales. Diversidad, ecología e implicaciones en el ciclo biogeoquímico del silicio

Coastal microphytoplankton and microphytobenthos. Diversity, ecology and implications in silicon biogeochemical cycle

Arianna Bucci, Septiembre 2010

Universitat de Barcelona Facultad de Biología, Departamento de Ecología Doctorado en Ecología Fundamental y Aplicada, Bienio 2005-2006

Microfitoplancton y microfitobentos en sistemas litorales. Diversidad, ecología e implicaciones en el ciclo biogeoquímico del silicio

Coastal microphytoplankton and microphytobenthos. Diversity, ecology and implications in silicon biogeochemical cycle

Tesis Doctoral Presentada por Arianna Bucci Para optar al título de Doctor por la Universitatat de Barcelona

Director Co-directora Dr. Manuel Maldonado Barahona Dra. Zoila Velásquez Forero (Centro d’Estudios Avanzados de (Centro d’Estudios Avanzados de Blanes - CSIC) Blanes - CSIC)

Tutora Dra. Montserrat Vidal Barcelona, Universitat de Barcelona

Agradecimientos

He esperado hasta el último momento para redactar los agradecimientos porque quería tener una visión del conjunto de lo que han sido mis 4 años en Blanes y en el CEAB con cierto distanciamiento emocional. Por lo visto, debería haber esperado más, pero ya tenía fecha para la defensa...

Lo siento por las personas más cercanas, que leerán estos agradecimientos con alguna expectativa, pero os voy a avisar, lo mejor de mi y de mi cariño hacia vosotros no está en esta tesis, ni en estos últimos 4 años, ni, por supuesto, en estas páginas. Por eso, tampoco se la dedico a nadie, prefiero dedicar algo que se parezca más a esa versión entusiasta y positiva de mí que tiene que quedar en algún lugar...

Sin embargo, no puedo decir que no estoy orgullosa del resultado final de mi trabajo, porque sé lo que ha costado.

El trabajo de estos años no hubiese sido posible sin la ayuda económica del Gobierno de España, cuya beca FPU financió los 4 años de tesis y las estancias breves. Las investigaciones realizadas han sido posibles gracias a la financiación por parte del Smithsonian Caribbean Coral Reef Ecosystems Program (2005-2006, CCRE contribution number 871), de dos proyectos del Gobierno de España (CTM2005- 05366/MAR; BFU2008- 00227/BMC), y de la financiación por parte del grupo de investigación dirigido por el Dr. Ragueneau (LEMAR-IUEM).

Agradezco a mi director, el Dr. Manuel Maldonado, por haberse atrevido a dirigir una tesis que trata de temas tan alejados de los con los que tiene más confianza, sus queridas esponjas. Gracias por su entusiasmo al contar sus descubrimientos y anécdotas, por su tiempo, por incluirme en sus proyectos, por traerme las muestras de Belize, por participar en los muestreos de Blanes y por dejarme utilizar sus equipamientos. En particular, gracias por estar siempre disponible cuando llamaba a su puerta y por sentarse conmigo para enseñarme a escribir artículos científicos.

Gracias a Zoila Velásquez, la co-directora, por el tiempo y la paciencia que me dedicó, hace ya 4 años, para introducirme al mundo de la taxonomía del fitoplancton, ayudándome a reconocer especies donde yo solo veía granos de arena, palitos y bolitas. Y también por la cercanía, el trato humano y los consejos sobre la vida.

Gracias a la tutora, Montserrat Vidal, por su disponibilidad y cortesía y por haberme aceptado como estudiante.

Muchas gracias a Antonio Cruzado, por sus comentarios sobre los estudios de investigación llevados a cabo, por poner a mi disposición el microscopio, con el que he pasado tantas horas, y el CTD, por compartir su experiencia y por las conversaciones muy instructivas acompañando el café.

Una serie de personas han aportado ideas y mejoras a mi trabajo, a veces durante charlas informales en los pasillos o en los laboratorios del CEAB. Seguramente olvidaré nombrar a alguien y lo siento, pero no por no estar explícitamente citados no tienen mi reconocimiento. Agradezco en particular a Raffaele Bernardello, Jean- Christophe Auguet, Gilberto Cardoso, Sergi Pla, Paola Mura, Miquel Ribot, Carlos Rivera, David Soto, Romero Roig, Dani Von Schiller, Nuria Teixido, Marta Sales, Albert Barberán y Antoni Fernández. I also thank Klaus Rützler and the anonymous reviewers of the study carried out in Belize for helpful comments.

Gracias a Laura Arín, Celia Marrasé, Josep M. Gasol, Maximino Delgado, Olivier Herlory por materiales y consejos.

Gracias al personal técnico del CEAB por hacer posible el trabajo de investigación, en particular a Carmen Carmona, por introducirme al funcionamiento de los laboratorios y por ser una compañera de despacho muy divertida; a Susana Pla, por los análisis de nutrientes; a Roser Ventosa (ICM y CEAB), por los análisis de nutrientes, la ayuda en cálculos y valiosos consejos; a Gustavo Carreras, por participar en los muestreos en Blanes y prestarse a llevar las muestras a Barcelona; a Ferrán Crespo, por la ayuda en los muestreos en Blanes a bordo de la Dolores; a Irene, Alba, Gil y Nixon por participar en los muestreos; a Ramón Coma, indispensable para solucionar los más diversos y absurdos problemas informáticos, siempre con una sonrisa; a Ángel Luque, por encontrar la manera de hacer funcionar las cosas. Muchas gracias a Helena del Barrio por encontrar todos los artículos que le pedí, incluso los japoneses. Gracias al personal administrativo, en particular a Gema Peña, a Carmela Bosca, por su eficiencia y amabilidad, a Roser Guix y a Marta Alamán.

Thanks very much to Dan Miller, Claudette De Courley, Ana Riesgo, and Michelle Nestlerode for assisting with fieldwork in Belize, and to Tanya Rützler, Jim Taylor, and Martha Richotas for logistic support at the Smithsonian’s Marine Field Station at Carrie Bow Cay. Hopefully, we will know each other in person one day.

Je remercie infiniment le groupe de recherche dirigé par Olivier Ragueneau au LEMAR pour m’avoir accueilli en Bretagne pendant les deux stages. Durant ces six mois, j’ai appris énormément au sujet des microalgues, des cycles biogéochimiques et de l’écologie en général. Mais, grâce à vous, j’ai surtout appris ce qu’était un travail d’équipe, j’ai appris l’importance d´échanger les idées et de promouvoir les contacts entre différentes disciplines et points de vue. J’ai également appris que les plus grands chercheurs peuvent aussi se porter de manière humble et être des personnes splendides! Je remercie spécialement Olivier Ragueneau pour sa disponibilité et pour m’avoir offert la possibilité de travailler au LEMAR, pour me demander mon opinion, pour discuter avec moi sur le travail et les résultats. Merci beaucoup à Aude Leynaert pour son dévouement et sa sympathie écrasante, pour collaborer pendant les échantillonnages et les manips avec 32Si et m’aider avec les calculs et l’interprétation des résultats et pour son encouragement. Je remercie Beatriz Beker, Jacques Grall, Rudolph Corvaisier, Brivaela Moriceau, Jérémy Querné, Charlotte Soler, Laurent Chauvaud, Mélanie Raymonet, Sabine Schultes, Philippe Pondaven, Marie Czamanski, Anne Lorrain pour l’aide et les conseils. Merci beaucoup à Manon Le Goff et Emilie Grossteffan pour m’apprendre à utiliser le TechniCon et pour m’aider avec le matériel, et à Annik Masson pour l’analyse des sels nutritifs. Merci à Gérard Sinquin (Plataforme d’Imagerie et de Mesures en Microscopie, Université de Bretagne Occidentale) pour les photos au SEM. Merci à l’équipage du Côte de la Manche et au personnel administratif du LEMAR. Je remercie beaucoup Robert Marc, Erwan Amice et Céline Poulain pour plonger pour moi dans les froides eaux de la Rade de Brest et pour leur sympathie et disponibilité.

Muchas gracias también a todos los demás trabajadores, investigadores, becarios, precarios del CEAB, porque en algún momento han colaborado sin saberlo a la realización de esta tesis con su trabajo, comentarios, consejos, o simplemente haciendo más agradable el día a día. A Ana Riesgo, por compartir experiencias y solidaridad. A Raffa y Gil, por no dejar que me sintiera sola, por las risas, los sarcasmos y las charlas sobre la vida, la ciencia, los hombres y las mujeres. A Diana, por compartir despacho y confidencias. A Gemma, João, Miquel, Ana H, Edu A, Carmen, Simo, Marc, Steffi, Willy, Bego, Javi, Adri,Oscar, Edu S, Laura S, Laura N, Roser, Clara, Alba, Chiara, Albert, Antoni, Carlos, Daphne, David, Romero, Sergi, Dani, Susana, Andrea, Paola L, Paola F, Silvia, Paola y Paoletta, Alessandro, Valentina, Alba, Irene, Oriol, Carina, Maria Elena, Mian, Mireia, Raquel, Tatiana, Virginia G, Guillermo, Helena, Tina, Marta, Xenia, Xavier To, Xavier Tr. Porque en algún momento cada uno de vosotros me habéis regalado y enseñado algo. Muchas gracias también a Benito, Valentín, Jordi, Jose, Rafael, Emilia, Maricarmen y Ana, porque habéis sido capaces de regalarme una sonrisa cada día, lo que me ha permitido llegar al día de hoy con todavía algo de cordura.

Grazie a Morgana e Rossana, fondamentali e semplicemente fantastiche, che mi hanno fatto sentire a casa.

A Federico y a sus tablas de surf, por llevarme a conocer Bretaña, por su desenfrenada simpatía y la pizca de locura. À toutes les collègues et amis du LEMAR, et particulièrement à Céline, Mélanie, Marie, Antoine, Caroline, Yoann, Yann, Mathieu, Florent, Manon, Fred, Elodie, Charlotte, Valérie, Fanny, Rémi, Jonathan, Coralie, pour votre accueil, générosité, sympathie, pour les cafés, les repas à la cantine, les fêtes. Grace à vous, la chaleur du climat méditerranéen ne m’a pas trop manqué.

Grazie alle amiche di sempre, quelle con cui, anche se non ci sentiamo- vediamo,ci ritroviamo in un momento, con complicitá e fiducia: a Elo, Laura, Cri, Elena, Micol, Marzia, Sara e Nico.

Muchas gracias a Silvia, Cati y Mónica, mis “almas gemelas”( mellizas?), por todo lo que hemos compartido y por estar, siempre, a pesar de la geografía.

A Marc, por haber estado en momentos cruciales, y también por informarme de la propuesta de tesis. Quizás otra vez escuche todo lo que tienes que decir.

Gracias a Sinpa y Juno, las mejores psicólogas que se pueda desear.

Merci de tout coeur à Pascale et Loïc, qui ne m’ont pas seulement ouvert la porte de leur maison, mai aussi celle de leur pittoresque y pétillante famille. Ils se sont transformés en de merveilleux “parents adoptifs” et m’ont appris une manière différente de vivre la vie. A Marcoaurelio, pour sa sympathie, pour les conversations, la compagnie, les barbecues...et la voiture! A Loreline, Fiorina, Christophe et Amélie, a et au reste de la famille et amis brestois pour son accueil. A Pieruccio per avermi dato la possibilitá di conoscerli.

Merci beaucoup à Chantal et Nathalie Auguet et au reste de la famille pour son accueil, gaieté et pour les beaux moments passés ensemble.

Grazie alla mia famiglia, che mi ha sempre appoggiato e accompagnato, e che dopo l’Erasmus ha, poco a poco, perso la speranza di rivedermi in Italia per qualcosa che non fossero solo delle vacanze rubate. Grazie per venire a trovarmi, pensare a me e ridere del mio italiano. Per aver creduto in me e avermi lasciato libera di scegliere.

Gracias a Jean-Christophe, que me ha acompañado en esta aventura desde el principio, permaneciendo a mi lado siempre, dándome ánimos y agarrándome cuando me iba a caer. Sin su cariño y constancia, mi tozudez empedernida no me hubiese bastado para terminar la tesis. Y, más allá de una o de mil tesis, va todo el agradecimiento y el sentimiento que se escapa a estas líneas.

ÍNDICE DE CONTENIDOS

Abstract 1 Resumen 5

CAPÍTULO 1. Introducción general 11 1.1 Microfitoplancton y microfitobentos 11 1.2 Taxonomía y diversidad 12 1.3 Factores ambientales y microalgas 14 1.4 El ciclo del silicio en el mar 19 1.5 Bibliografía 21

CAPÍTULO 2. Objetivos 29

CAPÍTULO 3. Estudio 1 - Phytoplankton variability across a gradient of habitats over a tropical continental shelf 33 3.1 Introduction 33 3.2 Method 34 3.2.1 Study site and habitats 34 3.2.2 Environmental characterization 36 3.2.3 Phytoplankton community structure 37 3.3 Results 39 3.3.1 Environmental characterization 39 3.3.2 Phytoplankton community structure 43 3.4 Discussion 52 3.5 Aknowledgements 55 3.6 References 55

CAPÍTULO 4. Estudio 2 - Spatial-temporal patterns of nutrients and phytoplankton communities in nearshore habitats of the NW Mediterranean 61 4.1 Introduction 61 4.2 Method 61 4.2.1 Study site 61 4.2.1 Nutrients and environmental characterization 63 4.2.2 Phytoplankton community structure 65 4.3 Results 67 4.3.1 Environmental characterization and nutrients 67 4.3.2 Phytoplankton community structure 74 4.4 Discussion 83 4.5 Aknowledgements 87 4.6 References 88

CAPÍTULO 5. Estudio 3 - The role of benthic diatoms associated to maerl beds in the silicon cycle of the Bay of Brest (NE Atlantic) 93 5.1 Introduction 93 5.2 Method 94 5.2.1 Study site 94 5.2.2 Biogenic silica stock 97 5.2.3 Benthic diatom community and content of BSi per cell 98 5.2.4 Silicic acid uptake 99 5.3 Results 100 5.3.1 Water column 100 5.3.2 Biogenic silica stock associated to maerl 102 5.3.3 Benthic diatom community 103 5.3.4 Silicic acid uptake 105 5.4 Discussion 106 5.5 Aknowledgements 110 5.6 References 111

CAPÍTULO 6. Discusión 117 6.1 Discusión general 117 6.2 Conclusiones 123 6.3 Conclusions 125 6.4 Perspectivas 127

Bibliografía 131 Bibliografía y otras fuentes consultadas durante la identificación taxonómica de microalgas 140

ANEXO 1. Supplementary Table 1. Study 1, Caribbean 146 Supplementary Table 2. Study 2, Mediterranean 151 Supplementary Table 3. Study 3, NE Atlantic 154 Supplementary Table 4. Study 3, NE Atlantic 157

ANEXO 2. Photographs 161 Study 1. Belize, Caribbean 162 Study 2. Blanes, NW Mediterranean 173 Study 3. Bay of Brest, NE Atlantic 180

Coastal microphytoplankton and microphytobenthos. Abstract

Abstract

Microalgae form diverse and complex communities in aquatic systems, which play a key role in biogeochemical cycles of different elements, like carbon and silicon, and are the base of marine food webs. The presence of a particular microalgae species in a system is associated to numerous physico-chemical parameters and to specific ranges of variability of those parameters. Moreover, its success depend on its ability to compete for resources, like nutrients. The importance of each environmental parameter and resource in driving the abundance and composition of microalgae communities may be different in different systems. Since microalgal growth depend on the in situ conditions, the environmental heterogeneity found in coastal systems is reflected by a concurrent heterogeneity in microalgae community patterns. To understand microalgae dynamics and their implications in nutrient biogeochemical cycles in coastal systems, different spatial- temporal scales of analysis are needed. The aim of the present Thesis is to analyze the taxonomic composition and the spatial- temporal variability of microalgae communities (microphytoplankton and microphytobenthos) at different scales and in different coastal systems, and their relationships with environmental variables. In particular, we investigated the interactions of microalgae community with nutrient concentrations, and specifically with silicon biogeochemical cycle. The thesis comprises three complementary studies. In Study 1, “Phytoplankton variability across a gradient of habitats over a tropical continental shelf”, we investigated the species composition and abundance of the microphytoplankton over a shallow Mesoamerican continental shelf (Belize). Samples were collected during dry (December 2005) and rainy season (July 2005), along a presumptive environmental gradient extending from offshore blue water across a succession of continental-shelf habitats (i.e., fore reef, lagoon patch reef, turtlegrass bed and island mangrove). Rich phytoplankton communities occurred in all habitats. Diatoms (127 species) were the most abundant organisms, followed by dinoflagellates (70 species), coccolithophorids (12) and silicoflagellates (1). There were marked seasonal differences in some environmental variables (seawater temperature, irradiance, salinity, rainfall and some nutrients).

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Coastal microphytoplankton and microphytobenthos. Abstract

Accordingly, we detected significant between-season differences in the taxonomic composition of phytoplankton, although variations in cell abundances were hardly detectable. Surprisingly, neither the analysis of nutrients in the water column (silicate, phosphate, nitrite+nitrate) nor phytoplankton abundance revealed a clear offshore to inshore gradient in the study area; the lowest values did not always occur in open waters and, even if they did, they increased in a non- lineal, complex pattern across shelf habitats. Each habitat showed a characteristic nutrient composition and a distinctive phytoplankton community, with between-habitat differences being most marked in July. The mangrove habitat, with the highest nutrient concentrations and noticeable abundance of dinoflagellates and coccolithophorids, was the most distinct. The studied environmental parameters did not fully explain the variability in phytoplankton composition, suggesting that additional factors are responsible for the marked between-habitat distinctiveness. In Study 2, “Spatial-temporal patterns of nutrients and phytoplankton communities in nearshore habitats of the NW Mediterranean”, we examined one-year round patterns in variability of inorganic nutrients and microphytoplankton assemblages at the habitat and microhabitat scales in nearshore waters of a wave-exposed coast in the NW Mediterranean. As habitats, we considered a) the nearshore, 37 m deep water column overlying a soft bottom and b) the demersal water layer associated to rocky bottoms. As microhabitats, we considered three depths (surface, mid depth, near bottom) within the water-column habitat and vertical versus horizontal rocky substrates within the hard-bottom habitat. Concentrations of silicate, phosphate and dissolved inorganic N compounds, as well as seawater N:Si:P ratios, varied as a function of season and habitat, and to a lesser extent, of microhabitat. Phytoplankton abundance and species composition varied primarily associated with changes in nutrient (particularly silicate) availability. Diatoms were the dominant group through most of the year, with a major bloom in March and seasonal species replacement. However, in July, when abundance of total cells reached its annual minimum, dinoflagellates surpassed diatoms, probably as a consequence of silicon limitation, being zooplankton grazing postulated as a secondary control of diatom production. Silicon and phosphate were suspected to be limiting in this nearshore phytoplankton assemblage. When silicon in the system was separately analyzed as its dissolved (silicate) and particulate planktonic (frustules) forms, these forms showed reciprocal concentration patterns, indicating alternating processes of uptake by diatoms and subsequent frustule redissolution

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Coastal microphytoplankton and microphytobenthos. Abstract

during most months, except from May through September, when total silicon showed minimum values. This minimum probably indicated that Si was exported from the planktonic system to the bottom through either deposition, grazing or uptake by microphytobenthos and siliceous sponges. The boundary layer associated to rocky bottoms was characterized by a particular “demersal” (not benthic) phytoplankton assemblage, clearly distinguishable from that typically occurring in the water column over adjacent soft bottoms. A delicate nutrient-phytoplankton coupling, which varies at both habitat and microhabitat scales, seems to occur in these nearshore, coastal systems. In Study 3, “The role of benthic diatoms associated to maerl beds in the silicon cycle of the Bay of Brest (NE Atlantic)”, we analyzed the taxonomic composition, abundance, biogenic silica (BSi) stock and silicon uptake rate of benthic diatoms associated to different shallow maerl banks in the Bay of Brest. The studied maerl habitat hosts diverse and complex assemblages of microphytobenthos, whose spatial variability in terms of specific composition and abundance was detected at a scale of few kilometers. We did not observe this same variability for the overlying phytoplankton communities. Benthic BSi stock ranged between 52.21 and 239.48 mmol BSi m-2 in summer, depending on the maerl bank, corresponding to 7-34 times planktonic BSi of the overlying 3 m-deep water-column. In autumn, the benthic BSi stock and diatom abundance were almost 10 times lower than in summer. The production rate of BSi by benthic diatoms associated to maerl banks, estimated from a 24 hour incubation of a a natural assemblage with 32Si as a tracer, was 156.9 (±57.2) µmol Si m-2 day-1 in autumn, when seawater silicate concentration was 14.70 µmol L-1, whereas it was only 3.4 (±1.4) µmol Si m-2 day-1 in summer, with a silicate concentration of 0.76 µmol L-1. We estimated a specific uptake rate of 0.039 (±0.01) day-1 and 2.27×10-5 (±8.36×10-6) day-1, for autumn and summer, respectively. The high BSi stock and low productivity registered in the studied seasons highlight the need of additional studies to elucidate the possible limiting effect of a combination of nutrients. Our results remark the key role of benthic diatoms in the silicon cycle of this coastal system, which is comparable to that of phytoplankton, and highlights the importance of considering different habitats and spatial-temporal scales of variability when elaborating biogeochemical models of the silicon cycle in coastal systems. The study of microalgal communities in different coastal systems revealed the existence of complex relationships between environmental factors and local biological communities. The result is a great variability in microalgal patterns at different spatio-temporal

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Coastal microphytoplankton and microphytobenthos. Abstract

scales, which should be taken into account when developing studies and models in coastal systems.

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Microfitoplancton y microfitobentos en sistemas litorales. Resumen

Resumen

Las microalgas forman comunidades complejas y con elevada diversidad en los sistemas acuáticos, desarrollando una función clave en los ciclos biogeoquímicos de varios elementos, como el carbono y el silicio, y representando la base de las redes tróficas marinas. La presencia de una determinada especie de microalga en un sistema está asociada a numerosos parámetros físico-químicos y a rangos de variación específicos de dichos parámetros. Asimismo, su éxito depende de su habilidad en competir para los recursos, como los nutrientes. La importancia de cada parámetro ambiental y recurso en influenciar la abundancia y composición de las comunidades de microalgas puede ser diferente en distintos sistemas. De momento que el crecimiento de las microalgas depende de las condiciones in situ, la heterogeneidad ambiental que se encuentra en sistemas costeros se ve reflejada por los patrones de heterogeneidad de las comunidades de microalgas. Para entender las dinámicas de las microalgas y sus implicaciones en los ciclos biogeoquímicos de los nutrientes en sistemas costeros, es necesario realizar análisis a diferentes escalas espacio-temporales. El objetivo del presente trabajo de Tesis es analizar la composición taxonómica y la variabilidad espacio-temporal de comunidades de microalgas (microfitoplancton y microfitobentos) a diferentes escalas y en diferentes sistemas costeros, y sus relaciones con algunas variables ambientales. En particular, la Tesis investiga las interacciones entre las comunidades de microalgas y las concentraciones de nutrientes, y específicamente las implicaciones en el ciclo biogeoquímico del silicio. La tesis se compone de tres estudios complementares. El Estudio 1, “Variabilidad del fitoplancton a lo largo de un gradiente de hábitats asociados a una plataforma continental tropical” analiza la composición específica y la abundancia del microfitoplancton de una plataforma continental Mesoamericana poco profunda (Belize). Las muestras se recogieron durante la estación seca (Diciembre 2005) y húmeda (Julio 2005), a lo largo de un presunto gradiente ambiental, desde el océano abierto y pasando a través de una sucesión de hábitats de la plataforma continental (arrecife externo, arrecifes parche, praderas de fanerógamas marinas e

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Microfitoplancton y microfitobentos en sistemas litorales. Resumen

islas de manglar). Se observaron ricas comunidades de fitoplancton en todos los hábitats. Las diatomeas (127 especies) fueron los organismos más abundantes, seguidas por dinoflagelados (70 especies), coccolitofóridos (12 especies) y silicoflagelados (1 especie). Se detectaron marcadas diferencias estacionales en las variables ambientales analizadas (temperatura del agua, irradiancia, salinidad, pluviometría y algunos nutrientes). Con correspondencia, observamos diferencias estacionales significativas en la composición taxonómica del fitoplancton, a pesar de que las diferencias en las abundancias de células fueran débiles. Sorprendentemente, ni el análisis de nutrientes de la columna de agua (silicato, fosfato, nitrito+nitrato) ni la abundancia de fitoplancton mostraron un claro gradiente ambiental offshore-inshore; los valores más bajos no siempre se detectaron el océano abierto y, aún cuando se daba el caso, aumentaban de una manera compleja y no lineal a través de los hábitats de plataforma. Cada hábitat se caracterizó por una composición en nutrientes específica y una comunidad fitoplanctónica peculiar, siendo las diferencias entre hábitats más acentuadas en Julio. El hábitat de manglar, con las concentraciones de nutrientes más elevadas y una notable abundancia de dinoflagelados y coccolitofóridos, destacó como el más diferente. Las variables ambientales estudiadas explican solo en parte la variabilidad en la composición del fitoplancton, sugiriendo que otros factores adicionales son responsables de la marcadas diferencias entre hábitats. El Estudio 2, “Patrones espacio-temporales de nutrientes y comunidades fitoplanctónicas en hábitats litorales del Mediterráneo NO” examina la dinámica intra-anual de nutrientes inorgánicos y de comunidades de microfitoplancton, a escala de hábitat y microhábitat en una zona litoral “nearshore” expuesta del Mediterráneo noroccidental. Como hábitat, se consideraron a) la columna de agua por encima de un fondo arenoso “nearshore” de 37 m de profundidad y b) la capa demersal de agua asociada a fondos rocosos. Los microhábitats eran tres profundidades (superficie, mitad de la columna de agua y cerca del fondo) del hábitat de columna de agua, y sustratos horizontales y verticales del hábitat rocoso. Las concentraciones de silicato, fosfato y compuestos disueltos de nitrógeno inorgánico, así como las proporciones de N:Si:P del agua de mar, variaron en función de la estación y del hábitat, y en menor medida del microhábitat. La abundancia y composición específica del fitoplancton mostraron variaciones asociadas en su mayor medida a cambios en la disponibilidad de nutrientes (en particular de silicato). Las diatomeas fueron el grupo dominante durante la mayor parte del año, con un bloom principal en Marzo y alternancia de especies. Sin embargo, en Julio, cuando la abundancia total

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Microfitoplancton y microfitobentos en sistemas litorales. Resumen

de células alcanzó su mínimo, los flagelados superaron las diatomeas, probablemente como consecuencia de una limitación por silicio, siendo el consumo por parte del zooplancton un posible factor secundario de control de la abundancia de diatomeas. Los datos apuntaron a que esta comunidad de fitoplancton costero estaba limitada por silicio y fósforo. Cuando se analizó el silicio en el sistema en sus formas disuelta (silicato) y particulada (frústulas), estas formas mostraron patrones de concentración opuestos, indicando procesos alternados de uptake por parte de las diatomeas y de siguiente redissolución de las frústulas, durante la mayor parte del año, con excepción del periodo entre Mayo y Septiembre, cuando el silicio alcanzó valores mínimos. Este mínimo probablemente indica que el silicio se exportó del sistema planctónico hacia el fondo, a través de deposición, consumo o uptake por parte de microfitobentos y de esponjas silícicas. La capa demersal de agua asociada a los sustratos rocosos se caracterizó por la presencia de una particular comunidad “demersal” (no bentónica) de microalgas, distinta de la que se observa típicamente en la columna de agua por encima de sustratos arenosos. En estos sistemas costeros “nearshore”, parece existir un delicado acoplamiento nutrientes-fitoplancton, que varía a escala de hábitat y microhábitat. El Estudio 3, “El papel de las diatomeas bentónicas asociadas a fondos de maerl en el ciclo del silicio en la Bahía de Brest (Atlántico NE)”, analiza composición taxonómica, abundancia, stock de sílice biogénica (BSi) y tasa de uptake de silicio de diatomeas bentónicas asociadas a diferentes bancos de maerl en la Bahía de Brest. En el hábitat de maerl se observaron comunidades de microfitobentos complejas y con elevada diversidad, que mostraron variabilidad espacial a escala de algunos km en su composición específica y abundancia. Esta variabilidad no se vio reflejada por las comunidades de fitoplancton sobrestantes. El stock de BSi mostró un rango de variación, dependiendo del banco de maerl, comprendido entre 52.21 y 239.48 mmol BSi m-2 en verano, que corresponde a 7-34 veces el stock de BSi planctónica de la sobrestante columna de agua de 3 m de profundidad. En otoño, el stock bentónico de BSi y la abundancia de diatomeas resultaron alrededor de 10 veces inferiores a los valores registrados en verano. La tasa de producción de BSi por parte de las diatomeas bentónicas asociadas a bancos de maerl, estimada a partir de incubaciones de comunidades naturales durante 24 horas en presencia de 32Si como marcador, resultó ser de 156.9 (±57.2) µmol Si m-2 día-1 en otoño, cuando la concentración de silicato era de 14.70 µmol L-1, y de sólo 3.4 (±1.4) µmol Si m-2 día-1 en verano, con una concentración de silicato de 0.76 µmol L-1. Estimamos que la tasa específica de uptake fuera de

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Microfitoplancton y microfitobentos en sistemas litorales. Resumen

0.039 (±0.01) día-1 y 2.27×10-5 (±8.36×10-6) día-1 en otoño y verano, respectivamente. El elevado stock de BSi y la baja producción registradas en las estaciones del estudios resaltan la necesidad de realizar investigaciones adicionales para elucidar los posibles efectos limitantes de una combinación de nutrientes. Los presentes resultados remarcan el papel clave de las diatomeas bentónicas, comparable al del fitoplancton, en el ciclo del silicio en el sistema costero en estudio, y subrayan la importancia de considerar diferentes hábitats y escalas espacio-temporales a la hora de desarrollar modelos biogeoquímicos del silicio en sistemas costeros. El estudio de las comunidades de microalgas en diferentes sitemas costeros ha revelado la existencia de complejas relaciones entre los factores ambientales y las comunidades biológicas locales. El resultado es la gran variabilidad en los patrones de variación de las comunidades de microalgas a diferentes escalas espacio-temporales, un factor que se debería tener en cuenta a la hora de desarrollar estudios y modelos en sistemas costeros.

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CAPÍTULO 1

CAPÍTULO 1. Introducción general

Introducción general

1.1 Microfitoplancton y microfitobentos Los términos “microfitoplancton” y “microfitobentos” no tienen valor taxonómico, sino que sólo indican un conjunto de organismos, del tamaño comprendido entre los 20 y los 200 µm, capaces de realizar fotosíntesis. Comúnmente, se utiliza también el término “microalgas” para designar a estos organismos. Los sufijos “plancton” y “bentos” se refieren al ambiente en el que el organismo desarrolla su ciclo vital: en suspensión en la columna de agua (plancton) o en estrecha relación con el sustrato (bentos). Estas dos situaciones resultan ser, a menudo, extremos de un patrón continuo, ya que algunas especies se encuentran comúnmente tanto en el plancton como entre el bentos y otras muestran cambios de habito en diferentes fases de sus ciclos vitales. El microfitoplancton y el microfitobentos están constituidos por grupos heterogéneos de algas unicelulares y protozoos, que difieren entre si en cuanto a requerimientos ambientales y nutricionales y en la estructura de sus ciclos vitales. Entre ellos se consideran grupos como (clasificación según http://www.algaebase.org): diatomeas (Eukaryota, Chromista, Bacillariophyta), dinoflagelados (Eukaryota, Protozoa, Myzozoa), coccolitofóridos (Eukaryota, Chromista, Haptophyta), clorófitos (Eukaryota, Plantae, Chlorophyta) y cianobacterias (Procaryota, Bacteria, Cyanobacteria). Las células pueden vivir libres o asociadas en colonias. Aunque la mayor parte de estos organismos son autótrofos, existen diversos niveles de mixotrofía, e incluso algunas especies completamente heterótrofas (por ejemplo entre los dinoflagelados). Las “microalgas” juegan un papel clave en los ciclos biogeoquímicos de diversos elementos, como el carbono y el silicio, y son la base de las redes tróficas marinas (Tréguer et al 1995, Nelson et al 1995, Smetacek 1999). Las diatomeas planctónicas son reconocidas como las principales “exportadoras” del carbono desde el atmósfera hacia el “deposito” oceánico, ya que fijan el CO2 atmosférico mediante fotosíntesis y exportan el carbono al compartimento oceánico a través de dos

11

CAPÍTULO 1. Introducción general mecanismos: sedimentan fuera de la capa de mezcla o lo transfieren a niveles tróficos más elevados, ya que constituyen la base de las cadenas tróficas marinas (Ryther 1969, Sherr and Sherr 1988). El microfitoplancton y e microfitobentos muestran elevada diversificación morfológica y funcional, que les ha permitido colonizar prácticamente cualquier tipo de hábitat acuático. En muchos casos, las células secretan sustancias mucilaginosas que desarrollan un papel importante en la locomoción, la flotabilidad, la reproducción, la formación y protección de las colonias. Entre los organismos planctónicos se dan diversas especializaciones morfológicas y capacidad de agregación en colonias, así como otras especializaciones que permiten una regulación de la flotabilidad y lentos movimientos hacia zonas de mayor disponibilidad de luz y/o de nutrientes. Algunas especies secretan compuestos con propiedades bactericidas, antibióticas o tóxicas para otros organismos. En la interface agua-sedimento, el conjunto de células y sustancias extrapoliméricas forma el llamado biofilm, que desempeña funciones ecológicas cruciales, como aumentar la cohesión del sedimento y actuar como un “filtro” en el intercambio de nutrientes entre el sustrato y la columna de agua sobrestante.

1.2 Taxonomía y diversidad La descripción de la gran diversidad de microalgas marinas es a la vez un reto y un recurso. La taxonomía y sistemática de estos organismos son campos de investigación en pleno desarrollo, como testimonia el elevado y siempre creciente número de especies identificadas. La información taxonómica es una herramienta fundamental para cualquier investigación ecológica o ecofisiológica. En los últimos años, la importancia de la taxonomía ha sido remarcada por la comunidad científica internacional, entrando a formar parte de las recomendaciones adoptadas por Naciones Unidas y formalizadas en el Convenio sobre la Diversidad Biológica, elaborado en Rio de Janeiro en 2002, y en documentos de la Unión Europea en el campo del desarrollo científico y tecnológico. La Asamblea General de las Naciones Unidas proclamó el año 2010 “Año Internacional de la Diversidad Biológica”, con el fin de atraer más la atención internacional al problema de la pérdida de biodiversidad. El Convenio sobre la Diversidad Biológica reconoce la importancia de la diversidad biológica para los “bienes y servicios de los ecosistemas”, así como identifica cinco principales amenazas

12

CAPÍTULO 1. Introducción general a la diversidad biológica: las especies exóticas invasoras, el cambio climático, la carga de nutrientes y contaminación, el cambio de hábitats y la explotación excesiva de los recursos (http://www.cbd.int/GBO2). En las zonas costeras, estas amenazas son grandes y crecientes. En este sentido, el estudio de las microalgas marinas tiene derivaciones importantes, por el papel que estos organismos desempeñan en las redes tróficas y los ciclos biogeoquímicos de muchos elementos. Asimismo, la abundancia y distribución de determinadas especies son indicadores del “estado de salud” de los ecosistemas. Debido a su sensibilidad a los cambios ambientales a diferentes escalas, la composición de las comunidades de microalgas proporciona un parámetro sintético para interpretar las dinámicas de los ecosistemas acuáticos. Las alteraciones tróficas de los sistemas costeros modifican la abundancia y composición específica de las comunidades planctónicas, llegando a favorecer proliferaciones masivas de microalgas potencialmente peligrosas para la salud humana y el ecosistema (“HABs” o “mareas rojas”), que son un tema de preocupación creciente, y de alcance socio-económico importante. En los últimos tiempos, se ha incrementado con suma rapidez la tasa de introducción de especies exóticas y el riesgo derivado de esa introducción, debido al incremento de las actividades humanas que alteran rápidamente el medio ambiente y a una mayor probabilidad de propagación “artificial” de especies. Cuanto más se profundiza en la diversidad y biología de las microalgas, tanto más se reconoce su importancia, más allá aún de su papel en los sistemas naturales. La producción de peculiares compuestos químicos, además de impulsar la investigación con motivo de la salvaguardia de la salud pública, abre nuevas perspectivas para la industria farmacéutica, cosmética o para el desarrollo de nanotecnologías. Además, recientemente se está reconociendo el potencial de las microalgas para la producción de biodiesel. Para todo ello, es necesario encontrar y saber cultivar las especies más adecuadas y eficientes para cada caso, lo que implica en primer lugar conocer qué especies existen y qué pueden “ofrecer” y en segundo lugar comprender sus requerimientos ecológicos. Por otro lado, hace falta realizar investigaciones que procuren aumentar nuestro conocimiento de algunos parámetros biológicos básicos a fin de obtener una resolución suficiente que permita predecir con confianza el cambio general en las dinámicas espacio-temporales de los ecosistemas a diferentes escalas. El conocimiento de las especies, su abundancia, biología y ecología, es un primer paso crucial (Terlizzi et al 2003). Actualmente, están descritas más de 100 000 especies de diatomeas (Van Den

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CAPÍTULO 1. Introducción general

Hoek et al 1995) y alrededor de 2000 especies vivientes de dinoflagelados (Taylor et al 2008) aunque estos datos son extremadamente inciertos y variables. Por una parte, los avances tecnológicos (p.e., mejoras en los microscopios), el empleo de nuevas técnicas (p.e., moleculares) y el creciente interés hacia estos grupos permiten la descripción de nuevos taxones y la constante reorganización de la sistemática. Por otra parte, todavía no existen métodos estandarizados al alcance de todos para la determinación unívoca de las especies, con lo cual la determinación basada en caracteres morfológicos, guiada por un “ojo experto” sigue siendo el método más utilizado, aunque no exento de subjetividad y controversia. La información taxonómica existente se encuentra muy a menudo fragmentada, y una correcta identificación depende mucho de las publicaciones especializadas a las que se tiene acceso. La publicación de guías de identificación con fotografías de buena calidad realizadas con microscopio óptico, que es el instrumento más utilizado y accesible, es un resultado relativamente reciente y se debe a las mejoras en la microscopía y en los sistemas de captura y tratamiento de imágenes. Otro de los problemas que surgen con la continua actualización de los conocimientos a cerca de la taxonomía y sistemática de las microalgas es la existencia de un elevadísimo número de sinonimias. En los últimos años, se está realizando un notable esfuerzo para sintetizar la información existente e informatizarla para que sea accesible a cualquier usuario por medio de portales de internet (p.e., http://www.algaebase.org; http://planktonnet.sb- roscoff.fr; http://www.ceab.csic.es/~oceanlab; http://ucjeps.berkeley.edu/INA.html; htt p://www.marbef.org; http://www.com.univ-mrs.fr/PHYTOCOM).

1.3 Factores ambientales y microalgas La presencia de una determinada especie de microalga en un medio acuático está asociada a numerosos parámetros físico-químicos, y a un rango determinado en los valores de dichos parámetros. Además, en comunidades naturales de microalgas el éxito de las distintas especies depende de su capacidad de competir por los recursos. Entre los factores ambientales que afectan la producción y la composición específica de comunidades de microalgas destacan la cantidad y calidad de radiación lumínica, la temperatura, la cantidad de oxígeno, el pH, la salinidad, la concentración de materia orgánica particulada y disuelta y la concentración de nutrientes (macro y micronutrientes; Loir 2004).

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CAPÍTULO 1. Introducción general

La profundidad del fondo y la turbulencia de la columna de agua, unidas a la turbidez, determinan la cantidad y calidad de luz a la que están expuestas las células de, respectivamente, microfitobentos y microfitoplancton (Round et al 1990). La turbulencia representa una fuente de energía que impide a las células sedimentar y las mantiene en la zona fótica (Margalef 1978). La temperatura regula el metabolismo celular, además de modificar la solubilidad de los compuestos químicos y del oxígeno disuelto. El oxígeno es necesario para la respiración celular. El pH, que regula la disponibilidad de los elementos químicos, puede variar en zonas de aguas estancadas o en correspondencia de vertidos de origen antrópico. La materia orgánica, cuya descomposición requiere oxígeno, enriquece el medio en nutrientes. La salinidad tiene gran influencia sobre la composición específica de las comunidades, ya que cada especie tiene un nivel diferente de halofilia; la salinidad puede ser muy variable en sistemas litorales debido al “runoff” continental y a los aportes fluviales. Los nutrientes necesarios en mayores cantidades (macronutrientes) son, además del carbono, compuestos de nitrógeno, fosfato y silicato. La disponibilidad de macronutrientes es una de las variables que controlan la biomasa y la estructura de las comunidades de microalgas. Cada especie presenta unas características fisiológicas propias, que se traducen en requerimientos de recursos específicos. A nivel de grupo, las diatomeas requieren silicio en proporciones casi equivalentes al nitrógeno (Brzesinski 1985), así que la falta de ácido silícico puede limitar su crecimiento, favoreciendo otros grupos no silícicos (e.g., Tilman et al 1982, Conley et al 1993, Nelson and Dortch 1996). Combinaciones diferentes de recursos potencialmente limitantes tienen efectos distintos sobre la estructura de las comunidades de microalgas, ya que no todas las especies tienen las mismas respuestas de crecimiento a bajos niveles de los diferentes nutrientes (Tilman et al 1982, Sommer 1998, Nelson and Dortch 1996). Los micronutrientes (como metales en trazas y vitaminas), son necesarios en pequeñas cantidades para las funciones fisiológicas de las células (Frey and Small 1980) y raramente son limitantes en zonas costeras, debido a los aportes terrígenos. Otro factor que regula la abundancia y la composición de las comunidades de microalgas es la actividad de los herbívoros y de parásitos, que pueden limitar la producción algal o, a través de herbivoría selectiva, provocar cambios en la composición específica de las comunidades (Bergquist et al 1985).

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CAPÍTULO 1. Introducción general

En el medio natural, para conocer con exactitud cuales factores limitan las especies presentes en una masa de agua, habría que considerar la tasa de mortalidad y de exportación de las células, el nivel de dependencia de la tasa de reproducción de las distintas especies de la disponibilidad del recurso potencialmente limitante y la tasa de aporte de nutrientes (Tilman et al 1982). El análisis de la proporción de las concentraciones de nutrientes en el ambiente puede ser útil para estimar los nutrientes potencialmente limitantes (Tilman et al 1982, Leblanc et al 2003). La biomasa de las microalgas varía en función del aporte de nutrientes y de la tasa de mortalidad/exportación de células. Si la tasa de mortalidad es baja, los nutrientes se acumulan en forma de biomasa algal y los niveles de nutrientes en el sistema permanecerán bajos. En un sistema donde las tasas de mortalidad son más elevadas, no habrá acumulación de biomasa, las concentraciones ambiente de nutrientes serán elevadas y aumentaría la tasa de división (Tilman et al 1982). La tasa de reproducción de una célula representa de alguna manera la integración de los recursos a los que ha estado expuesta en un tiempo al menos equivalente al tiempo transcurrido desde el último evento reproductivo. Por eso, a la hora de analizar una comunidad, esta nos da informaciones sintéticas de los parámetros ambientales (Revelante et al 1982). En distintos sistemas los diferentes nutrientes pueden tener diferente importancia relativa como factor limitante o ser incluso co-limitantes. En los últimos cuarenta años, la carga de nutrientes derivante de actividades humanas (agricultura, ganadería, industria etc.), en particular de nitrógeno y fósforo, aparece como uno de los impulsores más importantes del cambio del ecosistema en los ambientes costeros. Los seres humanos producen ahora más nitrógeno reactivo que el que se produce por todas las vías naturales juntas. Además, se prevé un aumento del uso del nitrógeno en 20 a 50% a nivel mundial en los próximos 50 años

(http://www.un.org/es/events/biodiversity2010; http://www.cbd.int/GBO2). Los aportes antrópicos alteran la composición de las comunidades ya que, además de aumentar la cantidad de nutrientes en los sistemas, favoreciendo esas especies de rápido crecimiento que dependen de niveles de nutrientes más altos, alteran profundamente las proporciones estequiométricas de los nutrientes, de tal manera que se fuerza el aumento de unos grupos de microalgas en detrimento de otros. En particular, la disminución del silicio con respeto a los otros nutrientes puede alterar la composición específica de las comunidades de microalgas y llevar hacia la dominancia de especies que requieren menos silicio, o hacia grupos no silícicos, como es el caso de los dinoflagelados

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CAPÍTULO 1. Introducción general

(Smayda 1990, Egge and Aksnes 1992, Conley et al 1993, Humborg et al 2000). En algunos casos, se ve favorecida la proliferación de algas tóxicas, con importantes impactos sobre los ecosistemas y las pesquerías costeras (Roelke 2000). La disminución proporcional de Si:N y Si:P se debe al efecto combinado de, por un lado, el aumento de los aportes de compuestos de nitrógeno y fósforo en las aguas costeras, por otro lado, la disminución de aporte de silicio de origen terrestre, causada por la retención de sedimentos en correspondencia de presas (Conley et al 1993, Ragueneau et al 2005a, Laruelle et al 2009a, Bernard et al 2010). En el Mediterráneo y en sistemas costeros templados, el silicio y el fósforo son generalmente indicados como factores limitantes el crecimiento del fitoplancton, bien de forma alternada dependiendo de la estación, bien contemporáneamente (Del Amo et al 1997, Granéli et al 1999, Leblanc et al 2003, Lucea et al 2003). En regiones tropicales, la concentración de silicio disuelto parece estar menos afectada por factores antropogénicos, siendo más importantes factores climáticos, geológicos y geomorfológicos (Jennerjahn et al 2006). Tradicionalmente, el nitrógeno se ha considerado como el principal nutriente limitante la producción primaria en aguas marinas tropicales (Parsons et al 1977), aunque otros estudios sugieren que el fósforo tenga un papel relevante, y que la importancia relativa de cada nutriente dependa del hábitat considerado (Lapointe et al 1987). La variabilidad espacial y temporal de los factores ambientales hace que la columna de agua sea heterogénea, tanto espacial como temporalmente (Cloern and Jassby 2010). La heterogeneidad a larga escala está asociada a gradientes de nutrientes y luz, que varían con la profundidad; a pequeña escala, a la distribución agregada (o “patchiness”) es causada por moto turbulento, upwelling, vientos e mezcla térmica; a muy pequeña escala, es provocada por excreción de animales y descomposición de organismos (Tilman et al 1982). Dado que el crecimiento del microfitoplancton y del microfitobentos depende de las particulares condiciones que encuentra in situ, la heterogeneidad espacio-temporal de las microalgas del sistema costero refleja la heterogeneidad inherente a las zonas costeras (Barnett and Jahn 1987, Masó and Duarte 1989). Estudios de variabilidad de fitoplancton en zonas costeras (“nearshore”) indican que los patrones observados podrían diferir de los que se observan en oceano abierto, y que, dependiendo del sistema costero considerado, la variabilidad del fitoplancton depende de la importancia relativa de la climatología, de factores antropogénicos y del estado trófico (Cloern and Jassby

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CAPÍTULO 1. Introducción general

2010 y referencias). Por eso, es necesario comprender el funcionamiento de las dinámicas locales y la magnitud de las diferencias entre localidades y sistemas costeros diferentes (Cloern and Jassby 2010). La zona costera presenta una complejidad ambiental extremadamente elevada, al encontrarse al interfaz de fenómenos atmosféricos, oceánicos y terrígenos. En la zona costera, la columna de agua, relativamente poco profunda, se ve afectada por múltiples factores, que alteran su hidrodinámica, composición química y propriedades físicas (Legendre and Demers 1984). La descarga de los ríos, la escorrentía y los aportes terrígenos aportan episodicamente nutrientes y alteran patrones de salinidad, temperatura y turbidez (Cebrián et al 1996, Cloern and Jassby 2010). Tempestades, vientos y olas, asociados a eventos meteorológicos, pueden provocar resuspensión de material del fondo e influenciar fuertemente las dinámicas de nutrientes y plancton a escalas sub-estacionales (Dagg 1988, Nielsen and Kiorboe 1991, Duarte et al 1999, Lawrence et al 2004, Guadayol et al 2009). La amplitud de la plataforma continental, el grado de intercambio con el mar abierto y la topografía de fondos pueden alterar de manera consistente la hidrodinámica local, que a su vez puede ocasionar retención, resuspensión o exportación de partículas y nutrientes (Denman and Powell 1984, Ferrier and Carpenter 2009). Además, las comunidades biológicas bentónicas pueden modificar localmente los flujos de agua, de manera pasiva o activa, ampliando las capas límite o “boundary layers” (Paterson and Black 1999, Hearn et al 2001), así como alterar las concentraciones de nutrientes y la abundancia de organismos planctónicos a través de herbivoría, uptake y excreción (Asmus and Asmus 1998, Chauvaud et al 2000, Claquin et al 2010). Cuanto más cerca de la línea de costa y del fondo, tanto mayor será la variabilidad de las propriedades químico-físicas de las masas de agua. A pesar de que las zonas costeras recubren solo el 7% de la superficie del océano mundial, son uno de los ecosistemas más productivos del planeta y son responsables de una tercera parte de la producción primaria global (Wollast 1991). Las microalgas son especialmente abundantes en las zonas costeras, donde los aportes de nutrientes son más elevados. Además, la cercanía del fondo y el hidrodinamismo costero permiten a las células permanecer en la zona fótica, y suministran a sus formas de resistencia un ambiente idóneo para sobrevivir hasta ser resuspendidas y poder crecer. Las diatomeas son responsables de hasta el 75% de la producción primaria en las zonas costeras (Nelson et al 1995).

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CAPÍTULO 1. Introducción general

En áreas donde la zona fótica alcanza el fondo, el microfitobentos (MPB) se desarrolla sobre cualquier superficie disponible. En muchos sistemas poco profundos, la biomasa de las microalgas bentónicas puede sobrepasar la del fitoplancton de la columna de agua sobrestante (Macintyre et al 1996, Cahoon 1999, Webster et al 2002). La capa superficial del fondo es una zona de intensa actividad microbiana y donde se dan numerosos procesos químicos. Aquí es donde el MPB modula el intercambio de nutrientes entre el sustrato y la columna de agua (Sigmon and Cahoon 1997, Cahoon 1999, Cibic et al 2007). La abundancia y productividad del MPB se ve determinada por las características del agua sobrestante, por localidad, estación y propiedades del sustrato. Las variaciones en biomasa del MPB en ambientes adyacentes aunque distintos puede ser tan grande como a en zonas separadas por grandes distancias geográficas (Macintyre et al 1996). Debido a la complejidad ambiental que se observa en la zona costera, para comprender las dinámicas de las comunidades de microalgas y de sus implicaciones ecológicas en los ciclos de nutrientes, es necesario realizar estudios a diferentes escalas espacio-temporales, analizando respuestas hábitat-específicas (Cahoon 1999).

1.4 El ciclo del silicio en el mar El silicio es el segundo elemento en abundancia del planeta, pero sólo su forma disuelta, el ácido silícico (Si(OH)4, DSi) es biológicamente asimilable. El ácido silícico es un nutriente esencial para diatomeas, esponjas, silicoflagelados, crisofíceas y radiolarios, que lo polimerizan y lo transforman en sílice biogénica amorfa (BSi), que constituye sus esqueletos. El contenido de ácido silícico en el agua de mar depende del balance entre el ciclo geológico y el biológico del silicio. Comparado con la escala de tiempo biológica, la disolución de los minerales es un proceso lento. Los océanos actuales se encuentran insaturados en este nutriente. En cuanto a su distribución, existen marcadas diferencias a escala geográfica, pero también a escala hidrológica, siendo más abundante en aguas profundas comparado con la superficie y en zonas costeras comparado con alta mar (Tréguer et al 1995). Las diatomeas dominan el consumo de ácido silícico y la producción global de BSi (Lisitzin 1972, Nelson et al 1995). Cuando las células mueren, la sílice biogénica que compone sus frústulas se redisuelve rápidamente, liberando ácido silícico que vuelve a

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CAPÍTULO 1. Introducción general estar disponible para ser asimilado biológicamente. Diversos autores han realizado balances y modelos del ciclo biogeoquímico del silicio en el mar (Burton and Liss 1968, Calvert 1968, DeMaster 1981, Tréguer et al 1995, Nelson et al 1995, Ragueneau et al 2000, Ragueneau et al 2001, Ragueneau et al 2002, DeMaster 2002) y más recientemente se han también investigado sus respuestas a impactos antropogénicos y al cambio climático (Beucher et al 2004, Laruelle et al 2009a, Bernard et al 2010). Todavía, algunos aspectos clave del ciclo biogeoquímico global del silicio permanecen poco comprendidos, en especial el papel de las zonas costeras. Estimas recientes indican que en las zonas costeras y de plataforma continental se da un 18% de la fijación biológica y un 40% del depósito de todo el silicio marino (Laruelle et al 2009a). Vista la importancia de las zonas costeras en ciclo global del silicio, y teniendo en cuenta de la variabilidad espacio-temporal asociada a las mismas, su estudio es de crucial importancia para la comprensión del ciclo biogeoquímico del silicio. La complejidad de modelizar el ciclo del silicio reside en muchos factores, entre los que destacan la falta de métodos estandarizados para la cuantificación de BSi en los diferentes compartimentos, así como el número de compartimentos ambientales a tener en cuenta. Numerosos métodos han sido elaborados para estimar el contenido en BSi en los sedimentos marinos (Chester and Elderfield 1968, Eisma and Van der Gaast 1971, Ellis and Moore 1973, Leinen 1977, Eggiman et al 1980, DeMaster 1981, Pokras 1986, Mortlock and Froelich 1989, Conley 1998, Kamatani and Oku 2000) y en suspensión en el agua (Paasche 1973, Paasche 1980, Paasche and Ostergren 1980, Krausse et al 1983, Kamatani and Takano 1984, Tréguer et al 1988, Brzesinski and Nelson 1989, Tréguer et al 1992, Ragueneau and Tréguer 1994, Ragueneau et al 2005b). La mayoría de estos métodos necesitan instrumentos sofisticados, esfuerzos de muestreo notables o no son selectivos para sílice biogénica (Ragueneau and Tréguer 1994). Por otro lado, se está confirmando la necesidad de considerar factores o compartimentos ambientales que no habían sido incluidos en los primeros modelos. Entre estos, la importancia del acoplamiento bento-pelágico (Ragueneau et al 2002); los aportes fluviales de plantas terrestres y fitolitos, cuerpos silíceos de origen vegetal (Conley 2002); las alteraciones antropogénicas de los aportes de N, P y Si (Conley et al 1993) la actividad del microfitobentos (Ni Longphuirt 2006); la velocidad de disolución de fecal pellets y agregados de diatomeas (Moriceau et al 2007); el papel de las esponjas silícicas, que pueden ser notables al menos a escala local (Maldonado et al 2005, Maldonado et al 2010). Las diatomeas bentónicas contienen y requieren cantidades de silicio por unidad

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CAPÍTULO 1. Introducción general de clorofila más elevadas que las formas planctónicas y pueden ser una importante fuente o almacén de silicio en sistemas poco profundos, llegando a ejercer un control sobre el ácido silícico disuelto en la columna de agua, que se traduce en un control de la producción primaria planctónica (Sigmon and Cahoon 1997). Es en la zona costera donde estos factores tienen más relevancia y pueden modificar localmente la disponibilidad y la velocidad de reciclado de silicato, con concecuencias sobre la producción y la composición específica de comunidades de microalgas. Los estudios del ciclo del silicio en la zona costera, que se caracteriza por la elevada variabilidad espacio-temporal de sus parámetros ambientales, han sido generalmente realizados a meso-escala, limitando el análisis a la columna de agua por encima de fondos blandos y evitando zonas rocosas y su posible papel. Además, los estudios que investigan el papel del microfitobentos subtidal consideran el MPB asociado a fondos blandos. Los resultados derivados de estos estudios se consideran extrapolables a la mayoría de sistemas costeros. Sin embargo, para comprender las interrelaciones entre microalgas y el ciclo del silicio en distintos sistemas costeros, es necesario analizar patrones a diferentes escalas espacio-temporales, debido a la variabilidad inherente a esos sistemas.

1.5 Bibliografía Asmus H, Asmus R (1998), The role of macrobenthic communities for sediment-water material exchange in the Sylt-Rømø tidal basin, Marine Biodiversity 29: 111- 119 Barnett AM, Jahn A (1987), Pattern and persistence of a nearshore planktonic ecosystem off Southern California, Continental shelf research 7: 1-25 Bergquist AM, Carpenter SR, Latino JC (1985), Shifts in phytoplankton size structure and community composition during grazing by contrasting zooplankton assemblages, Limnology and Oceanography 30: 1037-1045 Bernard CY, Laruelle GG, Slomp CP, Heinze C (2010), Impact of changes in river fluxes of silica on the global marine silicon cycle: a model comparison, Biogeosciences 7: 441-453 Beucher C, Tréguer P, Corvaisier R, Hapette AM, Elskens M (2004), Production and dissolution of biosilica, and changing microphytoplancton dominance in the Bay of Brest (France), Marine Ecology Progress Series 267: 57-69 Brzesinski MA (1985), The Si:C:N ratio of marine diatoms: interspecific variability and the effect of some environmental variables, Journal of Phycology 21: 347-357 Brzesinski MA, Nelson DM (1989), Seasonal change in the silicon cycle within a Gulf Stream warm-core ring, Deep-Sea research 36: 1009-1030 Burton JD, Liss PS (1968), Ocean budget of dissolved silicon, Nature 220: 905-906

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Cahoon LB (1999), The role of benthic microalgae in neritic ecosystems, in Oceanography and Marine Biology: an annual review 37, ed. Ansell AD, Gibson RN, and Barnes M, Taylor & Francis. 47-86 Calvert SE (1968), Silica balance in the ocean and diagenesis, Nature 219: 919-920 Cebrián J, Duarte CM, Pascual J (1996), Marine climate on the Costa Brava (northwest Mediterranean) littoral, Publicaciones especiales del Instituto Español de Oceanografía 22: 9-22 Chauvaud L, Jean F, Ragueneau O, Thouzeau G (2000), Long-term variation of the Bay of Brest ecosystem: benthic-pelagic coupling revisited, Marine Ecology Progress Series 200: 35-48 Chester M, Elderfield H (1968), The infra-red determination of opal in siliceous deep- sea sediments, Geochimica et Cosmochimica Acta 32, 1128-1140 Cibic T, Blasutto O, Falconi C, Fonda Umani S (2007), Microphytobenthic biomass, species composition and nutrient availability in sublittoral sediments of the Gulf of Trieste (northern Adriatic Sea), Estuarine, Coastal and Shelf Science 75: 50- 62 Claquin P, Ni Longphuirt S, Fouillaron P, Huonnic P, Ragueneau O, Klein C, Leynaert A (2010), Effects of simulated benthic fluxes on phytoplankton dynamic and photosynthetic parameters in a mesocosm experiment (Bay of Brest, France), Estuarine, Coastal and Shelf Science 86: 93-101 Cloern JE, Jassby AD (2010), Patterns and Scales of Phytoplankton Variability in Estuarine–Coastal Ecosystems, Estuaries and Coasts 33: 230-241 Conley DJ (1998), An interlaboratory comparison for the measurement of biogenic silica in sediments, Marine Chemistry 63: 39-48 Conley DJ (2002), The biogeochemical silica cycle: elemental to global scales, Oceanis 28: 353-368 Conley DJ, Schelske L, Stoermer EF (1993), Modification of the biogeochemical cycle of silica with eutrophication, Marine Ecology Progress Series 101: 179-192 Dagg MJ (1988), Physical and biological responses to the passage of a winter storm in the coastal and inner shelf waters of the northern Gulf of Mexico, Continental shelf research 8: 167-178 Del Amo Y, Leblanc K, Tréguer P, Quéguiner B, Ménesguen A, Aminot A (1997), Impacts of high-nitrate freshwater inputs on macrotidal ecosystems. I. Seasonal evolution of nutrient limitation for the diatom-dominated phytoplankton of the Bay of Brest (France), Marine Ecology Progress Series 161: 213-224 DeMaster DJ (1981), The supply and accumulation of silica in the marine environment, Geochimica et Cosmochimica Acta 45: 1715-1732 DeMaster DJ (2002), The accumulation and cycling of biogenic silica in the Southern Ocean: Revisiting the marine silica budget, Deep-Sea research II 49: 3155-3167 Denman KL, Powell TM )1984, Effects of physical processes on planktonic ecosystems in the coastal ocean, in Oceanography and marine biology: an annual review 22, ed. Barnes H and Barnes M, 116-163 Duarte CM, Agustí S, Kennedy H, Vaqué D (1999), The Mediterranean climate as a template for Mediterranean marine ecosystems: the example of the northeast Spanish littoral, Progress in Oceanography 44: 245-270 Egge JK, Aksnes DL (1992), Silicate as regulating nutrient in phytoplankton competition, Marine Ecology Progress Series 83: 281-289 Eggiman DW, Manheim FT, Betzer PR (1980), Dissolution and analysis of amorphous silica in marine sediments, Journal of Sedimentary Petrology 50, 215-225

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Eisma DB, Van der Gaast SJ (1071), Determination of opal in marine sediments by X- ray diffraction, Netherlands Journal of Sea Research 5, 382-389 Ellis DB, Moore TC (1973), Calcium carbonate, opal and quartz in Halocene pelagic sediments and the calcite compensation level in the South Atlantic Ocean. Journal of Marine Research 31, 210-227 Ferrier GA, Carpenter RC (2009), Subtidal benthic heterogeneity: flow environment modification and impacts on marine algal community structure and morphology, The Biological Bullettin 217: 115-129 Frey BE, Small LF (1980), Effects of micro-nutrients and major nutrients on natural phytoplankton populations, Journal of plankton research 2: 1-22 Granéli E, Carlsson P, Turner JT, Tester PA, Béchemin C, Dawson R, Funari E (1999), Effects of N:P:Si ratios and zooplankton grazing on phytoplankton communities in the northern Adriatic Sea. I. Nutrients, phytoplankton biomass, and polysaccharide production, Aquatic Microbial Ecology 18: 37-54 Guadayol O, Peters F, Marrasé C, Gasol JM, Roldán C, Berdalet E, Massana R, Sabata A (2009), Episodic meteorological and nutrient-load events as drivers of coastal planktonic ecosystem dynamics: a time-series analysis, Marine Ecology Progress Series 381: 139-155 Hearn CJ, Atkinson MJ, Falter JL (2001), A physical derivation of nutrient-uptake rates in coral reefs: effects of roughness and waves, Coral Reefs 20: 347-356 Humborg C, Conley DJ, Rahm L, Wulff F, Cociasu A, Ittekkot V (2000), Silicon retention in river basins: far-reaching effects on biogeochemistry and aquatic food webs in coastal marine environments, Ambio 29: 45-50 Jennerjahn TC, Knoppers BA, Souza WFL, Brunskill GJ, Silva EIL (2006), Factors controlling dissolved silica in tropical rivers., in The silicon cycle. Human perturbations and impacts on aquatic systems, ed. Ittekkot V, Unger D, Humborg C, and An NT, Island Press, Washington. 29-51 Kamatani A, Oku O (2000), Measuring biogenic silica in marine sediments, Marine Chemistry 68: 219-229 Kamatani A, Takano M (1984), The behaviour of dissolved silica during the mixing of river and sea waters in Tokyo Bay, Estuarine, Coastal and Shelf Science 19: 505-512 Krausse GL, Schelske CL, Davis CO (1983), Comparison of three wet-alkaline methods of digestion of biogenic silica in water, Freshwater Biology 13: 73-81 Lapointe BE, Littler MM, Littler DS (1987), A comparison of nutrient-limited productivity in macroalgae from a Caribbean barrier reef and from a mangrove ecosystem, Aquatic Botany 28: 243-255 Laruelle GG, Roubeix V, Sferratore A, Brodherr B, Ciuffa D, Conley DJ, D³rr HH, Garnier J, Lancelot C, Thi Phuong Q, Meunier JD, Meybeck M, Michalopoulos P, Moriceau B, NÆ Longphuirt S, Loucaides S, Papush L, Presti M, Ragueneau O, Regnier P, Saccone L, Slomp CP, Spiteri C, Van Cappellen P (2009a), Anthropogenic perturbations of the silicon cycle at the global scale: Key role of the land-ocean transition, Global Biogeochemical Cycles 23: GB4031 Lawrence D, Dagg MJ, Liu H, Cummings SR, Ortner PB, Kelble C (2004), Wind events and benthic-pelagic coupling in a shallow subtropical bay in Florida, Marine Ecology Progress Series 266: 1-13 Leblanc K, Queguiner B, Garcia N, Rimmelin P, Raimbault P (2003), Silicon cycle in the NW Mediterranean Sea: seasonal study of a coastal oligotrophic site, Oceanologica Acta 26: 339-355

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Legendre L, Demers S (1984), Towards dynamic biological oceanography and limnology, Canadian Journal of Fisheries and Aquatic Sciences 41: 2-19 Leinen M (1977), A normative calculation technic for determining opal in deep-sea sediments, Geochimica et Cosmochimica Acta 41: 671-676 Lisitzin AP (1972), Sedimentation in the world ocean. Society of economic paleontologist and mineralogists Special publication 17: 1-218 Loir M (2004), Guide des diatomées, Delachaux & Niestlé, Paris. 1-240 Lucea A, Duarte CM, Agusti S, Sondergaard M (2003), Nutrient (N, P and Si) and carbon partitioning in the stratified NW Mediterranean, Journal of Sea Research 49: 157-170 Macintyre HL, Geider LJ, Miller DC (1996), Microphytobenthos: the ecological role of the secret garden of unvegetated, shallow-water marine habitats. I. Distribution, abundance and primary production, Estuaries 19: 186-201 Maldonado M, Carmona MC, Velásquez Z, Puig A, Cruzado A, López A, Young C (2005), Silieous sponges as a silicon sink: an overlooked aspect of benthopelagic coupling in the marine silicon cycle, Limnology and Oceanography 50: 799-809 Maldonado M, Riesgo A, Bucci A, Rützler K (2010), Revisiting silicon budgets at a tropical continental shelf: silica standing stocks in sponges surpass those in diatoms, Limnology and Oceanography 55: 2001-2010 Margalef R (1978), Life-forms of phytoplankton as survival alternatives in an unstable environment, Oceanologica Acta 1: 493-509 Masó M, Duarte CM (1989), The spatial and temporal structure of hydrographic and phytoplankton biomass heterogeneity along the Catalan coast (NW Mediterranean), Journal of Marine Research 47: 813-827 Moriceau B, Garvey M, Ragueneau O, Passow U (2007), Evidence for reduced biogenic silica dissolution rates in diatom aggregates, Marine Ecology Progress Series 333: 129-142 Mortlock RA, Froelich PN (1989), A simple method for rapid determination of biogenic opal in pelagic marine sediments, Deep-Sea research 36: 1415-1426 Nelson DM, Dortch Q (1996), Silicic acid depletion and silicon limitation in the plume of the Mississippi River:evidence from kinetic studies in spring and summe, Marine Ecology Progress Series 136: 163-178 Nelson DM, Treguer P, Brzezinski MA, Leynaert A, Queguiner B (1995), Production and dissolution of biogenic silica in the ocean: revised global estimates, comparison with regional data and relationship to biogenic sedimentation, Global Biogeochemical Cycle 9: 359-372 Ni Longphuirt S (2006), Role du microphytobenthos dans le cycle dy silicium et le fonctionnement d'un ecosystème côtier: la Rade de Brest. PhD Thesis, Université de Bretagne Occidentale. 1-210 Nielsen TG, Kiorboe T (1991), Effects of a storm event on the structure of the pelagic food web with special emphasis on planktonic ciliates, Journal of plankton research 13: 35-51 Paasche E (1973), Silicon and the ecology of marine plankton diatoms. I. Thalassiosira pseudonana (Cyclotella nana) grown in a chemostat with silicate as limiting nutrient, Marine Biology 19: 117-126 Paasche E (1980), Silicon content of five marine plankton diatom species measured with a rapid filter method, Limnology and Oceanography 25: 474-480 Paasche E, Ostergren I (1980), The annual cycle of plankton diatom growth and silica production in the Inner Oslofjord, Limnology and Oceanography 25: 481-494

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Parsons TR, Takahashi M, Hargrave B (1977), Biological Oceanography Processes, Pergamon Press, New York p 1-332 Paterson DM, Black KS (1999), Water flow, sediment dynamics and benthic biology, in Advances in Ecological Research 29, ed. Nedwell DB and Raffaelli DG, 155- 186 Pokras E (1986), Preservation of fossil diatoms in Atlantic sediment cores-control by supply rate, Deep-Sea research 33: 893-902 Ragueneau O, Chauvaud L, Leynaert A, Thouzeau G, Paulet YM, Bonnet S, Lorrain A, Corvaisier R, Le Hir M, Kamatani A, Jean F, Clavier J (2002), Direct evidence of a biological active coastal silicate pump: ecological implications, Limnology and Oceanography 47: 1849-1854 Ragueneau O, Chauvaud L, Moriceau B, Leynaert A, Thouzeau G, Donval A, Le Loc'h F, Jean F (2005a), Biodeposition by an Invasive Suspension Feeder Impacts the Biogeochemical Cycle of Si in a Coastal Ecosystem (Bay of Brest, France), Biogeochemistry 75: 19-41 Ragueneau O, Gallinari M, Corrin L, Grandel S, Hall P, Hauvespre A, Lampitt RS, Rickert D, Stahl H, Tengberg A, Witbaard R (2001), The benthic silica cycle in the Northeast Atlantic: annual mass balance, seasonality, and importance of non- steady-state processes for the early diagenesis of biogenic opal in deep-sea sediments, Progress in Oceanography 50: 171-200 Ragueneau O, Savoye N, Del Amo Y, Cotten J, Tardiveau B, Leynaert A (2005b), A new method for the measurement of biogenic silica in suspended matter of coastal waters: using Si:Al ratios to correct for the mineral interference, Continental shelf research 25: 697-710 Ragueneau O, Tréguer P (1994), Detrermination of biogenic silica in coastal waters: applicability and limits of the alkaline digestion method, Marine Chemistry 45: 43-51 Ragueneau O, Tréguer P, Leynaert A, Anderson RF, Brzesinski MA, DeMaster DJ, Dugdale R, Dymond J, Fischer G, François R, Heinze C, Maier-Reimer E, Martin-Jézéquel V, Nelson DM, Quéguiner B (2000), A review of the Si cycle in the modern ocean:recent progress and missing gaps in the application of biogenic opal as a paleoproductivity proxy, Global and Planetary Change 26: 317-365 Revelante N, Williams WT, Bunt JS (1982), Temporal and spatial distribution of diatoms, dinoflagellates and trichodesmium in waters of the Great Barrier Reef, Journal of Experimental Marine Biology and Ecology 63: 27-45 Roelke DL (2000), Copepod food-quality threshold as a mechanism influencing phytoplankton succession and accumulation of biomass, and secondary productivity: a modeling study with management implications, Ecological Modelling 134: 274 Round FE, Crawford RM, Mann DG (1990), The Diatoms. Biology and morphology af the genera, Cambridge University Press, Melbourne, Australia. 1-747 Ryther JH (1969), Photosynthesis and fish production in the sea, Science 166: 72-76 Sherr E, Sherr B (1988), Role of microbes in pelagic food webs: a revised concept, Limnology and Oceanography 33: 1225-1227 Sigmon DE, Cahoon LB (1997), Comparative effects of benthic microalgae and phytoplankton on dissolved silica fluxes, Aquatic Microbial Ecology 13: 275- 284

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Smayda TJ (1990), Novel and nuisance phytoplankton blooms in the sea: Evidence for a global epidemic, in Toxic Marine Phytoplankton, ed. Graneli E, Sundstrom B, Edler R, and Anderson DM, Elsevier, New York. 29-40 Smetacek V (1999), Diatoms and the Ocean Carbon Cycle, Protist 150: 25-32 Sommer U (1998), Silicate and the functional geometry of marine phytoplankton, Journal of plankton research 20: 1853-1859 Taylor FJR, Hoppenrath M, and Saldarriaga JF(2008), Dinoflagellate diversity and distribution, Biodiversity Conservation 17: 407-418 Terlizzi A, Bevilacqua S, Fraschetti S, Boero F (2003), Taxonomic sufficiency and the increasing insufficiency of taxonomic expertise, Marine Pollution Bulletin 46: 556-561 Tilman D, Kilham SS, Kilham P (1982), Phytoplankton community ecology: the role of limiting nutrients, Annual Review of Ecology and Systematics 13: 349-372 Tréguer P, Gueneley S, Kamatani A (1988), Biogenic silica and particulate organic matter from the indian sector of the Southern Ocean, Marine Chemistry 23: 167- 180 Tréguer P, Nelson DM, Brzesinski MA, DeMaster DJ, Van Bennekom AJ, Kamatani A (1992), Protocol for determination of biogenic and of lithogenic silica in particulate matter. SO-JGOFS core parameter, Internal Report, 1-4 Tréguer P, Nelson DM, Van Bennekom AJ, DeMaster DJ, Leynaert A, Quéguiner B (1995), The silica balance of the world ocean: a reestimate, Science 268: 375- 379 Van Den Hoek C, Mann DG, and Jahns HM (1995), Algae, an introduction to phycology, Cambridge University Press, Cambridge, UK. 1-623 Webster IT, Ford PW, Hodgson B (2002), Microphytobenthos contribution to nutrient- phytoplankton dynamics in a shallow coastal lagoon, Estuaries 25: 540-551 Wollast R (1991), The coastal organic carbon cycle: fluxes, sources and sinks., in Ocean margin processes in global change, ed. Mantoura RFC, Martin JM, and Wollast R, Wiley-Interscience, New York. 365-382 http://www.algaebase.org http://www.cbd.int/GBO2 http://www.un.org/es/events/biodiversity2010 http://www.marbef.org http://planktonnet.sb-roscoff.fr http://ucjeps.berkeley.edu/INA.html http://www.ceab.csic.es/~oceanlab http://www.com.univ-mrs.fr/PHYTOCOM

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CAPÍTULO 2

CAPÍTULO 2. Objetivos

Objetivos

El presente trabajo de tesis pretende analizar la composición taxonómica y la variabilidad espacio-temporal de las comunidades de microalgas (microfitoplancton y microfitobentos) a diferentes escalas y en distintos sistemas costeros, así como sus relaciones con variables ambientales, especialmente con las concentraciones de nutrientes disueltos. En particular, pretende examinar las interacciones de las comunidades de microalgas con el ciclo biogeoquímico del silicio. Más específicamente, el presente trabajo se compone de tres estudios complementarios:

Estudio 1 – “Phytoplankton variability across a gradient of habitats over a tropical continental shelf”

Estudio 2 – “Spatial-temporal patterns of nutrients and phytoplankton communities in nearshore habitats of the NW Mediterranean”

Estudio 3 – “The silicon cycle in a coastal system: the role of benthic diatoms associated to maerl beds in the Bay of Brest (NE Atlantic)”

El Estudio 1 tiene por objetivo analizar las comunidades de fitoplancton considerando su variabilidad estacional (estación húmeda y seca) a lo largo de un gradiente de hábitats tropicales (océano abierto, arrecife externo, arrecifes parche, praderas de fanerógamas marinas e islas de manglar) asociados a un sistema de arrecife barrera en la plataforma continental de Belize (Caribe). Es el primer estudio completo de microfitoplancton para Belize y uno de los pocos estudios de diversidad de fitoplancton asociado a sistemas recifales y que ofrece una aproximación multi-hábitat. El objetivo del Estudio 2 es un análisis de la dinámica intra-anual en las concentraciones de nutrientes y de las comunidades de fitoplancton con derivaciones sobre el ciclo biogeoquímico del silicio a escala de hábitat y microhábitat, en una zona costera del Mediterráneo noroccidental. El interés de este estudio reside en que, mientras una mayoría de estudios sobre la variabilidad de nutrientes y fitoplancton analiza patrones en la columna de agua a nivel de meso-escala, la aproximación aquí

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CAPÍTULO 2. Objetivos presentada compara la capa demersal asociada a hábitats rocosos con la columna de agua sobrestante en fondos arenosos costeros poco profundos. El Estudio 3 tiene por objetivo investigar la diversidad de comunidades de diatomeas bentónicas inframareales del Atlántico Noreste asociadas al hábitat de maerl, cuantificar su contribución al stock de sílice biogénica del sistema, así como evaluar su variabilidad espacial dentro del hábitat. Es el primer estudio que analiza la variabilidad espacial de las comunidades de diatomeas bentónicas en el hábitat de maerl, además de su contribución al ciclo biogeoquímico del silicio a escala local. Los estudios realizados contribuyen al conocimiento de la diversidad de microfitoplancton y microfitobentos en distintos sistemas costeros y aportan información útil para futuros estudios ecológicos y ecofisiológicos. El análisis de las interrelaciones de las comunidades de microalgas con diversos factores ambientales y con ciclos biogeoquímicos ayudará a conocer mejor el funcionamiento de los sistemas litorales y contribuirá a mejorar los modelos predictivos frente a cambios antropogénicos y climáticos.

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CAPÍTULO 3

CAPÍTULO 3. Phytoplankton variability over a tropical continental shelf

Estudio 1

Phytoplankton variability across a gradient of habitats over a tropical continental shelf

3.1 Introduction On shallow tropical continental shelves, coral-reef systems promote remarkable habitat complexity, with a “patchwork” of adjacent and interconnected areas with specific benthic biological communities, such as reefs, seagrass meadows, and mangroves. Plankton constitutes a major source of food for these communities. Previous studies comparing zooplankton from reef-associated habitats, in the Caribbean and Pacific, found habitat-related differences in planktonic communities, from offshore to inshore, from exposed to sheltered areas. Moreover, many endemisms were described from lagoons, and a continuum between planktonic and epibenthic species assemblages was observed (Bakus 1964, Emery 1968, Johnson 1949, Johnson 1954, Odum and Odum 1955). On the other hand, detailed taxonomic studies of phytoplankton communities over different habitats are scarce, because less time-consuming measurements of chlorophyll a are routinely employed to quantitatively estimate total phytoplankton (Furnas et al 1990, Van Duyl et al 2002). In Australia, phytoplankton surveys over the Great Barrier Reef found the existence of a cross-shelf gradient of phytoplankton community types, with regional sub-systems, one a lagoonal, the other associated with patch reef and outer reef, and yet another associated with shallow, mangrove- dominated, inshore coastal channels (Marshall 1933, Revelante and Gilmartin 1982). In the Caribbean, only few studies have addressed the taxonomic composition of phytoplankton associated with the extensive seagrass beds and coral reefs (Faust 2000a, Furnas et al 1990, Hargraves 1982, Morton 2000), despite the ecological and physiographical importance of these habitats. Likewise, studies of mangrove phytoplankton seem to agree that its assemblages are rather peculiar and their

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CAPÍTULO 3. Phytoplankton variability over a tropical continental shelf composition variable with local conditions (Aké-Castillo and Vázquez 2008, Faust 1996, Faust 2000b, Kannan and Vasantha 1992, Mani 1992, Morton 2000, Santra et al 1991). Previous studies on microphytoplankton in Belizean waters focused mostly on some particular groups, that is, dinoflagellates (Faust 1990, Faust 1993a, Faust 1993b, Faust 1993c, Faust 1996, Faust 2000a, Faust 2000b, Faust 2004, Faust and Gulledge 1996, Morton and Faust 1997, Faust et al 2005), diatoms (Hargraves 1982), and coccolithophorids (Kling 1975). To our knowledge, a global comparison of the entire microphytoplankton community of major coastal habitats has hitherto not been made. The lack of taxonomic detail precludes us from understanding how and why phytoplankton communities change across these complex tropical shelves. Therefore, we initiated the current study to investigate the taxonomic composition and abundance of microphytoplankton assemblages along a gradient of habitats on the Belizean continental shelf, starting in offshore waters close to the shelf’s edge and continuing through a sequence of inshore habitats, including the fore reef, a lagoon patch reef, a seagrass bed, and an island mangrove.

3.2 Method

3.2.1 Study site and habitats The current study was conducted in the surroundings of Carrie Bow Cay (Belize, 16º49’48’’ N, 88º06’11’’ W), a small island situated 15.5 km from the nearest mainland at the southern reaches of the Belize barrier reef and base of a Smithsonian’s marine field station (Figure 3.1). In this area, the continental-shelf edge is topped by an intertidal reef barrier that is interrupted only by a few shallow (10-30 m), perpendicular channels or cuts; it separates the open ocean from an extensive lagoon and provides a variety of habitats (Rützler et al 2004, Rützler and Macintryre 1982). Facing east and the open ocean, there is a luxuriant fore reef, with a fore-reef slope dropping abruptly to some 200 m depth. Toward the west is the less exposed barrier back reef, followed by shallow (1-5 m) seagrass meadows and patch reefs, and, further inshore, an extensive, deeper (10-15 m) sandy lagoon dominated by sea grasses and interrupted by a few scattered patch reefs. Numerous mangrove islands are dispersed over the shallows of the barrier reef platform that delimits the outer (eastern) expanse of the lagoon. Water from the open ocean flows into the lagoon, over the reef and through the cuts across the

34

CAPÍTULO 3. Phytoplankton variability over a tropical continental shelf

barrier reef. Therefore, we expected to find an environmental gradient in terms of water quality (nutrients, temperature, salinity, oxygen, and others) and exposure to waves and currents when comparing open-water conditions with those in habitats such as different reef types, seagrass meadows, and mangroves. We investigated four major continental shelf habitats (fore reef, R; patch reef, P; Thalassia testudinum turtle-grass beds, T; and mangrove, M) and compared them with surface open waters (O) adjacent to the shelf edge (Figure 3.1). The outer fore reef was 12 to 15 m deep and made up of a diverse coral community. The patch reef was located just South of Carrie Bow Cay, in the channel (bottom depth 10-18 m) separating the island from Curlew Bank. The seagrass bed, dominated by dense stands of turtle grass, was located on a sandy lagoon bottom (10 m deep) to the West of Carrie Bow Cay. The studied mangrove was at Twin Cays, not quite 4 km northwest of Carrie Bow, and consisted of a lush community dominated, along the margins of tidal ponds and channels, by red mangrove (Rhizophora mangle); the two main parts of the island are separated by a tidal channel, about 10-100 m wide and 3-5 m deep. The channel is flanked by submerged red-mangrove stilt roots which are densely populated by macroalgae and benthic invertebrates.

Figure 3.1. Location and map of the study area on the Belizean continental shelf.

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CAPÍTULO 3. Phytoplankton variability over a tropical continental shelf

3.2.2 Environmental characterization Because of its distance from the mainland, the study area is little affected by continental runoffs. Water surface temperatures typically fluctuate from 18º C to 32º C (ocean mean temperature, 26º C) in January-March, and from 28º C to 41º C (ocean mean, 29º C) in July-September (Rützler et al 2004). Salinity in the open lagoon is fully oceanic, 35-36. Prevailing wind direction is northwest from October through February and northeast to east during the rest of the year. Monthly precipitation is lowest (0-25 mm) between March and May (during dry season), highest (100-480 mm) between June and November (during rainy season), with some interannual variability (Rützler and Ferraris 1982). The tide is micro-tidal and of mixed semidiurnal type, with a mean range of 15 cm and maximum fluctuations of 40 cm (Kjerfve et al 1982). By using the Smithsonian’s environmental monitoring system, with probes located at either the patch-reef or the reef crest, we measured some meteorological and hydrological variables that informed about general seasonal trends in the area during the year of study. We collected daily data of water temperature, salinity, dissolved oxygen, turbidity and rainfall during 2005 and 2006. From daily data we calculated monthly means and associated standard deviations (sd). Equipment limitations made it impossible to replicate observations for seagrasses and mangroves. The reef data could be used to identify trends of the meteorological variables over the year in the area, but did not allow assessment of between-habitat differences. On the other hand, concentrations of dissolved nutrients (silicates, phosphate, nitrite+nitrate) were measured for each particular habitat in both December 2005 and July 2006. Seawater samples were collected using Niskin bottles operated by scuba divers. Samples were taken at different depths in the water column overlaying each habitat and at various times of the day, then pooled for the analyses in an attempt to deal with potential depth and diel effects on nutrient distribution. Samples were also collected at 12 m depth from an open-water site (O) located 1.6 km offshore, in fully oceanic conditions and above a 200m-deep continental slope (Figure 3.1). This oceanic sampling was intended to serve as a reference value to be compared with those taken from inshore habitats. Immediately after collection, water samples for nutrient analysis were stored in refrigerated, acid-cleaned 20 ml polyethylene vials. Nutrient analysis was carried out using a TRAACS 2000 Autoanalyzer.

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CAPÍTULO 3. Phytoplankton variability over a tropical continental shelf

We examined differences in mean concentration of each nutrient as a function of season (December, July) and habitat (O, R, P, T, M) using two-way ANOVA (n=6 per season and habitat). To comply with normality and homoscedasticity requirements, analyses of silicate and phosphate data were made on rank-transformed data, while nitrite + nitrate data were Log-transformed. When required, pairwise Student-Newman- Keuls (SNK) tests were run to identify groups responsible for significant factors in the ANOVA. Nutrient ratios (N:P, Si:N, Si:P, considering N=nitrite+nitrate) were calculated and compared with the Redfield ratio of N:Si:P=16:16:1 (Redfield et al 1963), which gives an estimate of phytoplankton nutrient requirement. To examine global patterns in inter-sample similarities derived from collective nutrient values, we run a Multidimensional Scaling Analysis (MDS) and plotted sample scores in a bidimensional space. For the analysis, data were standardized by maximum and the inter-sample similarity matrix built using the Euclidean distance.

3.2.3 Phytoplankton community structure To study the specific abundance of microphytoplankton (diatoms, dinoflagellates, coccolithophorids and silicoflagellates), we collected water samples using Niskin bottles operated by scuba divers (n=3 per habitat and season), following a sampling design similar to that described for nutrients. Samples were stored in 100 ml vials, fixed with Lugol’s Iodine, settled using the Utermöhl settling technique (Utermöhl 1931), and observed with an inverted microscope. Microphytoplankton cells were counted and identified at the species level (whenever possible) to generate an abundance matrix. Taxonomic identifications were compared with a check-list of the phytoplankton previously known from Belizean waters, which had been compiled for the current study. To examine differences in phytoplankton abundance and composition as a function of season and habitat from different ecological perspectives, we used a variety of basic statistics, along with analyses of variance and multivariate techniques. We first determined species richness, Shannon diversity index (H’), and Pielou’s evenness (J’) per season and habitat for both total phytoplankton and each of the relevant groups (i.e., diatoms and dinoflagellates). Differences in abundance of total cells and of the dominant groups as a function of season and habitat were examined using a two-way

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CAPÍTULO 3. Phytoplankton variability over a tropical continental shelf

ANOVA on square-root-transformed data. “A posteriori” pairwise SNK tests were used to identify groups responsible for significant differences in the ANOVA. To examine global patterns in inter-sample similarities, we run a Multidimensional Scaling Analysis (MDS) based on square-root-transformed abundance data and an inter-sample Bray- Curtis dissimilarity matrix. Sample scores were plotted in a bidimensional space. To examine the role of season and habitat (n=3 per season and habitat) in determining the general patterns of phytoplankton abundance and composition, we used a Permutational Analysis of Variance (Anderson 2001) based on a Bray-Curtis dissimilarity matrix. Additionally, we performed a Similarity of Percentage (SIMPER) analysis to determine those species contributing most to the formation of major patterns. Finally, we assessed which proportion of the variability in the phytoplankton abundance matrix was explained by the measured environmental variables (i.e., nutrient concentrations and hydro-meteorological data sets) using a Canonical Correspondence Analysis (CCA). Rare species, i.e., those with total abundance throughout the sampling was less than 6 cells, were excluded. Abundance data were processed untransformed and the down-weighting option of the software (CANOCO Vo.4.5) selected. The initial environmental data matrix consisted of seasonal averages of nutrient concentration (silicate, phosphate, nitrite plus nitrate) and seasonal means of probe data (solar radiation, water temperature, salinity and rainfall). The latter were measured as the average of the data collected during each sampling period and a previous 30-days period. Nutrient and probe data were standardized by maximum. The relevance of the environmental variables to be considered in the analyses was checked by preliminary ‘‘manual addition’’ tests in a forward selection process, using a partial Monte-Carlo test to assess the usefulness of each variable. Each environmental variable was also tested separately by a Monte-Carlo permutation test to estimate its independent effect. Variables in the various trial models assayed were also checked for their inflation factor (VIF), finally discarding those with high factors, i.e., containing redundant information. The statistical significance of the first canonical axis and all canonical axes of the resulting models were tested by the Monte-Carlo test using 499 permutations under the reduced model or under the full model if covariables were considered in the analysis. Results are presented as a bi-dimensional ordination diagram with biplot scaling, in which habitats (and/or taxa) are represented by points and environmental variables by vectors.

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CAPÍTULO 3. Phytoplankton variability over a tropical continental shelf

3.3 Results 3.3.1 Environmental characterization Meteorological and hydrographical variables for 2005 and 2006 (Figure 3.2a) indicated modest water temperature variations over the year, with a minimum of about 26º C in January-February and a maximum of 30º C in September. Salinity values ranged from a minimum (32.1) in October 2005 to a maximum (37.3) in June 2006, depending on local rainfalls and evaporation (Figure 3.2a). Solar radiation was high from April to September (though with inter-annual differences), dropping from October to February (Figure 3.2b). Unlike solar radiation, dissolved oxygen values varied erratically through the year, with no evident seasonal trend (Figure 3.2b). During 2005, dissolved oxygen was nearly at saturation (80-100%) at all times, while values dropped to 45-50% at several times during 2006 (i.e., April, August and September). Turbidity and rainfall showed great daily variability all year round (Figure 3.2c). Interestingly, high turbidity was not always coupled to heavy rains but probably also caused by wind-generated sediment resuspension.

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CAPÍTULO 3. Phytoplankton variability over a tropical continental shelf

Figure 3.2. Monthly means (±sd) of meteorological and hydrological variables during 2005 and 2006. a) Temperature and salinity, b) solar radiation and dissolved oxygen, c) turbidity and rainfall.

The two-way ANOVA (Table 3.1; Figure 3.3) revealed that mean silicate concentrations were significantly higher (P<0.001) in July (4.027±0.626 µM) than in December (3.341±0.493 µM), that there were significant differences as a function of

40

CAPÍTULO 3. Phytoplankton variability over a tropical continental shelf

habitat (P<0.001), and that the magnitude of between-habitat differences depended on season (P<0.001). The “a posteriori” tests revealed mangrove to have a silicate concentration consistently higher than that of the remaining habitats, and that the relative ranking of silicate values among those remaining habitats varied with season (Figure 3.3). Concentrations of phosphate and nitrite+nitrate varied as a function of season and habitat, with no significant interaction (Table 3.1; Figure 3.3). In both cases, concentrations were significantly higher in July than in December. “A posteriori” tests also indicated that concentrations were consistently higher in mangroves than in the remaining habitats (Figure 3.3). Despite the fact that an environmental gradient is postulated to run from the open ocean across the fore reef, patch reef, and seagrass bed into the mangrove, minimum nutrient concentrations did not appear in the open ocean but in either the seagrass bed or patch reef (Figure 3.3). Nutrient ratios indicated P along with Si as being the co-limiting nutrients of planktonic primary production in December (12.2

Table 3.1. Results of two-way ANOVAs of nutrient concentrations as a function of Season and Habitat factors.

Silicate Phosphate Nitrite + nitrate

df F P F P F P

Season 1 125.08 <0.001 249.77 <0.001 15.91 <0.001 Habitat 4 43.55 <0.001 10.12 <0.001 7.45 <0.001 Season x Habitat 4 14.06 <0.001 1.32 0.277 1.51 0.216

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CAPÍTULO 3. Phytoplankton variability over a tropical continental shelf

Figure 3.3. Nutrient concentrations in each habitat and season. a) Silicate, b) Phosphate, c) Nitrite + nitrate. Ju=July, De=December, O=open water, R=fore reef, P=patch reef, T=turtle-grass bed, M=mangrove. Letters at the upper part of the graphs refer to ‘‘a posteriori” SNK test following the two-way ANOVA. Groups of underlined letters indicate non-significant differences (P > 0.05) between pairs of means. Only the results for the “season” factor are represented here.

A MDS analysis examining between-sample relationships based on nutrient concentrations revealed that samples became spatially distributed along a more or less recognizable gradient resulting from a combination of axis I and II in the graph (Figure 3.4). However, the gradient of sample scores in the biplot did not follow the expected order in the field gradient, since the oceanic samples were not at the origin. In addition, July and December samples clearly differed from each other. Between-habitat

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CAPÍTULO 3. Phytoplankton variability over a tropical continental shelf

differences were more evident in the group of July samples than in the December group, with July mangrove samples being the most distinctive (Figure 3.4).

Figure 3.4. Multidimensional scaling of water samples based on nutrient concentrations standardised by maximum. Ju=July, De=December, O=open water, R=fore reef, P=patch reef, T=turtle-grass bed, M=mangrove.

3.3.2 Phytoplankton community structure In the 30 samples, we found a total of 17,455 phytoplankton cells belonging to 210 species, of which 127 were diatoms, 70 dinoflagellates, 12 coccolithophorids, and one a silicoflagellate (Supplementary Table 1 ANEXO 1, Photos 1-20 ANEXO 2). In terms of cell numbers, there was high between-sample variability (Figure 3.5a), mostly due to the variable abundance of both dinoflagellates and chain-forming diatoms. Diatoms were the most abundant group in all studied habitats in both seasons, representing at least 61% of all microphytoplankton cells (Figure 3.5b). The prevailing species were Thalassionema nitzschioides, Thalassionema frauenfeldii/bacillare, Chaetoceros affinis var. circinalis, Guinardia striata and Chaetoceros lorenzianus. Dinoflagellates followed diatoms in abundance. They were well represented in all habitats in December (e.g., Gymnodinium spp. and Gyrodinium spp.), whereas in July they were abundant only in mangrove samples (e.g., Prorocentrum spp.). Coccolithophorids were few, mostly found in the mangrove habitat. Silicoflagellates occurred in negligible numbers. At the first glance, mean cell numbers in oceanic samples (O), on the fore reef (R), and on the patch reef (P) appeared to be higher in July than December, while this pattern reversed in seagrass beds (T) and mangroves (M; Figure 3.5a). Nevertheless, a two-way ANOVA indicated that those patterns were not

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CAPÍTULO 3. Phytoplankton variability over a tropical continental shelf statistically significant. There was no significant difference in total cell abundance as a function of either “season” or “habitat” (Table 3.2; Figure 3.5a). Neither was the interaction term statistically significant. Because our phytoplankton sampling size was only three replicates per habitat and season, we cannot rule out that the power of the analysis (5% to 30%, depending on the ANOVA term) was responsible for the absence of significant differences. When cell abundance was analyzed separately for each of the major groups (i.e., diatoms and dinoflagellates), patterns differed depending on the group (Table 3.2; Figure 3.5c-d). A two-way ANOVA examining differences in mean abundance of diatoms as a function of season and habitat revealed that only the interaction term was significant (Table 3.2). “A posteriori” SNK tests indicated the explanation that only two habitats varied significantly with season, and those followed opposite trends. That is, significantly higher abundances occurred in the fore reef in July, while similarly high abundance occurred in the mangrove, but in December (Figure 3.5c). In the case of dinoflagellates, the ANOVA detected only significant differences as a function of season (i.e., higher abundances in December; Table 3.2) and the SNK tests corroborated that seasonal differences were particularly marked in the fore-reef habitat (Figure 3.5d).

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CAPÍTULO 3. Phytoplankton variability over a tropical continental shelf

Figure 3.5. Means (±sd) number of microphytoplankton cell per habitat and season. a) Number of total cells, b) Number of diatoms, c) Percent abundance per taxonomic group, d) Number of dinoflagellates. Ju=July, De=December, O=open water, R=fore reef, P=patch reef, T=turtle-grass bed, M=mangrove. Letters at the upper part of graphs refer to ‘‘a posteriori” SNK test following the two-way ANOVA. Groups of underlined letters indicate non-significant differences (P > 0.05) between pairs of means. Only the results for the “season” factor are represented here.

Table 3.2. Result of two-way ANOVAs on number of total microphytoplankton cells, diatoms and dinoflagellated, respectively, as a function of Season and Habitat factors.

Total cells Diatoms Dinoflagellates

df F P F P F P

Season 1 0.42 0.839 0.75 0.398 11.46 0.003 Habitat 4 1.12 0.377 0.38 0.821 1.97 0.140 Season x Habitat 4 2.58 0.070 4.76 0.008 0.33 0.853

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CAPÍTULO 3. Phytoplankton variability over a tropical continental shelf

Diversity and evenness indexes indicated that the phytoplankton assemblage was quite diverse (Figure 3.6), with all H’ values >2.50 and a mean J’=0.75. For diatoms, richness, diversity, and evenness increased through the putative ocean-mangrove gradient, but mostly in July (Figure 3.6). Dinoflagellates were somewhat less diverse, with mangrove July samples having higher J’ and species richness than the others (Figure 3.6). There was some “seasonal pattern” in the taxonomic composition of the phytoplankton assemblage, with 68 species recorded exclusively in July while only 31 occurring exclusively in December samples. As for habitats, 33 species were exclusive to mangroves, 17 to seagrass beds, ten to the patch-reef, three to the fore reef, and two to open water (Supplementary Table, ANEXO 1). Therefore, mangroves supported the most distinctive assemblage. Most diatoms exclusively occurring in mangrove were benthic species (e.g. Entomoneis gigantea), but also a few planktonic species only occurred there (e.g., Thalassiosira anguste-lineata). Furthermore, many dinoflagellates (particularly Prorocentrum spp.) that never appeared in samples from other habitats occurred in the mangrove.

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CAPÍTULO 3. Phytoplankton variability over a tropical continental shelf

Figure 3.6. Species richness (presented as S/10), Shannon diversity index (H’), and Pielou’s evenness (J’) for a) total microphytoplankton cells, b) diatoms and c) dinoflagellates per season and habitat. Ju=July, De=December, O=open water, R=fore reef, P=patch reef, T=turtle-grass bed, M=mangrove.

The MDS graph revealed a clear separation between July and December samples along the first axis, while the second axis was more related to minor between-habitat differences (Figure 3.7). Although a clear environmental gradient is not reflected in the score distribution, it must be noticed that oceanic samples appear to be more related to fore-reef and patch-reef samples than to seagrass-bed and mangrove samples. This pattern is likely to reflect a greater influence of the oceanic water on the fore reef and patch reef than on the other habitats. Within habitats, samples showed the greatest heterogeneity in mangroves, particularly during July because of high abundance of coccolithophorids and dinoflagellates. The PERMANOVA analysis corroborated that

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CAPÍTULO 3. Phytoplankton variability over a tropical continental shelf season and habitat factors have a significant effect on the species distribution (Table 3.3). Further, there was also a significant interaction between these factors, so that the magnitude of differences between habitats changed in a dissimilar way, depending on season.

Figure 3.7. Multidimensional Scaling (MDS) of samples as derived from square-root transformed specific abundances of microphytoplankton. Ju=July, De=December, O=open water, R=fore reef, P=patch reef, T=turtle-grass bed, M=mangrove.

Table 3.3. Results of a PERMANOVA examining differences in the specific composition of microphytoplankton as a function of Season and Habitat factors. p (perm)=probability of permutation test; P (MC) =probability of Monte-Carlo test.

df Pseudo-F p (perm) P (MC)

Season 1 11.31 <0.001 <0.001 Habitat 4 2.17 <0.001 0.002 Season x Habitat 4 1.44 0.008 0.038

The SIMPER analysis indicated a dissimilarity of 77.44% between December and July samples. December samples were more homogeneous (52.06% similarity) than July samples (39.09%). Seasonal differences were due either to species exclusively occurring during one season (e.g., A. glacialis, C. socialis, H. sinensis, E. zodiacus occurred only in July while C. laevis, C. laciniosus and Synedra sp. only in December) or to drastic seasonal changes in the relative abundance of some species (e.g., T. frauenfeldi/bacillare, T. nitzschioides, C. affinis var. circinalis abounded in July, while A. formosa, Navicula spp, N. closterium, Gymnodinium spp., Gyrodinium spp., in 48

CAPÍTULO 3. Phytoplankton variability over a tropical continental shelf

December). The SIMPER analysis also indicated that mangrove samples were peculiar. They could be clearly distinguished from those in the remaining habitats (Table 3.4), but also showed little internal relatedness, having an elevated intra-group dissimilarity (65%). The reason of this pattern was a relatively high abundance of Prorocentrum spp. dinoflagellates, several coccolithophorids, and benthic diatoms (e.g., Navicula spp., Entomoneis spp., Licmophora flabellata), as well as the scarcity of species that were abundant in other habitats (T. nitzschioides, C. affinis var. circinalis). The species matrix submitted to CCA excluded 54 rare species, which collectively accounted for 147 cells. The forward selection of environmental variables (i.e., nutrient concentrations, solar radiation, water temperature, salinity and rainfall; Table 3.5) revealed the collinearity of most hydro-meteorological variables, so that their individual contribution in explaining variability of species data cannot be determined. In addition, “Phosphate Concentration”, which was the most explanatory variable, turned out to be redundant with “Solar Radiation”, as indicated by extremely high VIF. Nevertheless, we included both nutrients and solar radiation in the final ordination model, because such an addition prompted the model to explain a supplementary 14.4% of variability. Axis 1 (Figure 3.8), which appeared clearly related to seasonal differences in phosphate concentrations and hydro-meteorological variables (solar radiation, temperature, salinity and rainfall), explained 25.8% of variability in species data and 49.8% of variability in the species-environment relation. Axis 2 (Figure 3.8) appeared more related to habitat differences, particularly those based on a combination of silicate and nitrite + nitrate concentrations. It explained 13.9% of variability in species data and 26.7% in the species-environment relation. The sum of all canonical eigenvalues explained 52% of the species variability. The relative position of habitats in the CCA biplot (Figure 3.8) strongly varied with season, as between-habitat differences were more marked in July than in December. Oceanic phytoplankton composition was well correlated with nutrient concentrations, as the low-nutrient December conditions were characterized by a relatively high abundance of small dinoflagellates, while the more fertile July favored the dominance of diatoms (see also Figure 3.5b). Seagrass and patch-reef environments seemed to be little influenced by the seasonal differences in silicate or nitrite + nitrate concentrations, since their position along that ordination axis hardly varied with season. Nevertheless, both habitats were significantly affected by higher phosphate in July. Mangrove showed a distinctive community, particularly in July, when abundance of dinoflagellates and coccolitophorids was high (see also SIMPER results in this section). 49

CAPÍTULO 3. Phytoplankton variability over a tropical continental shelf

Table 3.4. Between-habitat percent dissimilarity (Bray-Curtis) in the specific composition of microphytoplankton as derived from a SIMPER analysis.

O R P T M O 42.8 R 55.2 57.7 P 52.6 57.4 50.4 T 61.5 64.7 64.6 55.4 M 73.1 73.4 70.1 64.7 65.8

Table 3.5. Summary of the CCA output, showing t the percentage of total variability in the species data explained by each of the environmental variable as if it were the only explanatory one (variance explained by canonical eigenvalues=1.161 out of total variance=2.234), a long with the F-value, the significance level (P-value) of the Monte- Carlo test derived from 999 permutations, and the variable inflation factor.

Variables % explained F P (MC) VIF

Phosphate 0.55 2.64 0.004 2552.7 Solar radiation 0.55 2.64 0.003 2495.2 Temperature 0.55 2.64 0.002 0.0 Salinity 0.55 2.64 0.005 0.0 Rainfall 0.55 2.64 0.005 0.0 Nitrite + Nitrate 0.41 1.79 0.048 5.5 Silicate 0.32 1.35 0.211 3.8

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CAPÍTULO 3. Phytoplankton variability over a tropical continental shelf

Figure 3.8. Canonical Correspondence Analysis (CCA) based on specific abundances of microphytoplankton, depicting the relative positions of the studied habitats in each season in relation to the environmental variables and nutrient concentrations. Ju=July, De=December, O=open water, R=fore reef, P=patch reef, T=turtle-grass bed, M=mangrove. Numbers indicate some species of interest, as pointed by the SIMPER analysis (4=A. hyalina, 8=A. formosa, 10=A. glacialis, 19=C. affinis var. circinalis, 26=C. lascinosus, 89=T. anguste-lineata, 94=T. frauenfeldii/bacillare, 99=M. challengeri, 107=P. nigra, 120=Gymnodinium spp., 139=P. compressum, 142=P. mexicanum).

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CAPÍTULO 3. Phytoplankton variability over a tropical continental shelf

3.4 Discussion The microphytoplankton assemblage that we found in our study area was quite rich and diverse, dominated by diatoms which represented about 60% of the total cell number. Both, species composition and abundances in our study were similar to those reported by other authors from similar tropical environments (Faust 1995, Faust and Gulledge 1996, Faust 2000a, Faust 2000b, Morton 2000, Faust 2004, Faust and Tester 2004, Faust et al 2005). The most abundant diatoms in the study were not local but cosmopolitan species, some commonly found in the Mediterranean (e.g., Velásquez Forero, 1997) Diversity indexes were relatively high in all habitats, but an appreciable ocean-mangrove gradient in diversity or abundance was only recognizable for diatoms during July, which is in agreement with an inshore diversity increase found in the Great Barrier Reef (Revelante and Gilmartin 1982). In each habitat, the microphytoplankton community seemed to respond differently to seasonality, with differences stronger in July than in December. Habitats that receive a strong, direct input of oceanic waters (i.e., the fore reef and the patch reef) showed higher mean cell abundances in July compared to December, while the opposite trend appeared in the seagrass bed and the mangrove. These findings are consistent with previous reports from the Great Barrier Reef: phytoplankton biomass (estimated through Chl a) within semi-enclosed reef lagoons was found to be higher than that of adjacent shelf waters, although seasonal differences were only significant during July (Ricard and Delesalle 1982). In our study, mangroves showed the most distinctive microphytoplankton taxonomic pattern, particularly in July, with noticeable occurrence of dinoflagellates and coccolithophorids aggregated in some areas of the channels. In the case of dinoflagellates, both the ability of some species to actively swim and the ability to associate to floating detritus may favor the formation of aggregated, patchy distributions (Faust and Gulledge 1996). Despite all habitats being interconnected by the oceanic water flowing over the entire shelf, and despite species assemblages encountered at any given time and habitat not being precisely recurring time and again, our results support Revelante and co- authors’ view (Revelante et al 1982) that strong environmentally-determined patterns may be sufficiently robust to transcend the particular species-assemblages which serve to define them on any given occasion. In other words, even though we are aware that the assemblages we are describing may not be permanent in a given habitat, local

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CAPÍTULO 3. Phytoplankton variability over a tropical continental shelf

environmental conditions (in terms of nutrients, flushing rate, light, salinity etc.), seem to favour some species to proliferate to the detriment of others, and the net results of these environmental pressures are between-habitat differences during most of the annual cycle. When water flows from offshore over the reef, the patch-reef and turtle-grass habitats, and through the mangrove channels, local planktonic and benthic communities may alter the incoming nutrient budget by excretion and uptake; the net result depends on the local biological communities, and, probably, to physical factors as wind-driven sediment resuspension (e.g., Revelante and Gilmartin 1982, Arfi et al 1993, Lawrence et al 2004). Indeed, our results showed marked between-season differences in some important environmental variables (seawater temperature, solar irradiance, salinity, rainfall and nutrients), which appear to cause between-season differences in the taxonomic composition of microphytoplankton. Although an environmental gradient from offshore to inshore was expected in the study area (Herndl 1991), such gradient was not corroborated by the nutrient content in seawater. Neither was it clearly confirmed by the analyses of the microphytoplankton assemblages. The observed budgets in dissolved nutrients emphasized the distinctiveness and complexity of the studied system, a shallow, tropical coral reef quite far from the mainland, and with associated island mangroves: nutrient concentrations were intermediate between those of other typically oligotrophic coral reefs (Shyka and Sebens 2000,Villareal et al 2000) and coastal waters enriched by river discharges and terrigenous inputs (Beucher et al 2004). Nutrient ratios confirmed the peculiarity of the system, indicating that planktonic primary production in the study area may be co- limited by combinations of nutrients, whose rank in importance as limiting factors depended primarily on season, and secondarily on habitat. Such a scale of temporal and spatial variability in nutrients is in agreement with nutrient dynamics described for the Great Barrier Reef (Revelante and Gilmartin 1982, Revelante et al 1982). The nutrient which showed the largest seasonal variation, responsible for altering seasonal nutrient ratios, was phosphate. Silicate proved to be limiting, or at least co-limiting, all year round, the effect being stronger in December when a relatively higher dinoflagellate:diatom ratio occurred, compared to July. The combination of silicate and nitrite + nitrate emphasized between-habitat differences. Surprisingly, offshore waters showed similar nutrient ratios as mangrove habitat, while T and P habitats were those whose nutrient ratios deviated most from the Redfield “optimum”. Microphytoplankton production in these habitats, probably limited by low nutrient concentration along with 53

CAPÍTULO 3. Phytoplankton variability over a tropical continental shelf increased grazing by plankton-feeders, is most likely sustained by the rapid regeneration of nutrients in the shallow, warm, clear waters (D’Elia and Wiebbe 1990), and by the rapid turnover of phytoplankton cells. In mangrove channels, the surrounding waters are enriched with major nutrients and many secondary compounds, owing to local regeneration from leaf-litter decomposition, in addition to stilt-root epibenthos and bacterial mat productivity (Kathiresan and Bingham 2001). In our study, July enrichment in phosphate may be caused by torrential rains which sweep debris rich in remineralized phosphate from mangrove habitat. Moreover, the specific hydrographic features created by the submerged mangrove roots attenuate the current regime and promote retention of nutrients. These properties, according to Margalef’s Mandala hypothesis (Margalef 1978, Margalef et al 1979, Faust et al 2005), are favorable to dinoflagellates and impel the formation of peculiar phytoplankton communities, facilitating primary productivity and phytoplankton diversity (Herrera-Silveira and Ramirez-Ramirez 1996, Rivera-Monroy et al 1998). Indeed, our mangrove samples showed the highest nutrient concentrations of all habitats and peculiar microphytoplankton assemblages, rich in dinoflagellates. However, in mangrove channels other limiting factors, such as tree-shading, high turbidity due to suspended particles, and surface-water temperature, in addition to large salinity fluctuations, may limit growth, especially in July (Kathiresan and Bingham 2001). Our results show that each habitat displayed particular microphytoplankton assemblages characterized by the relative abundances of different species. The studied environmental variables explained only partially the variability in the taxonomic composition and abundance of the microphytoplankton assemblages, so additional biogeochemical, physical and biological variables may be at action in the study area. In aquatic shallow systems, bentho-pelagic coupling plays a major role in determining the production and the structure of biological communities (e.g., Sommer 1989). Population dynamics of phytoplankton consumers, not investigated here, may have strong effects on the abundance and composition of local phytoplankton assemblages. It is also well demonstrated that the architectural structure of coral reefs creates hydrographic patterns that, in the long term, enhance retention of plankton from incoming waters, a mechanism that facilitates coral reef sustenance in nutrient-impoverished environments (Ayukai 1995). Glynn (Glynn 1973), in a 2-year study of a Caribbean coral reef, showed that reefs filter crossing waters with a retention efficiency of up to 91% for diatoms. 54

CAPÍTULO 3. Phytoplankton variability over a tropical continental shelf

While a few variables that we were unable to deal with in this study preclude unraveling specific factors that enhance phytoplankton diversity across the Belizean shelf, our results confirm marked, season-dependent differences between adjacent habitats. Our data show that the Mesoamerican Barrier Reef shelf off Belize is covered by a heterogenous water mass that provides for a substantial reservoir of phytoplankton diversity.

3.5 Acknowledgements This study has been developed in collaboration with Manuel Maldonado, Klaus Rützler and Zoila Velásquez. Thanks to Dan Miller, Claudette De Courley, Ana Riesgo, and Michelle Nestlerode for assisting with fieldwork, Tanya Rützler, Jim Taylor, and Martha Richotas for logistic support at the Smithsonian’s Marine Field Station at Carrie Bow Cay, and Antonio Cruzado for the access to the microscope and for commenting on the original manuscript. This research benefited from funds provided by a 2005-2006 grant from the Smithsonian’s Caribbean Coral Reef Ecosystems Program (CCRE contribution number 871), a FPU-2005-5369 fellowship and two grants (CTM2005- 05366/MAR; BFU2008- 00227/BMC) from the Spanish Government.

3.6 References Aké-Castillo JA, Vázquez G (2008), Phytoplankton variation and its relation to nutrients and allochthonous organic matter in a coastal lagoon on the Gulf of Mexico, Estuarine, Coastal and Shelf Science 78: 705-714 Anderson MJ (2001), A new method for non-parametric multivariate analysis of variance, Austral Ecology 26: 32-46 Arfi R, Guiral D, Bouvy M (1993), Wind induced resuspension in a shallow tropical lagoon, Estuarine, Coastal and Shelf Science 36, 587-604 Ayukai T (1995), Retention of phytoplankton and planktonic microbes on coral reefs within the Great Barrier Reef, Australia, Coral Reefs 14: 141-147 Bakus GJ (1964), The effects of fish grazing on invertebrate evolution in shallow tropical waters, Allan Hancock Foundation Occasional Papers 27: 1-29 Barnett AM, Jahn A (1987), Pattern and persistence of a nearshore planktonic ecosystem off Southern California, Continental Shelf Research 7, 1-25 Beucher C, Tréguer P, Corvaisier R, Hapette AM, Elskens M (2004), Production and dissolution of biosilica, and changing microphytoplancton dominance in the Bay of Brest (France), Marine Ecology Progress Series 267: 57-69

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D’Elia CF, Wiebbe WJ (1990), Biogeochemical nutrient cycles in coral-reef ecosystems, in Coral Reefs, Ecosystems of the world 25, ed. Dubinsky Z, Elsevier, Amsterdam, Netherlands, 49-74 Emery AL (1968), Preliminary observations on coral reef plankton., Limnology and Oceanography 13: 293-303 Faust MA (1990), Cysts of Prorocentrum marinum (Dinophyceae) in floating detritus at Twin Cays, Belize mangrove habitats, in Toxic Marine Phytoplankton, ed. Graneli E, Sundstrom B, Edler L, and Anderson DM, Elsevier, New York p 138- 142 Faust MA (1993a), A further SEM study of marine benthic dinoflagellates from a mangrove island, Twin Cays, Belize, including Plagiodinium belizeanum gen. et sp. nov., Journal of Phycology 29: 826-832 Faust MA (1993b), Prorocentrum belizeanum, Prorocentrum elegans, and Prorocentrum caribberanum, three new benthic species (Dinophyceae) from a mangrove island, Twin Cays, Belize, Journal of Phycology 29: 100-107 Faust MA (1993c), Surface morphology of the marine dinoflagellate Sinophysis microcephalus (Dinophyceae) from a mangrove island, Twin Cays, Belize, Journal of Phycology 29: 355-363 Faust MA (1995), Observation of sand-dwelling toxic dinoflagellates (Dinophyceae) from widely differing sites, including two new species, Journal of Phycology 31: 996-1003 Faust MA (1996), Dinoflagellates in a mangrove ecosystem, Twin Cays, Belize, Nova Hedwigia 112: 447-460 Faust MA (2000a), Dinoflagellate associations in a coral reef-mangrove ecosystem: Pelican and associated Cays, Belize, Atoll Research Bullettin 135-149 Faust MA (2000b), Biodiversity of planktonic dinoflagellate species in mangrove ponds, Pelican Cays, Belize, Journal of Phycology 36: 22 Faust MA (2004), The Dinoflagellates of Twin Cays, Belize: biodiversity, distribution and vulnerability, Atoll Research Bullettin 1-20 Faust MA, Gulledge RA (1996), Associations of microalgae and meiofauna in floating detritus at a mangrove island, Twin Cays, Belize, Journal of Experimental Marine Biology and Ecology 197: 159-175 Faust MA, Litaker RW, Vandersea MW, Kibler SR, Tester TA (2005), Dinoflagellate diversity and abundance in two Belizean coral-reef mangrove lagoons: A test of Margalef's mandala, Atoll Research Bullettin 531-542: 103-131 Faust MA, Tester TA (2004), Harmful dinoflagellates in the gulf stream and Atlantic barrier coral reef, Belize, in Xth International Conference on Harmful Algae, 2002, Florida Fish and Wildlife Conservation Commission and Intergovernmental Oceanographic Commission of UNESCO, ed. Steidinger KA, Landsberg JH, Tomas CR, and Vargo CA. 326-328 Furnas MJ, Mitchell AW, Gilmartin M, Revelante N (1990), Phytoplankton biomass and primary production in semi-enclosed reef lagoons of the central Great Barrier Reel Australia, Coral Reefs 9: 1-10 Glynn PW (1973), Ecology of a Caribbean coral reef. The Porites reef-flat biotope: part II. Plankton community with evidence for depletion, Marine Biology 22: 21 Hargraves PE (1982), Plankton diatoms (Bacillariophyceae) from Carrie Bow Cay, Belize, in The Atlantic barrier ecosystems at Carrie Bow Cay, Belize, I: Structure and Communities, ed. Rützler K and Macintryre IG, Smithsonian Institution Press, Washington, USA. 153-166

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Herndl GJ (1991), Microbial biomass dynamics along a trophic gradient at the Atlantic Barrier Reef off Belize (Central America), Marine Ecology 12: 41-51 Herrera-Silveira JA, Ramirez-Ramirez J (1996), Effects of natural phenolic material (tannin) on phytoplankton growth, Limnology and Oceanography 41: 1018-1023 Johnson MW (1949), Zooplankton as an index of water exchange between Bikini Lagoon and the open sea., Transactions - American Geophysical Union 30: 238- 244 Johnson MW (1954), Plankton of the Northern Marshall Islands, U.S. Geological Survey Professional Paper 260: 301-314 Kannan L, Vasantha K (1992), Microphytoplankton of the Pichavaram mangals, southeast coast of India: Species composition and population density., Hydrobiologia 247: 77-86 Kathiresan K, Bingham BL (2001), Biology of Mangroves and Mangrove Ecosystems, in Advances in Marine Biology, ed. Southward A, Tyler P, Young C, and Fuiman L, Academic Press, London, UK. 81-251 Kjerfve B, Rützler K, Kierspe GH (1982), Tides at Carrie Bow Cay, Belize, in Atlantic Barrier Reef Ecosystem at Carrir Bow Cay, Belize., Srnithsonian Institution Press. 53-58 Kling SA (1975), A lagoonal coccolithophore flora from Belize (British Honduras), Micropaleontology 21: 1-13 Lawrence D, Dagg MJ, Liu H, Cummings SR, Ortner PB, Kelble C (2004), Wind events and benthic-pelagic coupling in a shallow subtropical bay in Florida, Marine Ecology Progress Series 266: 1-13 Mani P (1992), Natural phytoplankton communities in Pichavaram mangroves, Indian Journal of Marine Sciences 21: 278-280 Margalef R (1978), Life-forms of phytoplankton as survival alternatives in an unstable environment, Oceanologica Acta 1: 493-509 Margalef R, Estrada M, Blasco D (1979), Functional morphology of organisms involved in red tides, as adapted to deacaying turbulence, in Toxic Dinoflagellate Blooms, ed. Taylor D and Seliger H, Elsevier, New York,USA. 89-94 Marshall S (1933), The production of microplankton in the Great Barrier Reef region., Scientific Reports of the Great Barrier Reef Expedition 2: 111-157 Morton SL (2000), Phytoplankton ecology and distribution at Manatee Cay, Pelican Cays, Belize, Atoll Research Bullettin 125-132 Morton SL, Faust MA (1997), Survey of toxic epiphytic dinoflagellates from the Belizean barrier reef ecosystem, Bulletin of marine science 61: 899-906 Odum HT, Odum EP (1955), Trophic structure and productivity of a windward coral reef community on Eniwetok Atoll., Atoll.Ecological Monographs 25: 291-320 Redfield AC, Ketchum BH, Richards FA (1963), The influence of organisms on the composition of sea water, in The Sea, ed. Hill MN, Wiley-Interscience, NewYork, USA. 26-77 Revelante N, Gilmartin M (1982), Dynamics of phytoplankton in the Great Barrier Reef Lagoon, Journal of plankton research 4: 47-76 Revelante N, Williams WT, Bunt JS (1982), Temporal and spatial distribution of diatoms, dinoflagellates and trichodesmium in waters of the Great Barrier Reef, Journal of Experimental Marine Biology and Ecology 63: 27-45 Ricard M, Delesalle B (1982), Phytoplankton and primary production of the Scilly lagoon waters. Proceedings of the 4th International Coral Reef Symposium. 425- 429

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Rivera-Monroy V, Madden C, Day J, Twilley R, Vera-Herrera F, Alvarez-Guillén H (1998), Seasonal coupling of a tropical mangrove forest and an estuarine water column: enhancement of aquatic primary productivity, Hydrobiologia 379: 41- 53 Rützler K, Ferraris JD (1982), Terrestrial environment and climate. The Atlantic Barrier Reef Ecosystem at Carrie Bow Cay, Belize, in Smithsonian Contributions to the Marine Sciences, ed. Rützler K and Macintyre IG, 12: 77- 91 Rützler K, Goodbody I, Diaz C, Feller I, Macintyre IG (2004), The aquatic environment of Twin Cays, Belize, Atoll Research Bullettin 1-35 Rützler K, Macintryre IG (1982), The Atlantic barrier reef ecosystem at Carrie Bow Cay, Belize, I. Structure and communities, Smithsonian Institution Press, Washington, USA. 1-109 Santra SC, Pal UC, Choudhury A (1991), Marine phytoplankton of the mangrove delta region of West Bengal., Journal of Marine Biological Association of India 33: 292-307 Shyka TA, Sebens KP (2000), Community structure, water column nutrients, and water flow in two Pelican Cays Ponds, Belize, Atoll Research Bullettin 105-121 Sommer U (1989), Plankton ecology: succession in plankton communities. Springer, Berlin, Germany. 1-369 Utermöhl H (1931), Neue wege in der quantitativen erfassung des planktons (mit besonderer berücksichtigung des ultraplanktons), Internationale Vereinigung fuer Theoretische und Angewandte Limnologie 5: 567-596 Van Duyl FC, Gast GJ, Steinhoff W, Kloff S, Veldhuis MJW, Bak RPM (2002), Factors influencing the short-term variation in phytoplankton composition and biomass in coral reef waters, Coral Reefs 21: 293-306 Velásquez Forero ZR (1997), Fitopláncton en el Mediterráneo Noroccidental. PhD Thesis. Universitat Politècnica de Catalunya. 1-329 Villareal TA, Morton SL, Gardner GB (2000), Hydrography of a semi-enclosed mangrove lagoon, Manatee Cays, Belize, Atoll Research Bullettin 87-103 Walsh JJ (1981), Shelf-sea ecosystems, in Analysis of marine ecosystems, ed. Longhurst AR, Academic Press, London, UK. 159-234

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Capítulo 4

CAPÍTULO 4. Spatial-temporal patterns of nutrients and phytoplankton in the NW Mediterranean

Estudio 2

Spatial-temporal patterns of nutrients and phytoplankton communities in nearshore habitats of the NW Mediterranean

4.1 Introduction Many studies have investigated distribution of nutrients and phytoplankton in nearshore systems at the mesoscale level (Estrada 1979, Masó and Duarte 1989, Velásquez Forero 1997, Flexas 2003), but patterns at smaller scales, and especially in wave-exposed rocky coasts, have seldom been examined (Barnett and Jahn 1987, Menge et al 1997, Wieters et al 2003). The aim of this study was to investigate the year-round pattern of nutrient concentrations and of microphytoplankton assemblages at the habitat and microhabitat scales in nearshore waters of a wave-exposed coastal zone in the NW Mediterranean.

4.2 Method

4.2.1 Study site The study was carried out at the coast of Blanes (41º40’24’’N, 002º48'11 E; Spain, NW Mediterranean; Figure 4.1a). The coastline, NE-SW directed, faces the open waters of a major regional current, the Catalan current, which runs parallel to shore (Font et al 1988). Nevertheless, local winds, storms and daily breezes may alter this prevailing hydrodynamic pattern, resulting in short-term shallow currents of variable direction and intensity (Flexas 2003). The coastline is mainly constituted by granitic rocks, interrupted by small, coarse-sand coves. In this coastal environment, we analyzed and compared two habitats: a) a 37 m deep water column (C) over a sandy bottom located about 1.5 km from the shoreline, 61

CAPÍTULO 4. Spatial-temporal patterns of nutrients and phytoplankton in the NW Mediterranean and b) the demersal water layer (or “boundary layer”, 0.5 m thick) associated with 15 m-deep rocky bottoms (R), located about 200 m from the shoreline. Within the water- column habitat, we considered three microhabitats, corresponding to three sampling depths, i.e., 3, 15 and 34 m depth, hereafter referred to as “C3”, “C15” and “C34” (Figure 4.1a,b). Within the rocky-bottom habitat, two microhabitats were considered: a) the boundary layer of horizontal, light-exposed rocks (referred to as “HR”), which were covered by a dense macroalgal community; and b) the boundary layer of overhangs and shaded rocky walls (“VR”; Figure 4.1a,b), which hosted a dense semi- sciaphilic community of filter-feeding and plankton-grazing invertebrates. A detailed description of the taxonomic composition of these local benthic communities can be found elsewhere (Biblioni et al 1982).

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Figure 4.1. The study area: a) location of the two habitats, indicated as C (the water- column habitat) and R (the rocky-bottom habitat); b) diagram representing a vertical section of the study area. The dotted vertical line indicates the position of the water- column CTD profiles. Microhabitat of the water column, at 3, 15 and 34 m depth, are indicated as C3, C15 and C34, respectively. HR and VR indicate the two microhabitats of the rocky substratum.

4.2.2 Nutrients and environmental characterization To analyze concentrations of inorganic nutrients (i.e., silicate, phosphate, nitrite+nitrate and ammonium), we collected seawater samples from all 5 microhabitats monthly, from January to December 2007. Samples from the water column (i.e., C3, C15 and C34; n=5 per depth and month) were collected using a Niskin bottle operated from a small oceanographic boat. Immediately after, we collected samples from the two boundary-

63

CAPÍTULO 4. Spatial-temporal patterns of nutrients and phytoplankton in the NW Mediterranean layer microhabitats (i.e., HR and VR; n=5 per microhabitat and month) using 50 ml acid-cleaned syringes on SCUBA dives. Upon collection, all samples were stored in refrigerated, acid-cleaned 20 mL polyethylene vials in dark. Nutrient analyses took place 24 hours after collection, using colorimetric methods by means of a TRAACS 2000 Autoanalyzer. These data served to estimate monthly averages of nutrient concentrations for each microhabitat. Since nutrient exhaustion is one of the factors which may control phytoplankton development, we investigated which of the analyzed nutrients may be regarded as limiting, in the sense of “Liebig’s law of minimum”, and ranked them in order of importance as potential limiting nutrient (PLN; Leblanc et al 2003). In order to detect the PLN at each microhabitat, we calculated nutrient ratios. We considered dissolved inorganic nitrogen compounds (DIN=NO2+NO3+NH4) as “N”. We compared the observed nutrient ratios with the Brzezinski ratio N:Si:P=16:16:1 (Brzesinski et al 2003), which is derived from the composition of biogenic matter for living diatoms and gives an estimate of nutrient requirement for phytoplankton development. A bi-dimensional chart was drawn, where the Si:N=1, Si:P=16 and N:P=16 lines delimited six areas, each indicating a different order of importance as PLN (Leblanc et al 2003). Therefore, each sample, which is characterized by a specific Si:N, Si:P and N:P ratio, will be plotted in the chart, falling in one of the six areas, thus revealing the rank of nutrients as potentially limiting elements. Moreover, the distance of a plotted sample to the intersection of the three lines Si:N=1, Si:P=16 and N:P=16 will indicate the magnitude of its deviation from the theoretical Brzezinski nutrient ratio. Concurrently with sampling of microhabitats for nutrient determination, we collected 1 L seawater samples (n=3 per microhabitat and month) for biogenic silica (BSi) analyses, using a Niskin bottle and storing refrigerated samples in dark, in acid- cleaned plastic bottles. Rocky-microhabitat samples (HR and VR) were also collected using a Niskin bottle, but operated by SCUBA divers rather than from the boat. The bottle was placed and gently moved parallel to the bottom, at about 10 cm from it, and closed carefully to avoid any resuspension of sediment. Two to four hours after collection, seawater samples were filtered through polycarbonate membrane filters (4.7 cm in diameter, 0.6 μm pore size) using a vacuum pump. Filters were dried at 60ºC, folded, and stored in refrigerator until being subjected to a double, wet-alkaline digestion to discriminate between Si derived from biogenic silica and lithogenic sources

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CAPÍTULO 4. Spatial-temporal patterns of nutrients and phytoplankton in the NW Mediterranean

(Ragueneau et al 2005). After each alkaline digestion of filters, silicate concentrations were determined by autoanalyzer. Aluminum concentrations were determined using a colorimetric method (Grasshoff et al 1983). From these digestions, we estimated averages of BSi per habitat and month. During each monthly sampling of the water-column habitat, we also registered profiles of water temperature (ºC), salinity (Practical Salinity Scale) and chlorophyll a (mg m-3), using a SeaBird 19 Plus CTD probe. Profiles had a vertical resolution of 10 cm. To simplify representation of the course of these variables over the year cycle, we plotted data corresponding only to 3, 15 and 34 m depths in the profiles, which are those most relevant to our phytoplankton and nutrient samples. To provide also a summarized approximate view of variability of Chl a profile in the entire nearshore water column over the year, we represented seasonally-averaged profiles pooling monthly data into seasons by considering January, February and December as winter (Wi), March, April and May as spring (Sp), June, July and August as summer (Su), September, October and November as autumn (Au).

4.2.3 Phytoplankton community structure To investigate phytoplankton, water samples from the microhabitats of both habitats (water column: C3, C15, C34; rocky bottom: HR, HV) were collected following the sampling techniques described for the biogenic silica. Subsamples (100 mL, n=1 per microhabitat and month) were immediately preserved in Lugol’s iodine and refrigerated until their study through an inverted microscope, using Utermöhl settling technique (Utermöhl 1931). To determine the taxonomic composition of phytoplankton communities at the various microhabitats, microphytoplankton cells were classified at the species level and counted, generating a “species x sample” matrix. We determined abundance of total cells and the relative importance of each group at each microhabitat each month. In addition to phytoplankton cells in our samples, we counted the abundance of fecal pellets produced by zooplanktonic organisms. In order to examine differences in abundance of total cells, abundance of diatoms, and abundance of dinoflagellates as a function of “season” (Wi, Sp, Su, Au) and “microhabitat” (i.e., C3, C15, C34 HR and VR), we performed two-way ANOVAs on ln-transformed abundance data. Since our low replication (n=3 per microhabitat and

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CAPÍTULO 4. Spatial-temporal patterns of nutrients and phytoplankton in the NW Mediterranean season) only allowed minimum power in the analysis, we decided to run a more solid comparison at the habitat level. For that, we pooled the samples of the two rocky- bottom microhabitats (HR, VR) and the two deepest microhabitats of the water-column habitat (i.e., C15, C34) to examine differences in cell abundance as a function of both “habitat” (C, R) and “season” (Wi, Sp, Su, Au) with a balanced design, using a two-way ANOVA on ln-transformed data (n=6 per habitat and season). We considered C15 and C34 samples rather than C3, because they are viewed as more comparable to those of the rocky-bottom habitat, in terms of light and of proximity to the bottom. “A posteriori” pairwise SNK tests followed to the ANOVAs to identify groups responsible for significant differences in the ANOVAs. We applied the same analysis scheme as explained for the ANOVAs (“season” and “microhabitat”; “season” and “habitat”, with the balanced design obtained by pooling HR, VR, C15, C34) to examine patterns of variability in the specific composition and abundance of phytoplankton (as a whole, then in diatoms and dinoflagellates separately), by means of a two-factor Permutational Analysis of Variance (PERMANOVA) under a reduced model (Anderson 2001). The PERMANOVAs were based on a Bray-Curtis dissimilarity matrix of Log-transformed specific abundance and used 999 permutations. To validate our result, we considered the number of unique permutations as an index of the reliability of the permutational P- value (Anderson 2005). To summarize the main trends in the succession of species in the water-column habitat throughout the year, we plotted monthly averages of cell abundance for the dominant species. To examine global patterns of inter-sample variability derived from phytoplankton specific abundances and to evaluate at which proportion the variability in the phytoplankton assemblages was explained by the measured environmental variables (i.e., seawater temperature, salinity and nutrient concentration), we performed a Canonical Correspondence Analysis (CCA). Abundance data were processed untransformed and the down-weighting option of the software (CANOCO Vo.4.5) selected. Seawater temperature, salinity and nutrient data were standardized by maximum. To rank the environmental variables according to their relevance in explaining the variability in the species data, we used a forward selection procedure, with a partial Monte Carlo test to assess the usefulness of each variable to be considered in the final ordination model. Previously, each environmental variable had been tested

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CAPÍTULO 4. Spatial-temporal patterns of nutrients and phytoplankton in the NW Mediterranean separately by a Monte Carlo permutation test to assess its independent effect. Variables in the various trial models assayed were also checked for their inflation factor (VIF), finally discarding those with high VIFs, i.e., containing redundant information. The statistical significance of the first canonical axis and of all canonical axes of the resulting models were tested by the Monte Carlo test using 499 permutations under the reduced model. Results are presented as bi-dimensional ordination diagrams with biplot scaling, in which samples (or taxa) are represented by points (or crosses) and environmental variables by vectors.

4.3 Results

4.3.1 Environmental characterization and nutrients Mean temperature in the water column showed a unimodal pattern throughout the year, ranging from 13.4 ºC to 23.4 ºC, with maximum in summer (Figure 4.2a). From May through September, shallow water was warmer than that at depths of 15 m and 34 m. In October and November, we observed this pattern to reverse transiently. Throughout most of the year, salinity ranged between 37.7 and 38.2, with higher values in winter than in summer and a minimum in May (Figure 4.2b). From June through November, surface water was less saline than the rest of the year. In October, salinity showed an abrupt episodic drop, reaching transiently brackish water values (20.2-24.6), being the least saline water at the surface. Fluorescence values from CTD readings showed a trimodal pattern in chlorophyll a over the year, with concentrations ranging from a minimum of 0.106 mg m-3 at 3 m depth in July to a maximum of 0.447 mg m-3 at 34 m depth in March. Maxima at the depths of interest in the water-column habitat (i.e., C3, C15 and C34) did not always co-occur (Figure 4.2c). On average, profiles revealed that chlorophyll a concentration was highest in spring and lowest in summer, and, in both seasons increasing with increasing depth (Figure 4.3). In winter and autumn, seasonally-averaged profiles of chlorophyll a concentration showed reduced variation with depth.

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CAPÍTULO 4. Spatial-temporal patterns of nutrients and phytoplankton in the NW Mediterranean

Figure 4.2. CTD monthly data (±sd) at 3, 15 and 34 m depth of a) temperature, b) salinity and c) chlorophyll a concentration.

Figure 4.3. Vertical profiles of chlorophyll a concentration data in the water column (seasonal means). Winter: January, February and December; spring: March, April and May; summer: June, July and August; autumn: September, October and November.

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CAPÍTULO 4. Spatial-temporal patterns of nutrients and phytoplankton in the NW Mediterranean

Monthly concentrations of nutrients (i.e. silicate, phosphate, nitrite+nitrate and ammonium) reflected seasonal trends and, occasionally, values strongly varied between microhabitats (Figure 4.4). Silicate concentrations (Figure 4.4a) were always ≤1.5 µM, dropping to values <0.5 µM in March, May, June, and August. Phosphate concentrations (Figure 4.4b) were low (near detection limit) throughout the year, with subtle increases in February and August. Nitrite+nitrate concentrations remained low throughout the year, being slightly higher in February and November-December (~2.0 µM). Ammonium (Figure 4.4d), unlike the remaining nutrients, showed marked differences in concentration between the water-column and the rocky-bottom habitats. In the water-column habitat, we detected relatively high values in February (1.7 µM), a strong decrease in March, and a new rise from summer through October. Rocky-bottom samples differentiated from water-column samples because of their much higher ammonium concentrations, especially in January, April, May, and October. Abnormally high P and N concentrations detected in January and February in some rocky-bottom samples (Figure 4.4b-c) were probably due to either accidental resuspension of bottom particles during sampling or to excretory pulses of the sessile and demersal fauna associated to these bottoms.

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CAPÍTULO 4. Spatial-temporal patterns of nutrients and phytoplankton in the NW Mediterranean

Figure 4.4. Monthly concentration of macronutrients (mean ±sd): a) silicate, b) phosphate, c) nitrite+nitrate, d) ammonium. On the left, values of the three microhabitats of the water-column habitat (C3, C15 and C34), on the right, values of the two microhabitats of the rocky-bottom habitat (VR and HR). *Note the difference between C and R scale of the ammonium concentration axis.

The order of importance of nutrients as potential limiting factors of primary production varied substantially as a function of habitat (water column or rocky-bottom boundary layer) and month, with a minor influence of microhabitat (Figure 4.5; Table 4.1). Most of the rocky-bottom samples fell in the area of the chart that pointed to silicon as the main PLN, followed by P and N, respectively (Figure 4.5); however, they were distributed far from the Brzezinsky ratio. On the other hand, water-column 70

CAPÍTULO 4. Spatial-temporal patterns of nutrients and phytoplankton in the NW Mediterranean samples spread over four of the six areas, but not as far from the theoretical ratio as the rocky-bottom samples. Silicon limitation was very obvious in the rocky-bottom samples, the Si:N ratio of which was never higher than 0.698, reaching values as low as 0.050 in January and March. The Si:N ratio of water-column samples ranged from 0.084 to 0.734 throughout the year, never reaching the Brzezinski ratio of Si:N=1, thus indicating either Si limitation or a co-limitation shared with phosphate. Average Si concentration data in the rocky-bottom boundary layer (0.602±0.027 µM) was lower than that found in the water-column habitat at equivalent depth (0.738±0.038 µM at 15 m). This suggests that the low Si:N values found in the boundary layer of rocky bottoms were due more to low silicate values than to high N levels. The N:P ratio in the water- column habitat ranged between a minimum of 6.897 in June (C34 was the only sample which showed N limitation) and a maximum of 50.013 in January, thus indicating that P was more limiting than N. In the boundary layer of rocky bottoms, the N:P ratio showed high variability, but it was always above the N:P=16, suggesting that N was never limiting there and that P was co-limiting element, along with silicon.

Figure 4.5. Si:N:P molar ratio of data collected from the water column (black diamonds) and from the boundary layer of rocky bottoms (white triangles). In each area, delimited by the Brzezinski ratio (Brzezinski 1985), the potential limiting nutrients (PLN) are reported in order of priority (inside the rectangles).

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Table 4.1. Potential limiting nutrient (PLN) in order of priority for each microhabitat and month. Microhabitat within the water–column habitat (C), at 3, 15 and 34 m depth, are indicated as C3, C15 and C34, respectively. HR and VR indicate the two microhabitats within the rocky bottom (horizontal and vertical rocks, respectively).

Month C microhabitat PLN R microhabitat PLN

Jan C3 P, Si, N VR Si, P, N Jan C15 P, Si, N HR Si, P, N Jan C34 P, Si, N Feb C3 Si, P, N VR Si, P, N Feb C15 Si, P, N HR Si, P, N Feb C34 Si, P, N Mar C3 Si, N, P VR Si, P, N Mar C15 Si, N, P HR Si, P, N Mar C34 Si, N, P Apr C3 Si, P, N VR Si, P, N Apr C15 P, Si, N HR Si, P, N Apr C34 P, Si, N May C3 Si, N, P VR Si, P, N May C15 Si, P, N HR Si, P, N May C34 P, Si, N Jun C3 Si, N, P VR Si, P, N Jun C15 Si, N, P HR Si, P, N Jun C34 N, Si, P Jul C3 Si, N, P VR Si, P, N Jul C15 Si, P, N HR P, Si, N Jul C34 P, Si, N Aug C3 Si, N, P VR Si, P, N Aug C15 Si, N, P HR Si, P, N Aug C34 Si, P, N Sep C3 Si, P, N VR Si, P, N Sep C15 Si, N, P HR Si, P, N Sep C34 Si, N, P Oct C3 Si, P, N VR Si, P, N Oct C15 Si, P, N HR P, Si, N Oct C34 Si, P, N Nov C3 Si, P, N VR P, Si, N Nov C15 P, Si, N HR P, Si, N Nov C34 Si, P, N Dec C3 Si, P, N VR P, Si, N Dec C15 P, Si, N HR P, Si, N Dec C34 Si, P, N

Monthly BSi and silicate stock showed inversely related concentrations during most of the year (Figure 4.6a, b), indicating the shift of silicon from particulate to dissolved form and vice versa. In March and, to a lesser extent, in August, BSi rose

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CAPÍTULO 4. Spatial-temporal patterns of nutrients and phytoplankton in the NW Mediterranean while silicate dropped in both the water-column and the rocky-bottom habitats (Figure 4.6a). From April until June, BSi showed a progressive decline, not correlated to an increase in silicate, suggesting a net export of silicon from the studied habitats (Figure 4.6). However, in July, when BSi reached a minimum, silicate increased again in both habitats (Figure 4.6a, c). The boundary layer of rocky bottoms showed more BSi than the water-column habitat (Figure 4.6a). When comparing the two rocky-bottom microhabitats, we expected BSi to be more abundant in the boundary layer of horizontal rocks than in that of vertical rocks due to sedimentation. Nevertheless, our data showed similar abundance of particulate silica in both microhabitats, or even higher abundance in the boundary layer of vertical rocks in some months (Figure 4.6b). Moreover, the BSi+silicate Si stock differed at habitat and microhabitat scale. The vertical rocky- bottom microhabitat showed, during most of the year, a pattern similar to that of the water column at the shallow and mid-depth microhabitats (Figure 4.6c, d), i.e., the lowest values from April through October and the highest in late autumn and winter (with a minor peak in July). In contrast, the deepest microhabitat of the water column showed a pattern in total Si that reflected that of dissolved silicate. The boundary layer of horizontal rocks showed a lower Si stock than that of vertical rocks until June, when this pattern reversed through September (Figure 4.6d).

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Figure 4.6. Monthly concentrations (mean ± sd) of a) biogenic silica (BSi) and silicate (DSi) in the water-column habitat (C) and in the rocky-bottom habitat (R); b) BSi and DSi in the vertical (VR) and horizontal (HR) rocky-bottom microhabitats; c) total silicon stock (BSi+DSi) at the three depths of the water-column habitat (C3, C15 and C34); d) total silicon stock in the vertical (VR) and horizontal (HR) rocky-bottom microhabitats.

4.3.2 Phytoplankton community structure Throughout the entire study (January-December 2007), we investigated a total of 60 samples, identifying 95,244 microphytoplankton cells. We found 123 species of diatoms, 91 of dinoflagellates, 15 of coccolithophorids and 1 of silicoflagellates. We also found occasionally cells of the chlorophyt Schroederia setigera (Schröder) Lemmermann (78 cells), which is a freshwater species (Supplementary Table 2 ANEXO 1, Photos 21-32 ANEXO 2). In general terms, abundance of total cells varied markedly throughout the year (Figure 4.7a), with a spring bloom in March (6464±714 cells/100 mL) and a secondary peak in August (2477±1240 cells/100 mL); minimum values were registered in July (257±75 cells/100 mL). Interestingly, not all microhabitats showed this same trend in cell abundance. For instance, cell abundance in “August-C34” sample was less than 1/6 the value of the remaining samples in that same month. In February, samples showed a decline in cell abundance in the water-column habitat, but an increase in the rocky- 74

CAPÍTULO 4. Spatial-temporal patterns of nutrients and phytoplankton in the NW Mediterranean bottom habitat. In October, “C3” and “C15” samples showed increased phytoplankton abundances, while the opposite happened in “C34” and all rocky-bottom samples. Diatoms were the most abundant group in all microhabitats during most of the year, accounting for up to 98% of cells during the spring bloom. However, in summer, the few cells found in the samples were mostly dinoflagellates (up to 92.6% in July; Figure 4.7b). Coccolithophorid abundance remained low throughout the year, with slight risings in August, September, and December. Silicoflagellates were scarce, occasionally found in late-autumn and winter samples (Figure 4.7a,b). The most abundant cells observed throughout the study were several diatoms of the genera Chaetoceros and Pseudo-nitzschia, also species such as Detonula pumila, Guinardia striata, Leptocylindrus danicus, along with small dinoflagellates of the genera Gymnodinium and Gyrodinium. We noticed a seasonal succession of dominant species (Figure 4.8), with Detonula pumila and Chaetoceros spp. dominating in March, Nitzschia longissima in April and G. striata in August. Other species, such as L. danicus, showed a trimodal abundance pattern, with peaks in March, June, and August (Figure 4.8). Some species were exclusively found in the boundary layer of the rocky-bottom habitat, never appearing in samples of the water-column habitat. Interestingly, some species found at the boundary layer of rocky bottoms occasionally occurred at the demersal sampling point (34m deep) of the water column overlying the adjacent soft bottom. Many of the species found in the boundary layer were benthic diatoms (e.g., Amphora hyalina, Licmophora sp., Toxarium undulatum) and dinoflagellates (Prorocentrum emarginatum, P. mexicanum, P. minimum, Protoperidinium conicum, P. diabolus and Dinophysis caudata). Surprisingly, clearly planktonic species, such as some Chaetoceros spp. appeared exclusively associated to the rocky-bottom boundary layer. Many species co-occurred in both the water-column and the rocky-bottom habitats, but showing, in many cases, different abundances depending on habitat. The clearest example was a much higher abundance of Cerataulina pelagica and Pseudo- solenia alata in the boundary layer than in the water column. In the water-column habitat, there were also species that are commonly found in both plankton and benthos (e.g., of the genera Pleurosigma and Diploneis). Abundance of fecal pellets was coupled with some delay to the main phytoplankton Spring peak, showing a maximum in April (54±27 in 100 mL). Nevertheless, fecal pellets peaked again in July-August, while phytoplankton abundance only peaked in August (Figure 4.7c). 75

CAPÍTULO 4. Spatial-temporal patterns of nutrients and phytoplankton in the NW Mediterranean

Figure 4.7. a) Monthly cell abundance per microhabitat (C3, C15, C34, VR, and HR); b) monthly percentage abundance of the main taxonomic groups (diatoms, dinoflagellates, coccolithophorids, silicoflagellates) per microhabitat (A, B, C, D and E are, respectively, C3, C15, C34, VR and HR); c) monthly abundance of fecal pellets (mean ±sd).

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Figure 4.8. Monthly mean number of cells (±sd) of dominant species, i.e., Chaetoceros spp., Guinardia striata, Leptocilyndrus danicus and Nitzschia longissima.

The two-way ANOVAs as a function of either “season” and “habitat” or “season” and “microhabitat” detected significant between-season differences in cell abundance when the entire community, diatoms, and dinoflagellates were respectively analyzed (Table 4.2). No significant between-habitat or between-microhabitat differences were detected in abundance of total cells or diatoms; but significant microhabitat differences occurred for dinoflagellates (Table 4.2). The SNK test revealed dinoflagellate abundances at 3 m depth being higher than at 34 m depth. When the entire phytoplankton assemblage was analyzed with PERMANOVA as a function of “season” and “habitat”, significant between-season and between-habitat differences in specific composition were detected (Table 4.2). When diatom and dinoflagellate communities were analyzed separately as a function of “season” and “habitat”, between-season differences were detected. Between-habitat differences for diatoms and dinoflagellates were not statistically significant (nevertheless the P value for diatoms was close to significance), thus indicating that the between-habitat differences detected for the entire phytoplankton assemblage were due to the abundance of dinoflagellates relative to diatoms. When the entire phytoplankton assemblage, diatoms or dinoflagellates were analyzed as a function of “season” and “microhabitat”, between-season differences were always detected. Between-microhabitat differences for diatoms and dinoflagellates were not significant. Neither were they for the whole phytoplankton, but showed a value nearly significant (P=0.056, Table 4.2), indicating that the main between-microhabitat differences may be due to varying proportions of

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CAPÍTULO 4. Spatial-temporal patterns of nutrients and phytoplankton in the NW Mediterranean dinoflagellates and diatoms. A higher replication could possibly reveal statistically significant differences at least at the between-habitat level for diatoms and at the microhabitat level for the whole phytoplanktonic assemblage. It is noteworthy that the “season x habitat” and “season x microhabitat” interaction terms were never significant, indicating that the observed differences at habitat and microhabitat level were not season-dependent.

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Table 4.2. Results of the two-way ANOVAs and PERMANOVAs to assess differences in phytoplankton abundance of total cells and in specific composition as a function of “season” and “habitat” or “season and “microhabitat”. df=degrees of freedom; F and P=statistic and probability of the test; UP=unique permutations. P < 0.05, P < 0.01, P < 0.001.

ANOVAs Factors df F P

Total cells season 3 6.171 0.002* habitat 3 1.021 0.396 season X habitat 9 0.186 0.994 season 3 6.458 0.001** microhabitat 4 0.742 0.569 season X microhabitat 12 0.262 0.992 Diatoms season 3 4.253 0.012* habitat 1 0.586 0.629 season X habitat 3 0.150 0.997 season 3 4.818 0.006** microhabitat 4 0.560 0.693 season X microhabitat 12 0.121 1.000 Dinoflagellates season 3 14.108 <0.001*** habitat 1 2.729 0.060 season X habitat 3 0.395 0.928 season 3 11.619 <0.001*** microhabitat 4 2.667 0.046* season X microhabitat 12 0.813 0.636 PERMANOVAs df F P UP

The whole community season 3 10,660 0,001** 998 habitat 1 3,826 0,014* 999 season X habitat 3 0,267 0,875 999 season 3 10,250 0,001** 999 microhabitat 4 1,865 0,056 999 season X microhabitat 12 0,110 0,999 997 Diatoms season 3 7,081 0,001** 998 habitat 1 2,793 0,060 998 season X habitat 3 0,277 0,909 997 season 3 3,890 0,001** 996 microhabitat 4 0.862 0.739 999 season X microhabitat 12 0.519 1.000 998 Dinoflagellates season 3 3,003 0,001** 997 habitat 1 1,301 0,181 999 season X habitat 3 0,888 0,708 998 season 3 5,394 0,001** 998 microhabitat 4 1,182 0,322 996 season X microhabitat 12 0,615 0,947 999

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The forward selection of environmental variables (i.e., seawater temperature, salinity and nutrient concentrations) for the CCA revealed the non-significance of ammonium when we tested the partial model (Table 4.3). When nitrite+nitrate concentration was added to the trial model, it resulted redundant with phosphate, as indicated by the inflation factors >>1 (Table 4.3). The final ordination model, therefore, included neither ammonium nor nitrite+nitrate. The selected model explained only 25% of total variability. Axe 1 (Figure 4.9), which appeared to be mostly related to water temperature (say also seasonal change in irradiance) and, to a lesser extent, to phosphate concentrations, explained 10.3% of variability in species data and 41.3% in the species- environment relationship. Axe 2 (Figure 4.9), positively associated with silicate concentrations and negatively with salinity values, explained 6.7% of variability in species data and 26.9 % in the species-environment relationship. Sample scores were relatively spread over the quadrants as a function of season, with winter samples on the negative domain of axis 1, summer samples on the positive region, and spring and autumn samples at intermediate positions (Figure 4.9). While winter and some autumn samples correlated positively with increasing silicate concentrations, spring and summer samples correlated negatively. Summer samples were also positively correlated with phosphate concentrations. Species scores also reflected these seasonal patterns. For instance, Chaetoceros and Nitzschia longissima became associated with spring samples, Proboscia alata with spring-summer samples, and most dinoflagellates with summer samples.

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Table 4.3. Summary of the CCA output. “% explained” is the percentage of total variability in the species data explained by each of the environmental variable as if it were the only explanatory one. The maximum amount of variance that can be explained by including all variables in the model is 0.982. “F” and “P” are the F-value and the significance level of the Monte-Carlo test after 499 permutations. Note that ammonium P is >0.05. The variable inflation factors (VIF) indicate some redundancy between nitrite+nitrate and phosphate (VIF1=considering all variables. VIF2=considering only those variables selected for the final ordination model).

Environmental % explained F P VIF 1 VIF 2 variable

Temperature 0.348 6.526 0.020 1.911 1.147 Silicate 0.238 4.314 0.020 1.602 1.143 Nitrite+nitrate 0.182 3.240 0.012 4.131 Salinity 0.179 3.177 0.004 1.205 1.031 Phosphate 0.126 2.204 0.028 2.968 1.047 Ammonium 0.080 1.379 0.122 1.045

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Figure 4.9.

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Figure 4.9. Canonical Correspondence Analysis of phytoplankton assemblages, depicting the relative positions of a) the samples and b) the species, in relation to the environmental variables (i.e., seawater temperature and salinity) and nutrient concentrations (silicate and phosphate). Winter: January, February and December; spring: March, April and May; summer: June, July and August; autumn: September, October and November. C=samples from the water-column habitat; R=samples from the rocky-bottom habitat. 19 Chaetoceros compressus, 23 C. danicus, 24 C. debilis, 27 C. didymus, 29 C. lauderi, 30 C. lorenzianus, 32 C. pendulus, 34 C. pseudocurvisetus, 62 Guinardia striata, 70 Leptocylindrus danicus, 78 Nitzschia longissima, 145 Neoceratium hexacanthum hexacanthum, 192 Podolampa bipes.

4.4 Discussion Throughout the study, we observed the typical NW Mediterranean seasonal patterns previously described in literature (e.g., Margalef 1978, Delgado et al 1992, Cebrián et al 1996, Mura et al 1996, Leblanc et al 2003). The studied coastal area is generally defined as oligotrophic, with low algal productivity (e.g., Masó and Duarte 1989, Mura et al 1996a, Velásquez Forero 1997, Lucea et al 2005). Our results showed that, despite the study being carried out in nearshore waters, nutrient concentrations were low over the year, also relative to those previously found in the close Blanes Bay or in other coastal habitats of the NW Mediterranean (Leblanc et al 2003, Lucea et al 2003). Microphytoplankton abundance, specific composition and chlorophyll a concentration were comparable to those found in literature for this area (Mura et al 1996a, Velásquez Forero 1997), It is noteworthy that chlorophyll a concentration was decoupled from cell abundance during most of the year, indicating variable chlorophyll content per cell as a function of depth (Cloern et al 1995). This result will be furthermore analyzed elsewhere. Phytoplankton abundance in the studied nearshore system appeared to be primarily limited by nutrient availability, so that grazing by zooplankton would be a secondary controlling factor (in agreement with previous studies, e.g. Nival et al 1975, Andreu and Duarte 1996, Mura et al 1996a, Mura et al 1996b, Buessler 1998), as suggested by the presence of fecal pellets. External inputs of nutrients and internal recycling were both important processes in terms of sustaining the local phytoplankton

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CAPÍTULO 4. Spatial-temporal patterns of nutrients and phytoplankton in the NW Mediterranean assemblage. The external inputs had marked seasonal dynamics, which included autumn-winter water column mixing, and seasonal rain regime with the associated intermittent river discharge. We have corroborated that maxima local precipitations, occurring in April and October and that amounted, respectively, 72.6 mm and 57 mm of monthly rain, corresponding to 27% and 21% of total annual precipitation (ECMWF reanalysis data), were followed by an immediate increase in nutrients and microphytoplankton abundance. We have also notice that the 3 to 4-fold increase in littoral demographic pressure occurring in summer in the studied area involves an equivalent increase in the sewage flux to the nearshore local water, which may be partially responsible for the progressive increase in ammonium and phosphate concentrations through summer that was not accompanied by nitrite+nitrate or silicate concentrations. We assume that an internal recycling of nutrients, especially silicon, favored diatoms to dominate after the March nutrient depletion in the local system, and to produce a secondary abundance peak in August. The effect of silicate, phosphate and nitrogen as primary potential limiting factor varied as a function of season, habitat and, less importantly, microhabitat. Both the study of nutrient ratios and the CCA showed the importance of silicon availability in explaining variability in the phytoplankton assemblage. The percentage in the variability of species data explained by silicate was about 1.8 times that explained by phosphate. Silicate concentration and the Si:N ratio were extremely low throughout the year. Therefore silicon appeared to be the primary potential limiting nutrient, followed by phosphate. This is not surprising for the nearshore waters of this densely populated coastal area, where the other nutrients, mainly N compounds, can arrive in excess from sewages, agricultural runoffs and local rivers. The silicate concentrations (<1.5 µM) found in our study are under the threshold at which diatom growth start being restrained (Nelson and Dortch 1996). We noticed a seasonal succession in diatom dominant species, involving also a shift in the geometry of the body shape of diatom species (Sommer 1998). The Si depletion, through the changes induced in diatom species abundance, usually favors dinoflagellate abundance (Conley et al 1993, Del Amo et al 1997, Nelson and Dortch 1996, Sommer 1994, Sommer 1998). After an early-spring bloom of “cylindrically-shaped” diatoms (Chaetoceros spp. and Detonula pumila), the exhaustion of nutrients - and the subsequent zooplankton grazing - led to a drop in cell abundance. During April-May,

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CAPÍTULO 4. Spatial-temporal patterns of nutrients and phytoplankton in the NW Mediterranean the nutrient increase associated to local rains and internal recycling (regenerated silicate from detritus and fecal pellet dissolution) favored proliferation of the “elongated- cylindrical-shaped” Proboscia alata. This phenomenon is similar to that explaining the abundance of Rhizosolenia sp. described in other coastal systems (Ragueneau et al 1994). In the beginning of summer, a subsequent depletion of silicate and the proliferation of plankton grazers (testified by the increase of fecal pellets) led to low abundance of diatoms and to a “summer phytoplankton assemblage” dominated by dinoflagellates. In August, nutrient enrichment, due to internal recycling, sewage, and possibly to some wind-driven resuspension in the weeks previous to our sampling, led to a minor abundance peak of “elongated-cylindrical-shaped” diatoms (Leptocylindrus minimus, L. danicus, and Guinardia striata), in agreement with previous reports by Leblanc et al 2003. In September-October, the “needle-shaped” Pseudo-nitzschia delicatissima, a low-salinity tolerant species, able to use regenerated nitrogen forms

(Thessen et al 2005, Fehling 2006), was the most abundant diatom species, and mainly at the low-salinity, surface samples. Beyond the dominant species, the specific composition of microphytoplankton assemblages and its relation with nutrient concentrations showed complex patterns, with marked between-habitat differences. Particularly, we found a peculiar diatom community in the boundary layer of rocky bottoms. Boundary layers are transition zones with peculiar characteristics in terms of local hydrodynamism and exchange of dissolved nutrients and particulate matter with the overlaying water column (Jørgensen 2001). The studied rocky bottoms show complex topography and uneven surfaces, also due to the tridimensional structure provided by local benthic biological communities, which may slow water flux, leading to local water stagnation and consequent depression of the transfer rates for particles, living cells and solutes (Jørgensen 2001). Due to local drag-reduced water flow and to the specific floatability of microalgae, different species (both those typically described as “benthic” and those regarded as “planktonic”) may become “trapped” in the boundary layer. Indeed, we found a “demersal” microalgal assemblage characterized by permanent, not-seasonally-induced features. As suggested for zooplankton (Emery 1968), the terms “planktonic” and “epibenthic” may represent extremes of a continuum. As for nutrients, in the two habitats (the rocky bottom and the water column) we observed the same seasonal trends and magnitude for both phosphate and nitrite+nitrate concentrations, whereas ammonium concentration was highest in the

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CAPÍTULO 4. Spatial-temporal patterns of nutrients and phytoplankton in the NW Mediterranean boundary layer of rocky bottoms, probably as a consequence of excretion by the important animal populations associated to these hard-bottom communities. On the other hand, the boundary layer of the rocky bottom was poorer in silicate than water-column habitat. The two habitats, are quite close to each other, so we assumed that they receive at least the same external input in silicate. We expected highest silicate concentration in the boundary layer, because most of silicon regeneration is thought to occur at the bottom-water interface (Ragueneau et al 1994). Furthermore, we expected the boundary layer of horizontal rocky bottoms to be richer in particulate silica compared to vertical rocky bottoms, because of gravitational accumulation of detritus. Contrary to expectations, the boundary layer of the two rocky- bottom microhabitats showed similar concentrations of particulate silica, moreover, silicate concentrations at the boundary layer were lower than those of the water-column habitat. Between-microhabitat differences were observed only during few months, possibly due to meteorological conditions which promoted either resuspension (e.g., in March) or settling (e.g., in August). The relation between BSi and silicate monthly values throughout the year indicated silicon shifting from its particulate form to its dissolved form and vice versa. Particularly, the concurrent BSi rise and the silicate drop in March and August corresponded respectively to the diatom early-spring and summer blooms and the uptake of silicate by diatoms to support growth. The fecal pellets and aggregates produced during late bloom are mainly constituted by silica (Dagg et al 2003). By April, BSi decreased and silicate increased, reflecting the dissolution of fecal pellets and aggregates. The lag between fecal pellets production and the subsequent rise in silicate was of approximately one-month: this lag is consistent with the fastest range of dissolution rate (18-37 days) found in experimental evidences (Schultes 2004, Moriceau et al 2007a, Moriceau et al 2007b), considered as the most suitable in our warm, shallow system. In May and June, silicon stock (BSi+silicate) showed a progressive decline due to a decrease in both BSi and silicate, which were probably exported from this nearshore system to outer coastal waters. Since at the habitat and microhabitat scale analyzed there are many biological, hydrodynamical and chemical factors which may be acting to modulate the observed patterns, we can only infer some possible causes and processes to explain our results. For instance, local benthic filter- feeding and plankton grazing invertebrates may promote particulate silica biodeposition and retention at the bottom-water interface (Chauvaud et al 2000). Furthermore, hard-

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CAPÍTULO 4. Spatial-temporal patterns of nutrients and phytoplankton in the NW Mediterranean bottom communities may seriously compete with planktonic organisms for some nutrients functioning like a “bentho-pelagic” filter; in particular, benthic siliceous organisms may reduce dissolved silicate seawater concentration by uptake. A study comparing the effects of phytoplankton and benthic diatoms on silicon fluxes (Sigmon and Cahoon 1997) showed that microphytobenthos was capable of limiting silicate available for phytoplankton during most of the year, and only in summer silicate flux coming from the dissolution of particulate matter exceeded microphytobenthic uptake, fertilizing the overlying water column. In addition to benthic diatoms, the studied rocky bottoms in our system are inhabited by many siliceous sponges, which, through silicate uptake, may contribute to silicate depletion. Local hydrodynamics may also be a relevant factor, as it changes as a function of wind direction and speed, waves and turbulence, affecting local concentrations of particulate matter and solutes and promoting particle accumulation, deposition and resuspension. To quantify the respective roles of these factors, additional experimental studies are needed, also assessing the spatial-temporal dynamics of benthic diatoms, benthic BSi stock, silicate fluxes and local hydrodynamics. In our study, the “demersal” microphytoplankton assemblage of the boundary layer of rocky bottoms resulted more silicon-limited than that in the adjacent nearshore water column. Many studies reports that nearshore waters of the Mediterranean and other highly-populated areas are experimenting a substantial and growing charge of terrestrial inputs, causing, among other things, disruption of natural nutrient ratios. This anthropogenic impact may lead to changes in planktonic communities and the derived trophic webs. Our results suggest that there is a delicate nutrient-phytoplankton coupling in nearshore waters, which may substantially differ even between adjacent microhabitats. Therefore, understanding disruption of nutrient balance in these nearshore systems may require more complicate, multi-scale assessments compared to those required for outer coastal waters.

4.5 Acknowledgements This study has been developed in collaboration with Manuel Maldonado, Raffaele Bernardello, and Zoila Velásquez (CEAB-CSIC). Thanks also to Roser Ventosa and Susana Pla for nutrient analyses, to Dr. Antonio Cruzado for access to the CTD and

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CAPÍTULO 4. Spatial-temporal patterns of nutrients and phytoplankton in the NW Mediterranean microscope and for helpful comments, and to Ferrán Crespo, Gustavo Carreras, Gilberto Cardoso and Irene for the help during fieldwork. This research benefited from funds provided by two grants (CTM2005-05366/MAR; BFU2008- 00227/BMC). A. Bucci was supported by a fellowship (FPU2005-5369) from the Spanish Government.

4.6 References Anderson MJ (2001), A new method for non-parametric multivariate analysis of variance, Austral Ecology 26: 32-46 Anderson MJ (2005), PERMANOVA: a FORTRAN computer program for permutational multivariate analysis of variance. Department of Statistics, University of Auckland, Auckland, New Zealand Barnett AM, Jahn A (1987), Pattern and persistence of a nearshore planktonic ecosystem off Southern California, Continental shelf research 7: 1-25 Biblioni MA, Cornet C, Ros JD (1982), Estudio bionómico del litoral de Blanes (Girona) entre Punta de Santa Anna y Cala Sant Francesc, Oecología aquática 6: 185-198 Brzesinski MA, Dickson ML, Nelson DM, Sambrotto R (2003), Ratios of Si, C and N uptake by microplankton in the Southern Ocean, Deep-Sea research II 50: 619- 633 Brzezinski MA (1985), The Si:C:N ratio of marine diatoms: interspecific variability and the effect of some environmental variables, Journal of Phycology 21: 347-357 Cebrián J, Duarte CM, Pascual J (1996), Marine climate on the Costa Brava (northwest Mediterranean) littoral, Publicaciones especiales del Instituto Español de Oceanografía 22: 9-22 Cloern JE, Grenz C, Vidergar-Lucas L (1995), An Empirical Model of the Phytoplankton Chrlorphyll: Carbon Ratio-the Conversion factor Between Productivity and Growth Rate, Limnology and Oceanography 40: 1313-1321 Conley DJ, Schelske L, Stoermer EF (1993), Modification of the biogeochemical cycle of silica with eutrophication, Marine Ecology Progress Series 101: 179-192 Dagg MJ, Urban-Rich J, Peterson JO (2003), The potential contribution of fecal pellets from large copepods to the flux of biogenic silica and particulate organic carbon in the Anctartic Polar Front region near 170ºW, Deep-Sea research II 50: 675- 691 Del Amo Y, Leblanc K, Tréguer P, Quéguiner B, Ménesguen A, Aminot A (1997), Impacts of high-nitrate freshwater inputs on macrotidal ecosystems. I. Seasonal evolution of nutrient limitation for the diatom-dominated phytoplankton of the Bay of Brest (France), Marine Ecology Progress Series 161: 213-224 Delgado M, Latasa M, Estrada M (1992), Variability in the size-fractionated distribution of the phytoplankton across the Catalan front of the northwestern Mediterranean, Journal of plankton research 14: 753-771 Estrada M (1979), Observaciones sobre la heterogeneidad del fitoplancton en una zona costera del mar Catalan, Investigacion Pesquera 43: 637-666 Flexas M (2003), Mesoscale variability of the Northern Current in the Gulf of Lions and the role of bottom topography. PhD Thesis, UPC-UB-CSIC. 1-153

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Font J, Salat J, Tintoré J (1988), Permanent features of the circulation in the Catalan Sea, Oceanologica Acta SP: 51-57 Grasshoff K, Ehrhardt M, Kremling K (1983), Methods of seawater analysis, Verlag Chemie, Weinheim p 1-419 Leblanc K, Queguiner B, Garcia N, Rimmelin P, Raimbault P (2003), Silicon cycle in the NW Mediterranean Sea: seasonal study of a coastal oligotrophic site, Oceanologica Acta 26: 339-355 Lucea A, Duarte CM, Agusti S, Sondergaard M (2003), Nutrient (N, P and Si) and carbon partitioning in the stratified NW Mediterranean, Journal of Sea Research 49: 157-170 Margalef R (1978), Life-forms of phytoplankton as survival alternatives in an unstable environment, Oceanologica Acta 1: 493-509 Masó M, Duarte CM (1989), The spatial and temporal structure of hydrographic and phytoplankton biomass heterogeneity along the Catalan coast (NW Mediterranean), Journal of Marine Research 47: 813-827 Menge BA, Daley BA, Wheeler P, Strub PT (1997), Rocky intertidal oceanography: an association between community structure and nearshore phytoplankton concentration, Limnology and Oceanography 42: 57-66 Mura MP, Agustí S, Cebrián J, Satta MP (1996), Seasonal variability of phytoplankton biomass and community composition in Blanes Bay (1992-1994), Publicaciones especiales del Instituto Español de Oceanografía 22: 23-29 Nelson DM, Dortch Q (1996), Silicic acid depletion and silicon limitation in the plume of the Mississippi River:evidence from kinetic studies in spring and summe, Marine Ecology Progress Series 136: 163-178 Ragueneau O, De Blas Varela E, Treguer P, Quéguiner B, Del Amo Y (1994), Phytoplankton dynamics in relation to the biogeochemical cycle of silicon in a coastal ecosystem of western Europe, Marine Ecology Progress Series 106: 157- 172 Sigmon DE, Cahoon LB (1997), Comparative effects of benthic microalgae and phytoplankton on dissolved silica fluxes, Aquatic microbial ecology 13: 275-284 Sommer U (1994), The impact of light intensity and daylength on silicate and nitrate competition among marine phytoplankton, Limnology and Oceanography 39: 1680-1688 Sommer U (1998), Silicate and the functional geometry of marine phytoplankton, Journal of plankton research 20: 1853-1859 Utermöhl H (1931), Neue wege in der quantitativen erfassung des planktons (mit besonderer berücksichtigung des ultraplanktons), Internationale Vereinigung fuer Theoretische und Angewandte Limnologie 5: 567-596 Velásquez Forero ZR (1997), Fitopláncton en el Mediterráneo Noroccidental. PhD Thesis. Universitat Politècnica de Catalunya. 1-329 Wieters EA, Kaplan DM, Navarrete SA, Sotomayor A, Largier J, Nielsen KJ, Véliz F (2003), Alongshore and temporal variability in chlorophyll a concentration in Chilean nearshore waters, Marine Ecology Progress Series 249: 93-105

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CAPÍTULO 5

CAPÍTULO 5. Benthic diatoms associated to maerl beds in the NE Atlantic

Estudio 3

The role of benthic diatoms associated to maerl beds in the silicon cycle of the Bay of Brest (NE Atlantic)

5.1 Introduction The surficial layer of the sea bottom of coastal systems is a zone of intense microbial and geochemical activity, as microphytobenthos (MPB) modulates the exchange of nutrients between sediments and water column (Sigmon and Cahoon 1997, Cibic et al 2007). The abundance and productivity of MPB is determined by the influence of the overlying water, location, season and bottom properties. Variations in biomass of MPB in adjacent but distinct environments may be as great as those over long geographic distances (Macintyre et al 1996). In many shallow ecosystems, the biomass of benthic microalgae often exceeds that of the phytoplankton in the overlying waters (Macintyre et al 1996, Webster et al 2002). Microphytobenthos is mainly constituted by diatoms (Macintyre et al 1996), thus in the present study we will indistinctly refer to MPB or to “benthic diatoms”. Diatoms need dissolved silicon to synthesize their frustules of biogenic silica (BSi) and play a key role in the silicon biogeochemical cycle (Nelson et al 1995, Ragueneau et al 2000, Tréguer et al 1995). Benthic diatoms contain and require significantly more silica per unit chlorophyll than planktonic forms do, and can be an important source of and sink for silica in shallow marine environments (Sigmon and Cahoon 1997). Furthermore, in shallow systems MPB can not only contribute to, but also control dissolved silica cycle, resulting in a control of planktonic productivity (Sigmon and Cahoon 1997). An understanding of the functioning of the microphytobenthic ecosystem compartment, its productivity and influence on the cycling of nutrients is crucial to get a more holistic comprehension of biogeochemical

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CAPÍTULO 5. Benthic diatoms associated to maerl beds in the NE Atlantic cycles, of food web structure and also of the responses of the ecosystem to anthropogenic inputs (Ni Longphuirt et al 2007). The Bay of Brest (NE Atlantic) is a well studied coastal system, and a biogeochemical model integrating benthic functional groups is being realized (LEMAR, Université de Bretagne Occidentale – CNRS; Laruelle et al 2009b). Previous studies of primary production and spatial variability of MPB in the Bay of Brest do exist (Ni Longphuirt et al 2007, Sagan and Thouzeau 1998), but they refer to sandy-muddy habitats, while more than one third of the bottom of the bay is covered by maerl bed. The term maerl refers to live, unattached coralline red algae (mainly Lithothamnion corallioides and Phymatholithon calcareum) and their debris, which can accumulate locally above muddy or sandy bottoms, and form thick (up to 10 m) and extensive beds (Figure 5.1a, Grall 2002, Grall and Hall-Spencer 2003). Maerl fragments, with their twig-like form, develop a complex architectural structure which allows water, oxygen and nutrients to circulate; moreover, it enhances the surface area in the euphotic zone, an ideal substratum for macroalgae and microphytes fixation and growth (Figure 5.1b, Hily 1989, Hily 1991). Maerl beds are widespread over large areas worldwide and are considered among the most extended benthic communities dominated by macroalgae (Foster 2001). They are one of the most diverse marine ecosystems found in Europe, and their conservation is of international interest (Hall-Spencer et al 2003, Wilson et al 2004). In this study, we investigated the role of benthic diatoms associated to maerl beds in the silicon cycle within the Bay of Brest. The objectives were to analyze the taxonomic composition of diatom assemblages, and to assess BSi stock in form of benthic diatoms associated with maerl. In order to investigate if community composition affects ecosystem processes, we also estimated silicon uptake and compared it to silicate needs of benthic diatoms in soft bottoms and pelagic diatoms.

5.2 Method

5.2.1 Study site The Bay of Brest (180 km2) is a macrotidal, shallow, semi-enclosed system on the NW coast of France (48º10’- 48º25’ N; 04º10’- 04º35’ W). It is connected to the Iroise Sea by a narrow, 1.8 km-wide opening, and two main rivers (Elorn and Aulne) bring fresh

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CAPÍTULO 5. Benthic diatoms associated to maerl beds in the NE Atlantic water and nutrients. However, the bay has physical and biological marine characteristics, salinity ranging from 31 to 35 (Grall 2002), water temperature from 9 to 17 ºC. Half of the total area is shallower than 5 m, and only 15% is deeper than 20 m. Maerl beds are widespread in the bay, they occupy more than one third of the bottom surface in subtidal areas and can be found to depths of 15 m (Grall 2002, Martin et al 2005). We carried out sampling campaigns (23 September and 22 October 2008; 22 June, 02 and 07 July 2009) on board of CNRS R/V “Hesione” to sample maerl thalli, with the associated benthic diatoms, and surface water samples. We compared three maerl banks within the Bay of Brest (i.e., Keraliou=M1, Rozegat=M2, and Penn ar Vir=M3; Figure 5.1b), located at the same depth (3 m). These maerl banks are characterized by mixed sediments: silt, sand and gravel are found in similar proportions, but they are vertically structured, with a more or less thick living maerl stratum laying above dead fragments mixed with sand-mud. Moreover, we considered a deeper sampling station in the southern part of the bay (Loumergat=M4), 8 m deep. In order to assess surface chlorophyll a we collected surface seawater samples by means of acid-cleaned plastic bottles. Subsamples (n=3) of 250 mL were filtered using GF/F filters (0.7 µM pore, 25 mm diameter) and immediately frozen at -80º C. Chlorophyll extraction was carried out by means of 90% acetone during 12 hours at 4 ºC. Chlorophyll concentration was measured fluorimetrically, also determining pheopigments after acidification with HCl (Lorenzen 1967). Average concentrations (±sd) were then calculated for each sampling point and season. To assess surface seawater nutrient concentration (silicate, nitrate, phosphate), water samples (n=3) were collected in acid-cleaned plastic bottles and refrigerated until the colorimetric analysis, performed by means of a BRAN+LUEBBE autoanalyzer. We calculated averages (±sd) for each sampling point and season. To study surface phytoplankton community, samples of 100 mL (n=1 per sampling point) were preserved with Lugol’s Iodine, analyzed using the Utermöhl settling technique (Utermöhl 1931), observed with an inverted microscope, generating a “species x abundance” matrix.

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Figure 5.1 a) Macroscopic aspect of a maerl bed (courtesy of J. Grall); b) scanning electron microscope photograph of the surface of a maerl thallus, with the associated diatoms; c) map of the Bay of Brest and the studied maerl banks (grey areas, redrawn from Grall 2002) and sampling points: M1=Keraliou bank, M2=Rozegat, M3=Pen Ar Vir; M4=Loumergat.

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5.2.2 Biogenic silica stock In order to assess the stock of BSi found in maerl beds in form of benthic diatom frustules, and to analyze its spatial variability within the Bay of Brest, SCUBA divers collected maerl thalli manually from the first centimeter of the bottom, at each maerl bank (M1, M2, M3, and M4; Figure 5.1b). The Keraliou M1 bank was sampled in both autumn 2008 and summer 2009, the other stations were sampled only in summer 2009. Samples were frozen at -20 ºC until their analysis. Before the analysis, samples of maerl thalli were weighted, freeze-dried, re-weighted, and crushed to obtain a fine, homogeneous powder. For each maerl bank, 10 samples of maerl thalli (1-9 g each) were used, and from each crushed sample, we analyzed one subsample of about 30 mg. To determine the BSi amount per maerl gram, pulverized samples were subjected to a wet-alkaline digestion, following an adapted method based on DeMaster’s method of analysis of BSi from marine sediments (DeMaster 1981). Approximately 30 mg of maerl powder were placed in a 50 ml polypropylene centrifuge tube, 30 mL of alkaline solution were added to samples, and the tube was placed in a 85ºC water bath, as previously tested (Kerembellec 2005). At fixed intervals of time (i.e., after 30’, 1 hour, then at each hour until hour 8), 0.5 mL was removed from the extraction and analyzed for dissolved silica using a BRAN+LUEBBE autoanalyzer. The amount percent silica extracted is plotted versus time, and the extrapolated intercept (at time zero) equals the biogenic silica content of the sample. The analytical technique relies on the difference between the rapid dissolution of biogenic silica and slower release of silica from coexisting clay minerals (DeMaster 1981). To obtain a complete opal recovery and a correction for the non-biogenic silica in reasonable reaction times, we tested and compared two alkaline solutions, 5% Na2CO3 and 0.2 M NaOH (Muller and Schneider 1993). Since from these preliminary tests we obtained the same final result in terms of BSi determination, we chose the NaOH solution for working slightly faster, indeed digestion was completed after 3 hours, while with Na2CO3 it took 6 hours. Once quantified the BSi per maerl gram, knowing the maerl weight per bottom surface area (2 kg m-2, Potin et al 1990), we extrapolated the result to obtain an estimate of BSi m-2. Differences in abundance of benthic BSi as a function of maerl bank were examined using a one-way ANOVA on square-root transformed BSi m-2 data of summer samples. “A posteriori” pairwise SNK tests were used to identify groups responsible for significant differences in the ANOVA. Differences in BSi abundance as a function of

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CAPÍTULO 5. Benthic diatoms associated to maerl beds in the NE Atlantic season within the same maerl bank were also investigated using a one-way ANOVA on ln-transformed BSi m-2 data of M1 samples. In parallel to maerl sampling, we collected surface seawater samples by means of acid-cleaned plastic bottles, to quantify planktonic BSi. Samples (n=3) from M1, M2 and M3 were kept in dark and refrigerated, until filtration with PC filters (0.6 µM pore, 4.7 mm diameter), which took place 2-4 hours after collection. Filters were subsequently folded and dried at 60 ºC, then kept in plastic Petri dishes until their analysis, which consisted in a double wet-alkaline digestion (Ragueneau et al 2005). Since the percentage of silicon coming from mineral interference and obtained from the analyses of benthic BSi was definitely low, we omitted the Al determination proposed by Ragueneau and co-authors’ method, and used the measured percentage as correction factor instead. Differences in abundance of planktonic BSi as a function of maerl bank were examined using a one-way ANOVA on raw seawater BSi L-1 data. “A posteriori” pairwise SNK tests were used to identify groups responsible for significant differences in the ANOVA. Differences in BSi concentration as a function of season within M1 maerl bank were also investigated using a one-way ANOVA on raw seawater BSi L-1 data.

5.2.3 Benthic diatom community and content of BSi per cell To describe and compare benthic diatom communities from the different maerl banks, samples of maerl thalli from each maerl bank (M1, M2, M3, and M4) obtained as previously described, were carefully brushed with a toothbrush, and the material, resuspended in pre-filtered seawater, was preserved with Lugol’s solution. Samples (n=1 in autumn, n=5 per bank in summer) were then observed with an inverted microscope using the Utermöhl settling technique (Utermöhl 1931), and a “species x abundance (%)” matrix was obtained. Moreover, some intact Lugol-preserved maerl thalli were observed with a scanning electron microscope. To examine MPB community of the studied maerl banks, we determined species richness (S), Shannon diversity index (H’), and Pielou’s evenness (J’). To examine global patterns in inter-sample similarities, we run a Non-metric Multidimensional Scaling Analysis (nMDS) based on abundance data and an inter-sample Bray-Curtis dissimilarity matrix. Sample scores were plotted in a bidimensional space. In order to

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CAPÍTULO 5. Benthic diatoms associated to maerl beds in the NE Atlantic assess differences in specific abundances as a function of maerl bank, we performed a one-factor Permutational Analysis of Variance (PERMANOVA) with unrestricted permutation of raw data (Anderson 2001), based on a Bray-Curtis dissimilarity matrix of specific abundance and using 999 permutations. The direct estimation of cell number m-2 bottom is difficult due to the presence of macroalgae debris, organic matter, sediment etc. in the sample, which may mask cells when samples are observed with the inverted microscope. Moreover, when brushing maerl thalli, some cells may remain attached to them, hidden in folds of the thalli. This may lead to underestimation of cell abundance. In order to analyze the abundance per square meter bottom of benthic diatoms associated to maerl, and to estimate the amount of BSi per cell, samples of maerl thalli, obtained as previously described, were brushed with a toothbrush. The resulting material was resuspended in pre-filtered seawater. The suspension was homogenized by gently mixing, without harming cells, and subdivided in parts of known volumes. Three parts were filtered and analyzed to quantify its content in BSi, as described for planktonic samples. One part was preserved with Lugol’s Iodine and analyzed using the Utermöhl settling technique (Utermöhl 1931) to count cell number. We also counted empty frustules and siliceous sponge spicules. Knowing cell number of the sample and mean BSi content per sample, we intended to estimate the amount of BSi per cell. In order to estimate cell number m-2, we divided the amount of BSi m-2, obtained from the digestion of whole maerl thalli, for the calculated amount of BSi cell-1. It is noteworthy that the “BSi cell-1” obtained here is useful in our calculations, but it must not be considered as the true measurement of the silica contained in living diatoms, since it comprises also empty frustules and siliceous sponge spicules.

5.2.4 Silicic acid uptake

In order to measure silicon uptake by a natural assemblage of diatoms associated to maerl branches, we incubated maerl thalli in presence of the radioisotope of silicon, 32Si. Uptake experiments took place in both autumn 2008 (M1 bank) and summer 2009 (M3 bank). Maerl branches (3 replicates per season), sampled as explained before, were placed in polycarbonate incubation bottles with pre-filtered seawater of known silicate concentration. Autumn maerl samples were incubated in 125 mL of pre-filtered

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CAPÍTULO 5. Benthic diatoms associated to maerl beds in the NE Atlantic seawater (silicate concentration=14.70 µM), to which 750 Becquerels of 32Si labeled-

Si(OH)4 (in Na2SiO3 solution, Los Alamos National Laboratory, New Mexico, USA), was added. Summer maerl samples were placed in 60 mL seawater (silicate concentration=0.76 µM), to which 750 Becquerels of 32Si were added. Increase in silicate concentrations due to isotope addition was negligible (<0.02 µmol at the most). After mixing, 1 mL of the incubation solution was withdrawn and placed in a plastic scintillation vial, to determine initial activity by means of a scintillation counter (Leynaert et al 1996). Incubation lasted 24 hours, in the natural light and temperature conditions as found in situ, considering the light extinction coefficient (Martin et al 2005, Grall unpubl.). As a blank, we used maerl fragments previously frozen at -80 °C and defrozen, to kill the associated diatoms. After the 24-hour incubation, maerl thalli were taken off the water, dried at 60 ºC during three days, and crushed to obtain a powder. To verify the homogeneity of the samples, they were divided into three weighted parts and their activity measured separately. A solution of 10 % HF (1 ml) was added to dissolve the BSi in the samples and homogenize the radioactive signal. Ten mL of the scintillation cocktail Ultima Gold XR was then added. Measure of the radioactivity coming from the silicon uptaken by diatoms were realized using a scintillation counter (Leynaert et al 1996). The silicate uptake rate was determined for each sample and normalized to the BSi concentration present at the beginning of the incubation, to calculate the specific uptake rate (V), as explained by Leynaert and co- authors (Leynaert et al 1996).

5.3 Results 5.3.1 Water column Surface seawater chlorophyll concentration ranged between 1.39 µg L-1 at Keraliou bank in autumn and 2.44 µg L-1 at Rozegat bank in summer (Table 5.1). Surface nutrient concentrations showed strong seasonal differences in the Bay of Brest (present study and data from Somlit-Brest, Coastal time-series station). Silicic acid ranged from 14.7 in autumn decreasing to almost depletion in spring (Table 5.1). In summer samples, nitrate concentration was low and phosphate was not detectable. We do not dispose of autumn data for phosphate.

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The analysis of planktonic BSi associated to maerl habitat in the Bay of Brest ranged between 1.35 µM at Keraliou bank, in autumn, and 2.49 µM at Rozegat bank, in summer. Integrating the planktonic BSi concentration over a depth of 3 m, we obtain values ranging from 4.05 to 7.46 mmol BSi m-2 (Figure 5.2a). The ANOVA confirmed significant between-bank differences in planktonic BSi (df=2; F=6.82; P=0.028). The “a posteriori” pairwise SNK test highlighted differences between M1 and M2. We also detected significant between-season differences in planktonic BSi, with lower amounts of silica in autumn compared to summer (df=1; F=14.33; P=0.019; Figure 5.2a). Phytoplankton abundance was minimum in autumn and maximum at Pen ar Vir bank in summer, when we observed more than 21,000 cells per 100 mL, mainly due to the small Chaetoceros gracilis proliferation. Phytoplanktonic community was dominated by diatoms, which in summer reached up to 97% in cell abundance. We identified 66 diatom taxa, 31 dinoflagellate, and 1 silicoflagellate species (Supplementary Table 3 ANEXO 1). Dinoflagellates were especially abundant in Pen Ar Vir summer sample. We also observed 3 chlorophyt species in the autumn sample. In autumn, the most abundant diatom species were, besides C. gracilis, Guinardia delicatula and Leptocylindrus danicus. In summer, Pseudo-nitzschia spp. and Thalassionema nitzschioides were also abundant species. Numerous rare species were present in similarly low abundance.

Table 5.1. Surface seawater chlorophyll and nutrient concentration. M1a=Keraliou bank, autumn 2008; M1=Keraliou bank, summer 2009; M2=Rozegat, summer 2009; M3=Pen Ar Vir; M4=Loumergat, summer 2009. n.d.=not detectable.

Date Maerl Chl a Silicate Nitrate Phosphate bank µg L-1 (±sd) µmol L-1 (±0.04) µmol L-1 (±0.07) µmol L-1 (±0.02) 22/10 M1a 1.39 (±0.53) 14.70 4.1 - 22/06 M1 1.66 (±0.19) 0.66 0.33 0.05 (±0.02) 02/07 M2 2.44 (±0.12) 1.34 1.5 n.d. 07/07 M3, M4 1.91 (±0.03) 0.76 0.1 n.d.

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Figure 5.2. Biogenic silica stock associated to different banks of the maerl habitat (M1a=Keraliou bank, autumn 2008; M1=Keraliou bank, summer 2009; M2=Rozegat, summer 2009; M3=Pen Ar Vir; M4=Loumergat, summer 2009). a) Planktonic Bsi, b) benthic Bsi (note the different scale). Error bars are standard deviations. Letters at the upper part of graphs refer to “a posteriori” SNK test following the one-way ANOVA as a function of maerl bank. Groups of underlined letters indicate non-significant differences (P>0.05) between pairs of means.

5.3.2 Biogenic silica stock associated to maerl The analysis of benthic BSi stock associated to maerl habitat in the Bay of Brest revealed that the amount of biogenic silica varied between 5.51 mmol BSi m-2 in autumn and 239.5 mmol BSi m-2 in summer (Figure 5.2b). It is noteworthy that the quantified silica comes from an alkaline digestion which cannot distinguish between living diatoms, frustules and siliceous sponge spicules. The average ratio between empty frustule number and living diatom number was 0.24 (±0.10), whereas the average

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CAPÍTULO 5. Benthic diatoms associated to maerl beds in the NE Atlantic ratio between spicule number and living diatoms was 0.18 (±0.32), with a maximum value of 1.27 in a M2 sample. Living diatoms were, on average, 72.03% (±12.08) in number of the sum of all siliceous elements. Therefore, the BSi attributable to living diatoms may only be estimated, since the BSi content of spicules and dead diatoms varies depending at least on the species, size and on the degree of decomposition. The ANOVA confirmed significant between-bank differences in benthic BSi stock (df=3; F=11.42; P<0.001). M1 and M2 banks showed similar BSi amounts, which were lower compared with M3 and M4 banks, whose BSi was similarly high, as confirmed by the “a posteriori” pairwise SNK tests (Figure 5.2b). Moreover, we detected significant between-season differences in BSi stock, with lower amounts of silica in autumn compared to summer (df=1; F=153.13; P<0.001; Figure 5.2b). Interestingly, no between-depth differences were detected. The average percentage of correction for lithogenic silica was 2.1 in M1a, 7.9 in M1s, 12.1 in M2, 14.6 in M3 and 16.0 in M4.

5.3.3 Benthic diatom community Throughout the study (autumn 2008 and summer 2009), we collected a total of 21 samples for MPB community description, and we identified 41,950 diatom cells, belonging to 70 taxa (Supplementary Table 4 ANEXO 1, Photos 33-42 ANEXO 2). Furthermore, we observed 12 species which are typically planktonic (e.g., Chaetoceros spp.), but we discarded them from the analyses, because they were probably present in seawater over maerl, but they are not part of the microphytobenthic communities. On the other hand, we did take into account other species that are considered as either planktonic and epibenthic, like Pseudo-nitzschia species. The most abundant MPB species were the quite large Cocconeis scutellum (up to 42% of total cells in M2 bank), followed by small Naviculacea species, Amphora spp., and Bacillaria paradoxa; other abundant species were Pseudo-nitzschia seriata and Navicula ramosissima in autumn, and Pinnularia viridis in summer. Keraliou-M1 and Rozegat-M2 maerl banks showed similarly higher MPB species richness (S), diversity (H’), and equitability (J’) compared to M3 and M4 banks (Table 5.2). The M1-autumn sample showed lower species richness but higher diversity and equitability compared to samples from the same bank in summer.

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Table 5.2. Species richness (S), Shannon diversity index (H’), and Pielou’s evenness (J’) for each bank and season (n=replicates; M1a=Keraliou bank, autumn 2008; M1=Keraliou bank, summer 2009; M2=Rozegat, summer 2009; M3=Pen Ar Vir; M4=Loumergat, summer 2009).

Maerl bank n S H J' M1a 1 40 2,80 0,76 M1 5 59 2,49 0,61 M2 5 57 2,10 0,52 M3 5 44 1,88 0,50 M4 5 42 1,93 0,52

The Multidimensional Scaling Analysis (nMDS) revealed a separation between samples from different maerl banks along the first axis, with M1 (of both, autumn and summer) and M2 samples separated from M4 and M3 (Figure 5.3). The second axis was more correlated with intrasample variability, and also divided M1-autum sample from all others. The PERMANOVA results confirmed the between-maerl bank differences in specific composition and relative abundance of MPB communities (df=3; Pseudo-F=16.0; P=0.001). It is noteworthy that no significant between-depth differences were detected in community composition. Among the species which seemed most responsible for these differences there were Cocconeis scutellum and Amphora spp., more abundant in the northern half of the Bay (M1 and M2), and small Navicula species, which, conversely, abounded in the southern half (M3 and M4). The amount of “BSi cell-1” varied between 197.8 and 395.7 pmol cell-1 (Table 5.3). This result is not surprisingly high since, as commented before, it comes from the alkaline digestion of living diatoms, frustules and siliceous sponge spicules, which were quite abundant. The calculated averages of living diatom abundances range between 27.8 × 106 cells m-2 of autumn-M1 sample and 870.7×106 cells m-2 of M4 sample (Table 5.3).

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Figure 5.3. Non-metric Multidimensional Scaling of samples from different maerl banks as a function of specific abundance of benthic diatoms. M1a=Keraliou bank, autumn 2008; M1=Keraliou bank, summer 2009; M2=Rozegat, summer 2009; M3=Pen Ar Vir; M4=Loumergat, summer 2009).

Table 5.3. Mean sample “BSi cell-1”, BSi m-2 and the calculated cell number m-2 per maerl bank. M1a=Keraliou bank, autumn 2008; M1=Keraliou bank, summer 2009; M2=Rozegat, summer 2009; M3=Pen Ar Vir; M4=Loumergat, summer 2009

Maerl bank BSi cell-1 BSi m-2 Cell n m-2 pmol cell-1 mmol m-2 (n×106) M1a 197.8 5.51 27.8 M1 395.7 65.38 165.2 M2 392.6 52.21 133.0 M3 300.1 226.90 756.1 M4 275.0 239.48 870.7

5.3.4 Silicic acid uptake The production rate of BSi by benthic diatoms associated to maerl banks was 156.9 (± 57.2) µmol Si m-2 day-1 in autumn, when seawater silicate concentration was 14.70 µM (Table 5.1), whereas it was only 3.4 (±1.4) µmol Si m-2 day-1 in summer, with a silicate concentration of 0.76 µM (Table 5.1). The specific silicon uptake rates (V) calculated from the measured BSi stock were 0.029 (±0.01) day-1 in autumn and 1.48×10-5 (±6.02×10-6) in summer. If we

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CAPÍTULO 5. Benthic diatoms associated to maerl beds in the NE Atlantic consider only the 72.03% of the BSi as attributable to living diatoms (taking into account that this is an estimation based on number ratios between living diatoms and dead diatoms+sponge spicules), the previous V estimations change to 0.039 (±0.01) day-1 and 2.27×10-5 (±8.36×10-6) day-1, for autumn and summer, respectively.

5.4 Discussion Most of the diatom species observed throughout the study were those commonly found in other benthic habitats (Cahoon 1999, Cibic et al 2007). We found epilithic, epipsammic, epipelic and epiphytic diatom species (Supplementary Table 4 ANEXO 1, Round et al 1990). Our results showed that the benthic diatoms associated to maerl banks form diverse and complex communities, due to the microscale heterogeneity of maerl habitat, suitable for the development of a diverse microflora, as it was already described for the fauna (Grall 2002). Moreover, we detected mesoscale (few kilometers) heterogeneity in MPB community composition, abundance, and diversity, the banks located in the northern half of the bay differing from those in the southern half. One of the factors which may induce the observed pattern is the variability of sedimentary fractions found in each bank. Even though the studied banks are characterized by 30- 50% gravel, the proportion of fine particles may vary of a two-factor between the banks (Grall 2002). Both Cocconeis scutellum and Amphora spp., which especially abounded in the northern half of the Bay, are described as both epiphytic and epilithic species, Cocconeis attaching to substratum. On the other hand, the small Navicula species, observed in high abundance in the southern half of the Bay, are epipelics, freely living on fine sediment or mud. This may suggest that the sampling points of the maerl banks located in the southern half of the Bay had a higher amount of fine sediment and mud than those of the other banks. Other factors may concur in originating the observed between-bank differences in MPB communities, and, in the absence of further data, we can only infer possible causes such as, e.g., different abundance of macroalgae, turbidity and other physical factors or even pollution. Indeed, two studies indicated Keraliou M1 bank as the most disturbed by pollution from the Elorn river and the city of Brest (Grall 2002, Grall and Glémarec 1997). The spatial variability in diatom abundance and specific composition was not reflected by the planktonic community, probably due to the mixing effect of waves and

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CAPÍTULO 5. Benthic diatoms associated to maerl beds in the NE Atlantic tidal currents. These mixing forces may be one of the factors maintaining the high number of rare species in the phytoplankton (Margalef 1978), less numerous in the MPB. Surprisingly, community composition, cell abundance and BSi stock were similar in the southern part of the bay at both 3 and 8 m depth, despite an elevated light extinction coefficient of 0.38 m-1, as previously estimated in spring (Martin et al 2005). This contrast with the data of decreasing biomass with increasing depth due to light limitation found in a microtidal system (Sundbäck et al 2004). However, the Bay of Brest is a macrotidal system, with maximum tidal amplitude of 8 m and tide periodicity of 12 h 15 min, therefore the analyzed depths may be too close to each other to develop different communities. Our results of chlorophyll a and nutrient concentration fell in the range of seasonal variability reported for the Bay of Brest (SOMLIT data, http://www.univ- brest.fr/IUEM/observation/observation_iroise.htm; Beucher et al 2004). The high surface-water silicate concentration registered in autumn was probably due to freshwater discharge, since the sampling point is located at the mouth of the Elorn river.

Nitrate concentrations, however, were not comparably high. Our results of planktonic BSi are comparable with those found in literature for the same coastal area (Beucher et al 2004, Del Amo et al 1997, Foullaron et al 2007, Ragueneau et al 1994). Few attempts have been made to measure benthic diatom BSi stocks, and especially of subtidal diatoms. Sigmon and Cahoon (Sigmon and Cahoon 1997), in a study on subtidal, soft-bottom benthic diatoms, found a mean annual biomass of 64.6 mg chl a m-2, and a mean silicate:chl a weight ratio of 14.3, or, in other words, a silica amount of 15.38 mmol BSi m-2. This value falls in the range of our autumn benthic BSi stock results. Another study, developed throughout one year in a shallow (5-10 m depth) subtidal mudflat in a bay in the Pacific, found that benthic BSi amounts ranged between 139 to 233 g m-2, apparently with spatial, season-related differences (Srithongouthai et al 2001), or 2.31-3.88 mol m-2, which means more than 16 times our highest value. However, since from the cited study the amount of chl a m-2 was similar to that found by Sigmon and Cahoon, we think that the biomass of living benthic diatoms in the Pacific bay of the cited study is comparable to that we found in the Bay of Brest, and that the high amounts of BSi measured by the authors came from detritus. Other studies about MPB production exist, but they generally do not include BSi measurements. If we apply the same silicate:chl a weight ratio found by Sigmon and Cahoon to calculate the

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BSi stock in soft-bottom habitat of the Bay of Brest from the measured chlorophyll a biomass (Ni Longphuirt 2006), we obtain a BSi amount ranging from 1.79 mmol BSi m-2 in winter and 3.14 mmol BSi m-2 in spring. Another study by the same author found an amount of chl a that, transformed to silicate amount, gives 1.10-1.29 mmol BSi m-2 (winter and late summer, respectively) in mud habitat and 0.74-0.88 mmol BSi m-2 in fine sand habitat (Ni Longphuirt 2006). These soft-bottom habitat values are much lower compared to our summer data of BSi stock, even considering the BSi due to living diatoms only. These results show that in maerl beds the MPB biomass, and though the BSi stock, may reach up to 70 times that attained in soft bottom habitat in the same area. The BSi stock of benthic diatoms associated to the studied maerl banks resulted almost equivalent to that of the plankton contained in the 3 m-deep overlying water-column in autumn. However, in summer, benthic BSi amount was 7-34 times higher than planktonic BSi, depending on the maerl bank considered. These results are not surprising, since the geometry of maerl fragments and the associated macroalgae, joint with low percentage of fine particles (Cahoon et al 1999), and the good water circulation within the sediment, offer favorable conditions to MPB development. However, this is the first study quantifying the benthic diatom biomass and BSi stock associated to maerl habitat. We detected that surface-water silicate concentration and benthic biogenic silica amount (or cell abundance) were inversely related, and their values differed of a 10- factor between autumn and summer. Our results of BSi production rate of benthic diatom communities associated to maerl habitat of the Bay of Brest in autumn (156.9 µmol Si m-2 day-1) fell within the range of the lowest values found for phytoplankton production in Euopean coastal areas or in some oceanic regions (0.2 mmol Si m-2 day-1, Ragueneau et al 2000). However, our summer results (3.4 µmol Si m-2 day-1) were at least two orders of magnitude smaller. Beucher and co-authors (Beucher et al 2004), in a study on phytoplankton of the Bay of Brest, estimated a silica production rate of 0.06 µmol Si l-1 day-1 in autumn and 0.77 µmol Si l-1 day-1 in summer, which, extrapolated to a 3m-deep water-column, correspond to 0.18 mmol Si m-2 day-1, thus almost equaling our autumn result, and 2.31 mmol Si m-2 day-1, three orders of magnitude higher than our summer data. Our autumn specific uptake rate of 0.039 day-1 of benthic diatom community is comparable (although lower) to that found in the cited study (0.09 day-1; Beucher et al 2004). In contrast, our summer V is four orders of magnitude smaller. As mentioned before, we can only estimate the BSi attributable to living diatoms, since the

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CAPÍTULO 5. Benthic diatoms associated to maerl beds in the NE Atlantic analytical methods cannot distinguish it from that coming from detritus. This may partially result in a biased V. The ratio of number of living diatoms:detrital elements, thus the ratio of BSi from living diatoms:BSi from detritus, may be overestimated (leading to an underestimation of the calculated V), due to the settled elements which cannot be correctly quantified, like fecal pellets or fine-broken frustules. This overestimation of the BSi associated to living diatoms may be stronger when studying benthic samples than when analyzing the water column, thus affecting the V calculations. Nevertheless, our low or even extremely low specific uptake rate of silicon by benthic diatoms compared to the cited planktonic results and to the mean for pelagic diatom assemblages from different environments (i.e., 0.026 (±0.60) h-1, Claquin et al 2006) are only partially attributable to the higher amount of benthic BSi compared to planktonic one. In a recent study about silicate uptake by a natural community of soft- bottom benthic diatoms in the Bay of Brest (Leynaert et al 2009), the authors found that, in absence of other nutrient limitation, at low silicate concentrations the uptake -1 -1 kinetic fitted the Michaelis-Menten function, with Ks=54 µmol L and Vmax=0.096 h . Using these constants and our silicate concentrations (14.7 µmol L-1 and 0.76 µmol L-1 for autumn and summer, respectively) we calculated the expected V, which resulted as being 0.021 h-1 in autumn and 0.0013 h-1 in summer. By dividing our 24 h measured V by 24 h day-1, we obtained a rough estimate of the production per hour, which resulted in 0.0016 h-1 and 9.46×10-7 h-1. Our experimental V results are 1 to 4 orders of magnitude lower than the theoretical V with the observed silicate concentrations. Therefore, some additional limiting factors or processes within the analyzed system may occur preventing benthic diatoms from growing in the studied seasons. Our summer data of surface-water nutrient concentrations appeared under the threshold that potentially limit planktonic diatom growth, which, for the conditions prevailing in the

Bay of Brest, was estimated as being 0.2, 2.0 and 2.0 µM, for phosphate, silicic acid and DIN, respectively (Del Amo et al 1997). Despite we only have nitrate concentrations, and not DIN, the high silicate concentration and low nitrate:silicate ratio in autumn make it impossible to discard nitrogen as the main limiting nutrient in that season, which would agree with Del Amo and co-authors (Del Amo et al 1997). The very low nitrogen, phosphate, and silicate concentrations in summer, and the theoretical calculated silicate V for MPB, indicate a possible co-limitation of the three nutrients. In the study of Del Amo and co-authors, nitrogen was not limiting in July for phytoplankton, suggesting, e.g., different nitrogen demand by MPB or differences in the

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CAPÍTULO 5. Benthic diatoms associated to maerl beds in the NE Atlantic environmental characteristics like nutrient ratio at the sediment-water interface. Additional studies should be carried out to elucidate the effects of nutrient concentrations on MPB, through uptake kinetics and studies on seasonality of abundance and production, as well as studies on nutrient fluxes at the sediment-water interface. In a study about community metabolism in maerl beds (Martin et al 2007), the authors found that silicate was taken up in winter and spring and released in summer and autumn, in agreement with our silicon uptake data. The higher summer benthic BSi amount compared to autumn values may indicate that the growing season of MPB within the system starts before summer, and leads to the accumulation of silicified cells observed in July. Accordingly, Ni longphuirt (Ni Longphuirt 2006), in a study on MPB on soft sediment in the Bay of Brest, found a maximum of benthic chl a concentration in spring. In a study developed in North Carolina, the highest subtidal MPB abundance was recorded between late summer and mid-winter (Sigmon and Cahoon 1997). However, in that system, minimal currents or sediment disturbance occurred. In our system, waves and storms are frequent in autumn and winter, and have strongest effects on the eastern part of the Bay; moreover, tidal currents are especially strong in the Elorn River estuary, altering the substrata and enhancing turbidity (Hily et al 1992). These physical disturbances, as well as variable solar radiation, may, together with nutrient limitation, act against diatom accumulation, especially in autumn, and may also be partially responsible for the spatial variability within the Bay. Our results remark the key role of benthic diatoms in the silicon cycle of the studied coastal system, which is comparable to that of phytoplankton. Our data suggest that several factors, among with a combination of limiting nutrients, may limit the MPB production in the Bay of Brest during summer and autumn. This is the first study quantifying the BSi stock of benthic diatoms associated to maerl habitat and highlights the importance of considering different habitat and spatial scale variability when realizing models of the cycle of silicon.

5.5 Acknowledgements This study has been developed in collaboration with Aude Leynaert, Jacques Grall, and Olivier Ragueneau (LEMAR, IUEM-CNRS). Thanks to Robert Marc, Erwan Amice and Céline Poulain for helping with sampling; to Manon Le Goff, Emilie Grossteffan,

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Annik Masson for help with nutrient analyses; to Roser Ventosa for realizing part of the silicate analyses and for useful advices; to Mélanie Raymonet, Jérémy Querné, Marie Czamanski and Rudolph Corvaisier for constructive comments on the methods and the study; to Gérard Sinquin (Plataforme d’Imagerie et de Mesures en Microscopie, Université de Bretagne Occidentale) for the SEM photographs; to Dr. Beatriz Beker for access to the microscope, bibliography and taxonomic help; to Antonio Cruzado for access to the microscope at the CEAB; to Manuel Maldonado for helpful comments on the manuscript. This research benefited from funds provided by the LEMAR group under the direction of Dr. O. Raguenau and from a grant from the Spanish Government. A. Bucci was supported by a fellowship (FPU2005-5369) and by two short-stay FPU fellowships from the Spanish Government.

5.6 References Anderson MJ (2001), A new method for non-parametric multivariate analysis of variance, Austral Ecology 26: 32-46 Beucher C, Tréguer P, Corvaisier R, Hapette AM, Elskens M (2004), Production and dissolution of biosilica, and changing microphytoplancton dominance in the Bay of Brest (France), Marine Ecology Progress Series, 267: 57-69 Cahoon LB (1999), The role of benthic microalgae in neritic ecosystems, in Oceanography and Marine Biology: an annual review 37, ed. Ansell AD, Gibson RN, and Barnes M, Taylor & Francis. 47-86 Cahoon LB, Nearhoof JE, Tilton CL (1999), Sediment grain size effect on benthic microalgal biomass in shallow aquatic ecosystems, Estuaries, 22: 735-741 Claquin P, Leynaert A, Sferratore A, Garnier J, Ragueneau O (2006), Physiological ecology of diatoms along the land–sea continuum, in Land–ocean nutrient fluxes: Silica cycle, ed. Ittekot V, Humborg C and Garnier J, SCOPE book series 66, Island Press, Washington DC, USA, 18-24 Cibic T, Blasutto O, Falconi C, Fonda Umani S (2007), Microphytobenthic biomass, species composition and nutrient availability in sublittoral sediments of the Gulf of Trieste (northern Adriatic Sea), Estuarine, Coastal and Shelf Science, 75: 50- 62 Del Amo Y, Leblanc K, Tréguer P, Quéguiner B, Ménesguen A, Aminot A (1997), Impacts of high-nitrate freshwater inputs on macrotidal ecosystems. I. Seasonal evolution of nutrient limitation for the diatom-dominated phytoplankton of the Bay of Brest (France), Marine Ecology Progress Series, 161: 213-224 DeMaster DJ (1981), The supply and accumulation of silica in the marine environment, Geochimica et Cosmochimica Acta, 45: 1715-1732 Foster MS (2001), Rhodoliths: between rocks and soft places. Journal of Phycology, 37: 659-667 Foullaron P, Claquin P, L'Helguen S, Huonnic P, Martin-Jézéquel V, Masson A, Ni Longphuirt,S., Pondaven P, Thouzeau G, Leynaert A (2007), Response of a

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phytoplankton community to increased nutrient inputs: A mesocosm experiment in the Bay of Brest (France), Journal of Experimental Marine Biology and Ecology, 351: 188-198 Grall J (2002), Biodiversité specifique et fonctionelle du maerl: réponse à la variabilité de l'environnement côtier. PhD Thesis. Université de Bretagne Occidentale. 1- 302 Grall J, Glémarec M (1997), Using biotic indices to estimate macrobenthic community perturbations in the Bay of Brest, Estuarine, Coastal and Shelf Science, 44: 43- 53 Grall J, Hall-Spencer JM (2003), Problems facing maerl conservation in Brittany. Aquatic Conservation: Marine and Freshwater Ecosystems, 31: 55-64 Hall-Spencer JM, Grall J, Moore PG, Atkinson RJA (2003), Bivalve fishing and maerl- bed conservation in France and the UK - retrospect and prospect, Aquatic Conservation: Marine and Freshwater Ecosystems, 13: 33-41 Hily C (1989), La megafaune benthique des fons meubles de la Rade de Brest: pre- échantillonnage par video sousmarine. Cahiers de Biologie Marine, 30: 433-454 Hily C (1991), Is the activity of benthic suspension feeders a factor controlling water quality in the Bay of Brest? Marine Ecology Progress Series, 69: 179-188 Hily C, Potin P, Floc'h JY (1992), Structure of subtidal algal assemblages on softbottom sediments: fauna/flora interactions and role of disburbances in the Bay of Brest, France, Marine Ecology Progress Series, 85: 115-130 Kerembellec P (2005), Spatial biomass of epiphytic microphytobenthos on the calcareous algae maerl in the Bay of Brest, France. Rapport de stage M2, Université de Bretagne Occidentale, Brest. 1-45 Laruelle GG, Roubeix V, Sferratore A, Brodherr B, Ciuffa D, Conley DJ, Dürr HH, Garnier J, Lancelot C, Le Thi Phuong Q, Meunier J-D, Meybeck M, Michalopoulos P, Moriceau B, Nı Longphuirt S, Loucaides S, Papush L, Presti M, Ragueneau O, Regnier P, Saccone L, Slomp CP, Spiteri C, Van Cappellen P (2009), Benthic-pelagic coupling and the seasonal silica cycle in the Bay of Brest (France): new insights from a coupled physical-biological model. Marine Ecology Progress Series, 385: 15-32 Leynaert A, Tréguer P, Nelson DM, Del Amo Y (1996), 32Si as a tracer of biogenic silica production: Methodological improvements, in Integrated marine system analysis.Minutes of the first meeting of the European Network for Integrated Marine Systems Analysis, Bruges, ed. Baeyens J, Dehairs F, Goyens, L, Laboratorium voor Analytische Chemie, Vrije Universiteit Brussel, Belgium, 29-35 Leynaert A, Ni Longphuirt S,Claquin P, Chauvaud L, Ragueneau O (2009), No limit? The multiphasic uptake of silicic acid by benthic diatoms, Limnology and Oceanography, 54(2): 571-576 Lorenzen CJ (1967), Determination of Chlorophyll and Pheo-Pigments: Spectrophotometric Equations, Limnology and Oceanography, 12: 343-346 Macintyre HL, Geider LJ, Miller DC (1996), Microphytobenthos: The ecological role of the Secret Garden of unvegetated, shallow-water marine habitats. I. Distribution, abundance and primary production, Estuaries, 19: 186-201 Margalef R (1978), Life-forms of phytoplankton as survival alternatives in an unstable environment, Oceanologica Acta 1: 493-509 Martin S, Clavier J, Chauvaud L, Thouzeau G (2007), Community metabolism in temperate maerl beds. II. Nutrient fluxes, Marine Ecology Progress Series, 335: 31-41

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Martin S, Clavier J, Guarini JM, Chauvaud L, Hily C, Grall J, Thouzeau G, Jean F, Richard J (2005), Comparison of Zostera marina and maerl community metabolism, Aquatic Botany, 83: 161-174 Muller PJ, Schneider R (1993), An automated leaching method for the determination of opal in sediments and particulate matter, Deep-Sea research I, 40: 425-444 Nelson DM, Tréguer P, Brzezinski MA, Leynaert A, Quéguiner B (1995), Production and dissolution of biogenic silica in the ocean: revised global estimates, comparison with regional data and relationship to biogenic sedimentation, Global Biogeochemical Cycle, 9: 359-372 Ni Longphuirt S (2006), Role du microphytobenthos dans le cycle dy silicium et le fonctionnement d'un ecosystème côtier: la Rade de Brest. PhD Thesis thesis. Université de Bretagne Occidentale. 1-210 Ni Longphuirt S, Clavier J, Grall J, Chauvaud L, Le Loc'h F, Le Berre I, Flye-Sainte- Marie J, Joelle R, Leynaert A (2007), Primary production and spatial distribution of subtidal microphytobenthos in a temperate coastal system, the Bay of Brest, France, Estuarine, Coastal and Shelf Science, 74: 367-380 Potin P, Floc'h JY, Augris C, Cabioch J (1990), Annual growth rate of the calcareous red alga Lithothamnion corallioides (Corallinales, Rhodophyta) in the Bay of Brest, France, Hydrobiologia, 204/205: 263-267 Ragueneau O, De Blas Varela E, Tréguer P, Quéguiner B, Del Amo Y (1994), Phytoplankton dynamics in relation to the biogeochemical cycle of silicon in a coastal ecosystem of western Europe, Marine Ecology Progress Series, 106: 157-172 Ragueneau O, Savoye N, Del Amo Y, Cotten J, Tardiveau B, Leynaert A (2005), A new method for the measurement of biogenic silica in suspended matter of coastal waters: using Si:Al ratios to correct for the mineral interference, Continental shelf research, 25: 697-710 Ragueneau O, Tréguer P, Leynaert A, Anderson RF, Brzesinski MA, DeMaster DJ, Dugdale R, Dymond J, Fischer G, François R, Heinze C, Maier-Reimer E, Martin-Jézéquel V, Nelson DM, Quéguiner B (2000), A review of the Si cycle in the modern ocean:recent progress and missing gaps in the application of biogenic opal as a paleoproductivity proxy, Global and Planetary Change, 26: 317-365 Round FE, Crawford RM, Mann DG (1990), The Diatoms. Biology and morphology of the genera. Cambridge University Press. Melbourne, Australia. 1-747 Sagan G, Thouzeau G (1998), Microphytobenthic biomass in the Bay of Brest and the Western English Channel, Oceanologica Acta, 21: 677-694 Sigmon DE, Cahoon LB (1997), Comparative effects of benthic microalgae and phytoplankton on dissolved silica fluxes, Aquatic microbial ecology, 13: 275- 284 Srithongouthai S, Sonoyama YI, Tada K, Montani S (2001), The influence of environmental variability on silicate exchange rates between sediment and water in a shallow-water coastal ecosystem, the Seto Inland Sea, Japan, Marine Pollution Bulletin, 47: 10-17 Sundbäck K, Linares F, Larson F, Wulff A (2004), Benthic nitrogen fluxes along a depth gradient in a microtidal fjord: the role of denitrification and microphytobenthos, Limnology and Oceanography, 49: 1095-1107 Tréguer P, Nelson DM, Van Bennekom AJ, DeMaster DJ, Leynaert A, Quéguiner B (1995), The silica balance of the world ocean: a reestimate, Science, 268: 375- 379

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Utermöhl H (1931), Neue wege in der quantitativen erfassung des planktons (mit besonderer berücksichtigung des ultraplanktons), Internationale Vereinigung fuer Theoretische und Angewandte Limnologie, 5: 567-596 Webster IT, Ford PW, Hodgson B (2002), Microphytobenthos Contribution to Nutrient- phytoplankton Dynamics in a Shallow Coastal Lagoon, Estuaries, 25: 540-551 Wilson S, Blake C, Berges JA, Maggs CA (2004), Environmental tolerances of free- living coralline algae (maerl): implications for European marine conservation, Biological Conservation, 120: 279-289

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CAPÍTULO 6. Discusión general, Conclusiones y Perspectivas

Discusión

6.1 Discusión general El presente trabajo de tesis comprende estudios de comunidades de microalgas en distintos sistemas litorales que han sido llevados a cabo a diferentes escalas espacio-temporales. Se han analizado las variaciones estacionales de comunidades de fitoplancton a lo largo de un gradiente de hábitats tropicales (Estudio 1); se han investigado las dinámicas intra-anuales de las concentraciones de nutrientes y de las comunidades de fitoplancton, así como sus implicaciones en el ciclo biogeoquímico del silicio a escala de hábitat y microhábitat, en una zona costera del Mediterráneo noroccidental (Estudio 2); se han estudiado las comunidades de diatomeas bentónicas inframareales del Atlántico Noreste asociadas al hábitat de maerl, analizando su variabilidad espacial dentro del hábitat y cuantificando por primera vez su contribución al ciclo biogeoquímico del silicio a escala local (Estudio 3). Los estudios de comunidades de microalgas llevados a cabo en el presente trabajo de tesis comprenden desde zonas para las que existían numerosos estudios previos (Mediterráneo NO, p.e. Margalef 1957, Estrada 1979, Masó and Duarte 1989, Velásquez Forero 1997, Guadayol et al 2009), pero que no analizaban la variabilidad espacio-temporal a la escala considerada en este trabajo, a zonas para las que sólo existían estudios fragmentados (Caribe, p.e. Kling 1975, Hargraves 1982, Faust 1990, Faust 1993c, Morton and Faust 1997, Faust 2004), hasta zonas para las que la información taxonómica era inexistente (hábitat de maerl del Atlántico NE). Las comunidades de microalgas analizadas presentan elevada diversidad y riqueza específica, con una composición específica y valores de abundancia que resultaron variar en función de la zona (Caribe, Mediterráneo o Atlántico Noreste), de la estación, del hábitat, y también a escala sub-estacional y dentro de un mismo hábitat. En general, la mayoría de las especies de microalgas que se han observado en los estudios que componen el presente trabajo son cosmopolitas (p.e., Tomas 1997, Horner 2002). En todos los sistemas costeros analizados, las diatomeas han resultado ser el grupo de microalgas mejor representado, seguidas por los

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dinoflagelados, como esperado (p.e., Lockwood et al 1998). En muestras de plancton demersal, se han observado tanto especies típicamente descritas como planctónicas como especies descritas como bentónicas, poniendo en evidencia que en los sistemas costeros poco profundos resulta difícil establecer una distinción radical entre estos dos compartimentos. Entre las microalgas presentes en el plancton, se han observado pocas especies dominantes y muchas presentes en baja o muy baja densidad, un patrón que difiere del encontrado en el bentos. Varios factores pueden influir en los patrones de complejidad observados en el plancton, como la turbulencia y diversos parámetros ecofisiológicos, dejando abierto un debate histórico (e.g., Margalef 1978, Kemp and Mitsch 1979, Estrada and Berdalet 1997, Arin et al 2002, Irigoien et al 2004). En las especies presentes en la columna de agua, en muchos casos se ha observado una distribución agregada de las células, bien debido a la presencia de colonias, bien debido a la capacidad de “nadar” de algunas especies y de asociarse con detritus flotantes (Faust and Gulledge 1996). El estudio de las comunidades de fitoplancton en el Caribe (Estudio 1) reveló diferencias entre hábitats en la composición específica dependientes de la estación y que no se adaptaban al gradiente offshore-inshore esperado. Las comunidades de microfitobentos asociadas a bancos de maerl en la Bahía de Brest (Atlántico NE) mostraron diferencias en abundancia y composición específica dentro a escala de algunos km, entre la mitad norte y la mitad sur de la bahía. El fitoplancton, por lo contrario, mostró un suave gradiente de variación espacial. En el caso del estudio llevado a cabo en Mediterráneo (Estudio 2), por lo contrario, las diferencias observadas entre los hábitats comparados (columna de agua y capa límite de sustrato rocoso) resultaron permanentes a lo largo del año. Estos patrones complejos son el resultado de múltiples interacciones físico-químicas y biológicas. La zona de estudio del Caribe presenta una plataforma continental ancha, pequeñas mareas y diferentes hábitats adyacentes e interconectados, pero que difieren entre sí por sus características hidrodinámicas y sus comunidades biológicas locales. Estas características pueden favorecer la creación de discontinuidades en los parámetros físico-químicos del agua que fluye desde el océano abierto hacia la laguna, resultando en masas de agua diferentes, con características distintas y que además varían con la estación, que seleccionan comunidades microalgales propias. En un sistema macromareal e influenciado por frecuentes vientos y tempestades, como en el caso de la Bahía de Brest, la masa de agua está más mezclada, lo que conlleva una mayor homogeneidad. En el litoral Mediterráneo, muy poco influenciado por las mareas, las causas de las diferencias

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permanentes observadas entre las comunidades de microfitoplancton de la columna de agua y las de la capa límite de fondos rocosos se pueden originar en el efecto del hidrodinamismo local y en diferencias que se crean a pequeña escala en las concentraciones de nutrientes. A su vez, las causas de estos patrones hidrodinámicos y físico-químicos locales se tienen que buscar en la topografía irregular del fondo, en la interacción con fenómenos atmosféricos, así como en los efectos de las comunidades locales. En sistemas poco profundos, como los analizados en este trabajo, los oranismos bentónicos modifican el espesor de la capa límite, crean zonas de retención de agua y partículas, alteran el patrón de deposición del material en suspensión, y en definitiva, modifican los flujos de agua, células y nutrientes (p.e., Glynn 1973, Chauvaud et al 2000, Jørgensen 2001). Los sistemas costeros analizados en el presente trabajo difieren entre si en cuanto a localización geográfica, características climáticas y estacionalidad, comunidades biológicas locales, concentración de nutrientes y tasa de reciclado de los mismos. En los tres sistemas en estudio, la disponibilidad de nutrientes parece ser uno de los principales factores de entre los analizados responsable de la limitación de la abundancia de microalgas. La importancia y el orden relativo de cada nutriente como limitante la producción microalgal dependió de la zona, de la estación, del hábitat y del microhábitat. La zona de estudio del Estudio 1, un sistema recifal con islas de manglar cercanas, ha resultado tener concentraciones de nutrientes intermedias entre las de arrecifes de coral oligotróficos y las de áreas costeras con aportes terrígenos (Shyka and Sebens 2000, Beucher et al 2004). En este sistema, la producción de microalgas parece estar limitada por diferentes combinaciones de nutrientes, que varían en función de la estación, en primer lugar, y del hábitat, en segundo lugar. El silicato parece limitante a lo largo de todo el año, siendo co-limitante con el fosfato en diciembre, y con nitrito y nitrato en julio. Las diferencias entre hábitats en las comunidades de microalgas parecen ser debidas principalmente a la combinación de concentración de silicato y de compuestos inorgánicos del nitrógeno. Sin embargo, habría que realizar estudios adicionales, como cinéticas de uptake de los distintos nutrientes, para delucidar los efectos limitantes de cada uno en un sistema donde la tasa de reciclado puede ser muy rápida (p.e., D'Elia and Wiebe 1990). Las concentraciones de nutrientes observadas en el Estudio 2, llevado a cabo en un área costera rocosa expuesta, han confirmado que la zona de estudio se puede definir como oligotrófica, a pesar de encontrarse en un entorno urbano y agrícola. Las comunidades microalgales locales parecen estar limitadas por la

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disponibilidad de nutrientes y, sólo en segundo lugar, por herbivoría del zooplancton. Silicato, fosfato y compuestos inorgánicos de nitrógeno han resultado tener diferente importancia como factores limitantes de la producción de fitoplancton, según la estación, el hábitat y, en menor medida, el microhábitat. En particular, los aportes de silicio y su reciclado en el interior del sistema, han resultado ser cruciales en determinar la abundancia y la alternancia estacional de grupos de microalgas. En particular, la falta de silicato en verano parece limitar las diatomeas y promover el crecimiento de los dinoflagelados, confirmando los resultados de otros estudios (Conley et al 1993, Nelson and Dortch 1996, Del Amo et al 1997, Sommer 1998). En este sistema, el fosfato parece tener un papel secundario como nutriente limitante, al contrario de lo que pasa en otros sistemas (Del Amo et al 1997, Granéli et al 1999, Leblanc et al 2003) . En la Bahía de Brest (Estudio 3) se ha observado una limitación de la producción de MPB, especialmente marcada en verano, que se puede deber a un conjunto de factores, en particular a las bajas concentraciones de nutrientes, principalmente nitrógeno y fosfato, y secundariamente silicato, concordando en parte con estudios anteriores sobre el fitoplancton de la bahía (Ragueneau et al 1994, Del Amo et al 1997). Las aproximaciones de análisis desarrolladas en el presente trabajo aportan información útil, si bien no exhaustiva, para interpretar las relaciones entre los factores ambientales y las comunidades de microalgas. Las variables ambientales analizadas (p.e., concentración de nutrientes, temperatura, salinidad, pluviosidad, radiación solar) muestran a menudo patrones de variación correlacionados, complicando así la jerarquización de sus respectivos efectos en una determinada comunidad de microalgas. En el caso del hábitat de manglar (Estudio 1), por ejemplo, a pesar de haber mayores concentraciones de nutrientes, la limitación del crecimiento algal podría derivar de factores como la turbidez y la sombra creada por la copa de los árboles, las elevadas temperaturas del agua o fluctuaciones de salinidad (Kathiresan and Bingham 2001). La producción de microfitobentos asociado al maerl (Estudio 3) podría verse afectada, al menos en otoño, por factores físicos que alteran la estabilidad del sustrato, tales como olas, tempestades, resuspensión y turbidez inducida por transporte fluvial de material en suspensión (Hily et al 1992), así como por la baja y variable radiación solar (Del Amo et al 1997). Además, otros factores, como la dinámica poblacional y estacional de los consumidores de microalgas, pueden tener fuertes efectos sobre la abundancia y la composición local de las comunidades. Por ejemplo, como se deduce del Estudio 2, los copépodos pueden participar en el control de las poblaciones

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de diatomeas planctónicas, directamente, a través de herbivoría, e indirectamente, a través del secuestro de sílice biogénica en fecal pellets, que ralentiza el reciclado de la sílice biogénica contenida en ellos (Schultes 2004, Moriceau et al 2007a, Moriceau et al 2007b). En particular, en sistemas costeros poco profundos, como los analizados en el presente trabajo, el acoplamiento bento-pelágico puede jugar un papel relevante en cuanto a modificación de comunidades fitoplanctónicas debido a la presencia de filtradores y de otros organismos que alteran los balances y los flujos de nutrientes locales (p.e., Legendre and Demers 1984, Denman and Powell 1984, Sommer 1989, Sigmon and Cahoon 1997, Paterson and Black 1999, Chauvaud et al 2000, Jørgensen 2001). Por ejemplo, las bajas concentraciones de silicato registradas cerca del sustrato rocoso en el Estudio 2 se podrían deber, entre otros factores, a la actividad de organismos silícicos bentónicos, como esponjas (e.g., Maldonado et al 2005) y diatomeas (e.g., Sigmon and Cahoon 1997, Estudio 3 del presente trabajo), muy abundantes asociadas a estos fondos rocosos (Bucci, observación personal). Una investigación complementaria al Estudio 1 del presente trabajo (Maldonado et al 2010) evidencia que las poblaciones de esponjas silícicas puedan ejercer algún tipo de control sobre el stock de silicio local. Como se ha demostrado en el Estudio 3, las diatomeas bentónicas pueden llegar a representar una pieza muy importante para comprender los ciclos biogeoquímicos de los nutrientes en ambientes costeros, y en particular de elementos como el silicio, ya que, en zonas poco profundas, pueden hasta superar en biomasa el plancton de la columna de agua sobrestante. Un estudio preliminar de cuantificación de BSi bentónica procedente de diatomeas asociadas a los mismos fondos rocosos analizados en el Estudio 2 reveló la presencia de una considerable cantidad de BSi (409 ± 333 g BSi m2, si bien en parte se debe a detrito, Bucci resultados no publicados). Además, los patrones espacio- temporales de biomasa de las microalgas bentónicas, así como de BSi a ellas asociada, presentan elevada variabilidad dependiendo del hábitat considerado (Estudio 3, Sigmon and Cahoon 1997, Ni Longphuirt 2006), pero también dentro de un mismo hábitat (Estudio 3), indicando la necesidad de utilizar aproximaciones a diferentes escalas espacio-temporales a la hora de cuantificar los stocks de silicio en diferentes sistemas. Los resultados del presente trabajo de tesis sugieren la existencia de un delicado equilibrio entre las comunidades microalgales y los parámetros ambientales en distintos sistemas costeros, en particular, una estrecha relación con la concentración de nutrientes. Este equilibrio muestra variaciones espaciales y temporales tales que, para su descripción y comprensión, requieren

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6.2 Conclusiones

i. La abundancia y composición específica de las comunidades de microalgas analizadas en diferentes sistemas costeros mostraron variabilidad en función de la zona (Caribe, Mediterráneo o Atlántico NE), de la estación y del hábitat. También se observó variabilidad a escala sub-estacional y dentro de un mismo hábitat. a. Las comunidades de fitoplancton asociadas a un sistema tropical de arrecife de la plataforma continental de Belize mostraron diferencias entre hábitat dependientes de la estación, no organizadas a lo largo del gradiente offshore- inshore esperado. b. En la zona costera del Mediterráneo Noroccidental se observó una alternancia estacional en las especies dominantes del fitoplancton. También se detectaron, durante todo el año, diferencias en las comunidades de fitoplancton comparando diferentes hábitats (columna de agua y capa límite de sustrato rocoso). c. Las comunidades de microfitobentos asociadas a bancos de maerl en la Bahía de Brest (Atlántico NE) mostraron diferencias en abundancia y composición específica dentro del mismo hábitat, entre la mitad norte y la sur de la bahía. Este patrón de variación espacial no se reflejó en el fitoplancton, que, por el contrario, mostró un gradiente suave de variación. También se observaron diferencias estacionales ii. En todos los sistemas costeros analizados, las diatomeas fueron el grupo de microalgas más abundante, seguidas por los dinoflagelados. iii. Las variables ambientales analizadas, aunque limitadas, aportan información útil para interpretar los complejos patrones de variación espacio-temporal de las comuidades de microalgas costeras. A pesar de que varias de las variables ambientales consideradas estén hasta cierto punto correlacionadas, la disponibilidad de nutrientes ha resultado ser el principal factor ambiental analizado responsable de la abundancia y composición específica de las comunidades de microalgas.

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iv. La importancia y el orden relativo de cada nutriente como limitante de la producción microalgal depende de la zona, de la estación, del hábitat y del microhábitat. a. En el sistema recifal del Caribe, el silicato emergió como limitante a lo largo de todo el año, siendo co-limitante con el fosfato en diciembre, y con el nitrito y el nitrato en julio. Las diferencias entre hábitats en las comunidades de microalgas parecieron ser debidas principalmente a la combinación de concentración de silicato y de compuestos inorgánicos de nitrógeno. b. En Mediterráneo Noroccidental, los aportes de silicio y su reciclado en el sistema resultaron ser los principales determinantes de la abundancia y la alternancia estacional de las especies y grupos dominantes de microfitoplancton. La disponibilidad de silicatos pareció ser más limitante en la capa límite de sustrato rocoso comparado con la columna de agua. La concentración de nutrientes y las proporciones relativas de N:Si:P variaron en función de la estación, del hábitat y, en menor medida, del microhábitat. c. En la Bahía de Brest, el nitrógeno pareció limitar la producción de diatomeas bentónicas en otoño, mientras que una combinación de nitrógeno, fósforo y silicio pareció ser el factor limitante en verano. v. Los resultados de MPB asociado a bancos de maerl evidencia el papel clave de las diatomeas bentónicas en el ciclo biogeoquímico del silicio en sistemas costeros, comparable con el del fitoplancton, y subraya la importancia de considerar diferentes hábitats y escalas de variabilidad espacio-temporales a la hora de desarrollar modelos biogeoquímicos del silicio en sistemas costero. vi. El estudio de las comunidades de microalgas en diferentes sitemas costeros ha revelado la existencia de complejas relaciones entre los factores ambientales y las comunidades biológicas locales. El resultado es la gran variabilidad en los patrones de variación de las comunidades de microalgas a diferentes escalas espacio-temporales, un factor que se debería tener en cuenta a la hora de desarrollar estudios y modelos en sistemas costeros.

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6.3 Conclusions

i. The abundance and specific composition of the microalgae communities of the different analyzed coastal systems varied as a function of zone (Caribbean, Mediterranean or NE Atlantic), season, and habitat. We also detected variability at sub-seasonal and within-habitat scale. a. The phytoplankton communities associated to a tropical reef system of the Belize continental shelf showed between-habitat, season-depending differences, which were not organized along the expected offshore-inshore gradient. b. In the NW Mediterranean coastal zone, we observed a seasonal replacement of dominant phytoplankton species. We also detected year-round between- habitat (water column and boundary layer of rocky bottom) differences in phytoplankton communities. c. The microphytobenthic communities associated to maerl beds of the Bay of Brest (NE Atlantic) showed within-habitat differences in abundance and specific composition between the northern and the southern half of the Bay. This spatial pattern of variability was not observed for the overlying phytoplankton communities, which varied along a smooth gradient instead. We also observed seasonal differences. ii. In all the analyzed coastal systems, diatoms were the most abundant microalgal group, followed by dinoflagellates. iii. The analyzed environmental variables, even though limited, were useful tools to intrerpret the complex spatio-temporal variability patterns of coastal microalgal communities. Despite several considered environmental variables being correlated to some degree, nutrient availability appeared as the main factor responsible for microalgae community abundance and specific composition.

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iv. The importance and rank of each nutrient as a limiting factor of microalgae production depended on zone, season, habitat and microhabitat. a. In the Caribbean reef system, silicate availability appeared limiting all year- round, being co-limiting with phosphate in December, and with nitrite and nitrate in July. Between-habitat differences in microalgae communities seemed mainly due to the combined effect of silicate and inorganic nitrogen compound concentration. b. In NW Mediterranean, silicon availability and recycling within the system seemed the main responsible in determinig the abundance and seasonal replacement of dominant phytoplankton species and groups, and it appeared more limiting in the boundary layer of rocky bottoms than in the water- column habitat. Nutrient concentrations and N:Si:P ratios varied as a function of season, habitat and, to a lesser extent, of microhabitat. c. In the Bay of Brest, nitrogen seemed to limit production of benthic diatom communities in autumn, while a combination of nitrogen, phosphorous and silicon appeared as the responsible of summer limitation.

v. Our results of MPB associated to maerl beds remark the key role of benthic diatoms in the silicon cycle of coastal systems, comparable to that of phytoplankton, and highlight the importance of considering different habitats and spatial scales of variability when developing biogeochemical models of the cycle of silicon in coastal systems. vi. The study of microalgal communities in different coastal systems revealed the existence of complex relationships between environmental factors and local biological communities. The result is a great variability in microalgal patterns at different spatio- temporal scales, which should be taken into account when developing studies and models in coastal systems.

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6.4 Perspectivas

Para aumentar el nivel de comprensión de las complejas relaciones ecológicas en las que están implicadas las microalgas en las zonas costeras haría falta analizar diferentes niveles de interacción entre las comunidades de micralgas y variables ambientales. Las técnicas moleculares podrían ayudar en mejorar la identificación taxonomica de algunas especies. El desarrollo de sistemas expertos eficientes y fiables para el procesado de muestras de microalgas podría acelerar, aunque no sostituir, la tarea de clasificación y contaje de células mediante observación al microscopio, que con frecuencia es un factor que limita el número de réplicas, debido a la especialización y al tiempo que su análisis requiere. Se necesitarían más estudios que proporcionen datos acerca de la autoecología de las diferentes especies, como por ejemplo sus requerimientos nutricionales específicos, su capacidad de mixotrofía, sus ciclos de vida y capacidad de producir formas de resistencia, su estacionalidad y tasa de producción en distintos sistemas, su plasticidad fisiológica para adaptarse a diferentes condiciones ambientales etc. Además, sería deseable tener mejor información sobre las relaciones tróficas, como la existencia y los efectos de herbivoría selectiva, y como éstas afectan la veocidad de reciclado y los flujos de los nutrientes en distintos sistemas, en particular en sistemas pocos profundos, donde el acoplamiento bento-pelágico puede tener un papel relevante en modificar la abundancia y composición de las comunidades de microalgas locales. Para alcanzar estos objetivos sería deseable realizar experimentos de cultivo en laboratorio y en mesocosmo in situ, no sólo de especies individuales, sino también de comunidades naturales, en diferentes condiciones ambientales (variaciones en la cantidad y calidad de luz, ciclos circadianos, temperatura, salinidad etc.), así como en presencia de diferentes concentraciones de nutrientes, en ausencia o presencia de depredadores. El uso de marcadores isotópicos radioactivos sería una buena herramienta en el estudio de flujos de sustancias. En particular, para mejorar las estimas de los flujos de silicio en distintos sistemas, sería necesario, en primer lugar, cuantificar las aportaciones de cada uno de los compartimentos ambientales, sin descartar ninguno a priori, como se ha sugerido desde estudios sobre el papel de invertebrados bentónicos consumidores de silicio (e.g., Maldonado et al 2010) o como surgido de recientes estudios sobre el microfitobentos (e.g., Leynaert et al 2009, presente trabajo). Para

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ello se necesitaría de manera urgente mejorar los métodos de determinación de BSi, evitando contaminaciones y errores analíticos que puedan falsar la importancia relativa de cada compartimento (como, por ejemplo, utilizar correcciones por sílice litogénica, o considerar la proporción y el orígen del detrito frente a células vivas). Serían deseables mediciones precisas de producción y stock de BSi en diferentes hábitats y escalas espacio-temporales, especialmente en el bentos, para el que los datos todavía escasean. Seguidamente, harían falta estudios de velocidad de disolución y reciclado de sílice biogénica de diferente orígen y en diferentes condiciones, así como estudios adicionales de cinética de uptake de Si en comunidades naturales. El uso de cámaras bentónicas podría ser útil a la hora de realizar estudios de acoplamiento bento- pelágico. Asimismo, una vez implementado el conocimiento sobre el ciclo biogeoquímico del silicio sería necesario, para mejorar la interpretación de los patrones naturales y desarrollar modelos ambientales predictivos, poder relacionar el ciclo del silicio con los ciclos de otros elementos, en particular carbono, nitrógeno y fósforo.

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Bibliografía y otras fuentes consultadas durante la identificación taxonómica de microalgas Balech E (1988), Los Dinoflagelados del Atlántico Sudoccidental. Publicaciones Especiales del Instituto Español de Oceanografía, 1. 1-310 Chrétiennot-Dinet MJ, Sournia A, Ricard M, Billard C (1990), Atlas du phytoplankton marin. Vol.3. Chlorarachniophycées, Chlorophycées, Chrysophycées, Cryptophycées, Euglenophycées, Eustigmatophycées, Prasinophycées,Prymnesiophycées, Rhodophycées, Tribophycées. Editions du CNRS, Paris, France. 1-261 Cupp EE (1943), Marine plankton diatoms of the west coast of North America, Bulletin. Scripps Institution of Oceanography. Technical Series 5 (1), 1-237 Faust MA, Gulledge RA (2002), Identifying harmful marine dinoflagellates, Smithsonian Institution Contributions from the United States National Herbarium 42: 1-144 Hasle GR, Syvertsen EE (1996), Marine diatoms, in Identifying marine diatoms and dinoflagellates, ed. Tomas CR. Academic Press, San Diego, USA. 5–386 Horner R (2002), A taxonomic guide to some common marine phytoplankton, Biopress Ltd., Bristol, UK. 1-195

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Larink O, Westheide W (2006), Coastal plankton - Photo guide for European Seas. Verlag Dr. Friedrich Pfeil, München, Germany. 1-143 Loir M (2004), Guide des diatomées, Delachaux & Niestlé, Paris, France. 1-240 Massuti M, Margalef R (1950), Introducción al estudio del plancton marino. Barcelona: Instituto de Biologia Aplicada. 1-182 Rampi L, Bernhard M (1978), Key for the determination of the Mediterranean pelagic diatoms. ENEA(CNEN), Rapporto Tecnico, RT/BIO (78)1. 1-71 Rampi L, Bernhard M (1980). Chiave per la determinazione delle peridinee pelagiche mediterranee. ENEA(CNEN), Rapporto Tecnico, RT/BIO(80)8. 1-193 Rampi L, Bernhard M (1981), Chiave per la determinazione delle coccolitoforidee mediterranee. ENEA(CNEN), Rapporto Tecnico, RT/BIO(81)13. 1-98 Ricard M (1987), Atlas du Phytoplancton marin. Vol II - Diatomophycées. Editions du Centre National de la Recherche Scientifique 2, Paris, France. 1-297 Round FE, Crawford RM, Mann DG (1990), The Diatoms. Biology and morphology of the genera. Cambridge University Press. Melbourne, Australia. 1-747 Sournia A (1986), Atlas du phytoplankton marin. Volume 1: Introduction, Cyanophydées, Dictyochophydées, Dinophycées et Raphidophycées. Editions du Centre National de la Recherche Scientifique, Paris, France. 1-219 Tomas CR (1997), Identifying marine phytoplankton. Academic Press: San Diego, USA. 1-858 Witkowski A, Lange-Bertalot H, Metzeltin D (2000), Diatom flora of marine coasts, in Iconographia Diatomologica. Annotated Diatom Micrographs, ed. Lange-Bertalot H, ARG Gantner Verlag KG, Ruggel, Liechtestein. 1-925

http://www.algaebase.org http://www.cbd.int/GBO2 http://www.un.org/es/events/biodiversity2010 http://www.marbef.org http://ucjeps.berkeley.edu/INA.html http://www.ceab.csic.es/~oceanlab http://www.com.univ-mrs.fr/PHYTOCOM http://planktonnet.sb-roscoff.fr http://www.serc.si.edu/ http://www.io-warnemuende.de http://www.math.ualberta.ca http://www.indiana.edu http://botany.si.edu http://www.diatomloir.eu

142

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ANEXO 1. Supplementary Tables

Supplementary Tables

The following Supplementary Tables list the species of microalgae found throughout Study 1, 2, and 3. The identification has been carried out with the help of several microalgae guides and pubblications, and also with images and web-sites found on-line. Among the consulted sources: Cupp 1943, Massutí and Margalef 1950, Rampi and Bernhard 1978, Rampi and Bernhard 1980, Rampi and Bernhard 1981, Sournia 1986, Ricard 1987, Balech 1988, Chrétiennot-Dinet 1990, Round et al 1990, Hasle et al 1996, Tomas 1997, Velásquez Forero 1997, Witkowski et al 2000, Loir 2004, Faust and Gulledge 2002, Horner 2002, Larink and Westheide 2006. http://www.com.univ-mrs.fr/PHYTOCOM, http://planktonnet.awi.de, http://www.algaebase.org, http://ucjeps.berkeley.edu/INA.html, http://www.io- warnemuende.de, http://www.serc.si.edu, http://www.math.ualberta.ca, http://www.indiana.edu, http://www.marbef.org, http://botany.si.edu, http://www.diatomloir.eu The identification was carried out at the species level whenever possible. However, in some cases, either we only could reach the genus level or higher (e.g., Amphora sp.), either we grouped similar species due to the impossibility to separe them (e.g., Thalassionema frauenfeldii/bacillare), either we grouped species by size classes (e.g., Navicula 20-40 µm). Since microalgae taxonomy and systematics are continuously reorganized, generating many synonimies, we report here the nomenclature according to one source, http://www.algaebase.org (with the actualization of the genus Ceratium to Neoceratium by Gómez et al 2010).

145 ANEXO 1. Supplementary Tables

Supplementary Table 1. Study 1, Caribbean. List of species* per season and habitat. O=open water, R=fore reef, P=patch reef, T=turtle-grass bed, M=mangrove.

December 2005 July 2006

Species O R P T M O R P T M

Diatoms Amphora hyalina x x x x x Amphora plicata x x Amphora sp. x x x x Asterionella formosa x x x x x x Asterionellopsis glacialis x x x Asterolampra marylandica x x x x Asteromphalus heptactis x x Asteroplanus karianus x x Bacillaria paradoxa x x x Bacteriastrum delicatulum x x x Bacteriastrum elongatum x Bacteriastrum furcatum x x x x x x x Bacteriastrum hyalinum x x x x Bacteriastrum princeps x x x Bacteriastrum sp. x x x x Biddulphia alternans x Biddulphia biddulphiana x x Caloneis sp. x x x Campylodiscus clypeus x Campylodiscus fastuosus x x Campylodiscus limbatus x x Chaetoceros affinis var. circinalis x x x x x x x x x x Chaetoceros atlanticus x x Chaetoceros curvisetus x Chaetoceros danicus x x Chaetoceros decipiens x x x x x x Chaetoceros decipiens var. singularis x x x Chaetoceros dichaeta x x x x Chaetoceros lacinosus x x x x Chaetoceros laevis x x x x x Chaetoceros lauderi x Chaetoceros lorenzianus x x x x x x x x x Chaetoceros pendulus x x x x x x x Chaetoceros peruvianus x x x x x Chaetoceros pseudocurvisetus x Chaetoceros socialis x x Chaetoceros spp. x x x x Chaetoceros teres? x Climacosphenia moniligera x x x x x x x x Cocconeis sp. x x x x x x x Corethron sp. x Coscinodiscus centralis x x x x x

(Continues)

146

ANEXO 1. Supplementary Tables

Supplementary Table 1 (Continues)

December 2005 July 2006

O R P T M O R P T M

Coscinodiscus curvatulus x x Coscinodiscus gigas x Coscinodiscus granii x x x x x x x Coscinodiscus marginatus x x Coscinodiscus oculus iridis x x x Coscinodiscus radiatus x x x Coscinodiscus sp. x x x x Cylindrotheca (Ceratoneis) closterium x x x x x x x Cymbella sp. x Dactyliosolen fragilissimus x x x Diatom s.i. x x x x x Dictyoneis marginata x x x x x x x x Diploneis crabro x Diploneis gorjanovici x x Ditylum brightwellii x x x x x Entomoneis alata x x x Entomoneis constricta x x x Entomoneis gigantea x Entomoneis ornata x Entomoneis paludosa x Entomoneis sp. x x x x x Eucampia zodiacus x x Fragilaria crotonensis x x Grammatophora oceanica x x x Guinardia delicatula x x x x x x Guinardia striata x x x x x x x x Gyrosigma balticum x Gyrosigma elongatum x x x Gyrosigma sp. x x x x x x x Gyrosigma spenceri x x x Hantzschia sp. x x Hemiaulus hauckii x x x x x x x x Hemiaulus sinensis x x x Leptocylindrus danicus x x x x Licmophora flabellata x x x x x x x x x Licmophora tincta x x Lyrella lyra x Mastogloia sp. x x x x x x Melosira granulata x Membraneis challengeri x x x Navicula distans x Navicula elginensis x Navicula sp. x x x Navicula spp. x x x x x x x x x

(Continues)

147 ANEXO 1. Supplementary Tables

Supplementary Table 1 (Continues)

December 2005 July 2006

O R P T M O R P T M

Navicula tripunctata x x Nitzschia longissima x x x x x x Nitzschia reversa x Odontella aurita x Odontella mobiliensis x Paralia sulcata x x Pinnularia sp. x x x x x x x x Pinnularia trevelyana x x Plagiogramma pulchellum x Pleurosigma angulatum x x Pleurosigma elongatum x x x Pleurosigma normanii x Pleurosigma sp. x x x Proboscia alata x x x x x x x x Pseudo-nitzschia delicatissima x x x x x x x x Pseudo-nitzschia seriata x x x x x x x Pseudosolenia calcar-avis x x x x Rhizosolenia pungens x x Rhizosolenia robusta x x x x Rhizosolenia setigera x x x x x x x x x x Skeletonema costatum x x x Streptotheca thamensis ? x Striatella sp. x x x Striatella unipunctata x x x x x x x x Synedra fulgens x x x x x x x x Synedra sp. x x x x x Thalassionema frauenfeldii/bacillare x x x x x x x x x x Thalassionema nitzschioides x x x x x x x x x x Thalassionema sp. x x x x Thalassiosira anguste-lineata x Thalassiosira leptopus x x x x x Thalassiosira punctigera x Thalassiosira sp. x x x x x x x x x x Thalassiosira spp. x x x x x x Thalassiotrix longissima x x x x x Thalassiotrix mediterranea x x Thalassiotrix spp. x Toxarium undulatum x x Triceratium alternans x Triceratium obtusum x x x x x x x x x x Tropidoneis lepidoptera x x

(Continues)

148

ANEXO 1. Supplementary Tables

Supplementary Table 1 (Continues)

December 2005 July 2006

O R P T M O R P T M

Dinoflagellates Amphidinium spp. x x x x x x x x x Blepharocysta splendor-maris x Ceratocorys armata x Ceratocorys horrida x x Corytodinium tessellatum x Dinoflagellate cyst x x x x x x x x Dinoflagellate s.i. x x x x Dinophysis caudata x Dinophysis rotundata x x Dinophysis sp. x x x x Glenodinium danicum x Gonyaulax sp. x x Gonyaulax polyedra x Gonyaulax spinifera x Gymnodinium sanguineum x x x x Gymnodinium spp. x x x x x x x x x Gymnodinium uncatenatum x Gyrodinium dominans x x Gyrodinium estuariale x x x x Gyrodinium fusiforme x x x x x x Gyrodinium spirale x x x x x x x Gyrodinium spp. x x x x x x x x x Heterocapsa sp. x Kofoidinium velleloides x x Neoceratium belone x Neoceratium candelabrum x Neoceratium contortum x x Neoceratium furca x x x x x x x Neoceratium fusus x x x Neoceratium lineatum x x x x x x x x x Neoceratium pentagonum x x x x x x x Neoceratium setaceum x Neoceratium teres x Neoceratium trichoceros x x Neoceratium tripos x Ornithocercus magnificus x Ostreopsis ovata x Ostreopsis sp. x Oxytoxum longiceps x x x Oxytoxum mediterraneum x x x x Oxytoxum scolopax x x Oxytoxum variabile ? x Phalacroma ovum x x

(Continues)

149 ANEXO 1. Supplementary Tables

Supplementary Table 1 (Continues)

December 2005 July 2006

O R P T M O R P T M

Plagiodinium belizeanum x x x Podolampa bipes x x x x Polykrikos kofoidi x Polykrikos sp. x x x Prorocentrum balticum x Prorocentrum belizeanum x x x Prorocentrum compressum x Prorocentrum emarginatum x x Prorocentrum lima x x Prorocentrum mexicanum x x Prorocentrum micans x x x x x Prorocentrum minimum x x Prorocentrum ruetzlerianum x Prorocentrum scutellum x Prorocentrum sp. x x x x Protoperidinium bispinum x Protoperidinium brochi x x x Protoperidinium cerasus x x x x x x x x x Protoperidinium divergens x Protoperidinium globulus x x x Protoperidinium leonis x x x Protoperidinium sp. x x x x x x Pyrocystis lunula x Pyrophacus horologium x x x x x x Scripsiella precaria x Scripsiella trochoidea x x x x x x x x Torodinium sp. x x x x x x x x x Warnowia polyphemus x

Coccolithophorids Calyptrosphaera sp. x x Coccolithophorid s.i. x x x x x Discosphaera sp. x x x x x Discosphaera tubifera x Emiliania huxleyi x x x x Helicosphaera carteri x x x Helladosphaera sp. x Pontosphaera nigra x Rhabdosphaera sp. x x x Syracosphaera pulchra x Syracosphaera sp. x x x x x Toracosphaera sp. x x

Silicoflagellates Distephanum speculum x x x

150

ANEXO 1. Supplementary Tables

Supplementary Table 2. Study 2, Mediterranean. List of species.

Diatoms

Amphora hyalina Dactyosoloen fragilissimus Amphora sp. Dactyosoloen mediterraneus Aterionella kariana Detonula pumila Asterionellopsis glacialis Diploneis smithi Asteromphalus heptactis Diploneis sp. Asteromphalus hookeri Ditylium brightwelli Auliscus sculptus Entomoneis alata Bacillaria paradoxa Entomoneis sp. Bacteriastrum delicatulum Eucampia zodiacus Bacteriastrum elongatum Fragilaria crotonensis Bacteriastrum hyalinum Grammatophora marina Bacteriastrum sp. Grammatophora sp. Caloneis sp. Guinardia delicatula Campylodiscus limbatus Guinardia flaccida Cerataulina pelagica Guinardia sp. Chaetoceros affinis Guinardia striata Chaetoceros compressus Gyrosigma elongatum Chaetoceros constrictus Gyrosigma sp. Chaetoceros curvisetus Gyrosigma spenceri Chaetoceros dadayi Haslea crucigera Chaetoceros danicus Hemiaulus hauckii Chaetoceros debilis Hemiaulus sinensis Chaetoceros decipiens Lauderia annulata Chaetoceros decipiens f. singularis Leptocylindrus danicus Chaetoceros didymus Leptocylindrus minimus Chaetoceros laciniosus Licmophora sp. Chaetoceros lauderi Navicula <20 µm Chaetoceros lorenzianus Navicula >40 µm Chaetoceros messanensis Navicula 20-40 µm Chaetoceros pendulus Navicula marginata Chaetoceros peruvianus Navicula spp. Chaetoceros pseudocurvisetus Nitzschia longissima Chaetoceros radicans ? Nitzschia reversa Chaetoceros socialis Odontella aurita Chaetoceros sp. Odontella sp. Chaetoceros teres Okedenia inflexa Climacosphaenia moniligera Paralia sulcata Cocconeis sp. Parlibellus sp. Coscinodiscus centralis Pinnularia sp. Coscinodiscus concinnus Planktoniella sol Coscinodiscus grani Pleurosigma angulatum Coscinodiscus marginatus Pleurosigma elongatum Coscinodiscus sp. Pleurosigma nicobaricum Cylindrotheca (Ceratoneis) closterium Pleurosigma normani Cymatoneis sulcata Pleurosigma sp. Cymbella sp. Podocystit adriatica

(Continues)

151 ANEXO 1. Supplementary Tables

Supplementary Table 2 (Continues)

Proboscia alata Diplopsalis sp. Proboscia alata var. gracillima Gambierdiscus toxicus Pseudo-nitzschia delicatissima Goniodoma sp. Pseudo-nitzschia multistriata Gonyaulax diacantha Pseudo-nitzschia pungens Gonyaulax polygramma Pseudo-nitzschia seriata Gonyaulax sp. Pseudo-nitzschia spp. Gymnodinium coeruleum Pseudosolenia calcar-avis Gymnodinium spp. (big) Rhaphoneis sp. Gymnodinium spp. (med.) Rhizosolenia robusta Gymnodinium spp.(small) Rhizosolenia setigera/pungens Gymnodinium sanguineum Rhizosolenia styliformis Gyrodinium fusiforme Stephanopyxis/Skeletonema Gyrodinium spp. (big) Striatella unipunctata Gyrodinium spp. (med.) Surirella smithii Gyrodinium spp.(small) Surirella sp. Gyrodinium spirale Synedra fulgens Heterocapsa sp. Synedra sp. Kryptoperidinium sp. Synedra undulata Neoceratium declinatum declinatum Thalassionema frauenfeldii Neoceratium furca Thalassionema nitzschioides Neoceratium fusus Thalassionema sp. Neoceratium hexacanthum hexacanthum Thalassiosira pacifica? Neoceratium macroceros Thalassiosira sp. Neoceratium massiliense Thalassiosira spp. Neoceratium pentagonum Thalassiosira weissflogii Neoceratium sp. Thalassiotrix longissima Neoceratium trichoceros Thalassiotrix mediterranea Neoceratium tripos Triceratium obtusum Neoceratium tripos cf. tripoidioides Triceratium sp. Ornithocercus magnificus Tropidoneis sp. Ostreopsis ovata Oxytoxum areolatum? Dinoflagellates Oxytoxum longiceps Achradina spp. Oxytoxum margalefi? Alexandrium sp. Oxytoxum mitra Amphidinium spp. Oxytoxum oblicuum Ceratocorys horrida Oxytoxum parvum? Ceratocorys sp. Oxytoxum scolopax Corytodinium sp. Oxytoxum spp. Corytodinium tessellatum Oxytoxum sp. 1 Dinophysis acuminata Peridinium cerasus Dinophysis acuta Podolampa bipes Dinophysis caudata Podolampa sp. Dinophysis parvula Polykrikos sp. Dinophysis sp. Prorocentrum compressum

(Continues)

152

ANEXO 1. Supplementary Tables

Supplementary Table 2 (Continues)

Prorocentrum emarginatum Pontosphaera nigra Prorocentrum lima Rhabdosphaera spp. Prorocentrum mexicanum Schyphosphaera spp. Prorocentrum micans Syracolithus spp. Prorocentrum minimum Syracosphaera sp.1 Prorocentrum nanum Syracosphaera sp.2 Prorocentrum scutellum Prorocentrum spp. Silicoflagellate Protoperidinium bipes Dichtyocha fibula Protoperidinium bispinum Protoperidinium cassum Chlorophyt Protoperidinium conicum Schroederia setigera Protoperidinium curvipes Protoperidinium depressum Protoperidinium diabolus

Protoperidinium elongatum Protoperidinium grande Protoperidinium latidorsale? Protoperidinium leonis Protoperidinium longipes Protoperidinium mediterraneum Protoperidinium oceanicum Protoperidinium ovum Protoperidinium parvicollum Protoperidinium pellucidum stellatum Protoperidinium spp. Pyrocystis lunula Pyrocystis obtusa Pyrophacus horologicum Pyrophacus spp. Scripsiella precaria? Scripsiella trochoidea Torodinium robustum Warnowia polyphemus Dinoflagellate Cyst

Coccolitoph orids Calyptrosphaera spp. Coccolitophorid sp.1 Coccolitophorid sp.2 Coccolitophorid sp.3 Corisphaera spp. Discosphaera tubifer Emiliania huxleyi Helladosphaera spp. Homozygosphaera spp.

153 ANEXO 1. Supplementary Tables

Supplementary Table 3. Study 3, NE Atlantic. List of phytoplankton species* per season and maerl bed. M1a=Keraliou bank, autumn 2008; M1= Keraliou bank, summer 2009; M2=Rozegat, summer 2009; M3= Pen Ar Vir.

Species M1a M1 M2 M3 Diatoms Achnantes longipes x Amphora hyalina x Amphora sp.1 x Amphora sp.2 x x Bacillaria paradoxa x Chaetoceros atlanticus x x Chaetoceros debilis x Chaetoceros lorenzianus x x Chaetoceros peruvianus x x Chaetoceros socialis x Chaetoceros gracilis x x x Chaetoceros sp. x Climacosphenia moniligera x Cocconeis sp. x x x x Coscinodiscus centralis x Coscinodiscus oculus-iridis x Coscinodiscus radiatus x x Coscinodiscus sp. x Cylindrotheca (Ceratoneis) closterium x x x Cymbella sp. x Dactyliosolen fragilissmus x x x Diploneis bombus x x x Diploneis didyma x Detonula pumila x x Entomoneis sp. x x x Euchampia zodiacus x Grammatophora marina x x Guinardia delicatula x x Guinardia flaccida x x x Guinardia striata x x Gyrosigma sp. x x x x Hantzschia sp. x x Haslea crucigera x Hemiaulus hauckii x Lauderia annulata x Leptocilindrus danicus x x x Leptocilindrus minimus x x Licmophora sp. x Melosira nummuloides x Navicula <20 µm x x x Navicula >40 µm x x x Navicula 20-40 µm x x x x Navicula ramosissima x

(Continues)

154

ANEXO 1. Supplementary Tables

Supplementary Table 3 (Continues)

M1a M1 M2 M3 Nitzschia longissima x x x Odontella sp. x x x x Paralia sulcata x x x x Pinnularia sp. x x x x Pleurosigma sp. x x x Proboscia alata var. gracillima x Pseudo-nitzschia delicatissima x x x Pseudo-nitzschia pungens x x x x Pseudo-nitzschia seriata x x Pseudo-nitzschia sp. x Rhabdonema arcuatum x Rhizosolenia setigera x x x x Rhizosolenia styliformis/imbricata? x x x x Stauroneis sp. x Stephanopyxis sp. x x x Striatella unipunctata x Surirella sp. x Synedra gaillonii var macilenta x x x Synedra sp. x x Thalassionema frauenfeldii x x Thalassionema nitzschioides x x x x Thalassiosira spp. x x Triceratium sp. x x

Dinoflagellates Alexandrium sp. x x x x Amphidinium sp. x x x Corytohdinium sp. x x x x Dinophysis sp. x Gonyaulax sp. x Gymnodinium spp. (big) x Gymnodinium spp. (med.) x x x Gymnodinium spp. (small) x Gymnodinium sanguineum x x Gyrodinium spp. (big) x x x x Girodinium spp. (med.) x x x x Gyrodinium spp. (small) x x x Gyrodinium spirale x x Heterocapsa sp. x x x Neoceratium furca x x x x Neoceratium fusus x x x Neoceratium lineatum x Ostreopsis ovata x Oxytoxum sp. x x x Prorocentrum emarginatum x Prorocentrum micans x x x x

(Continues)

155 ANEXO 1. Supplementary Tables

Supplementary Table 3 (Continues)

M1a M1 M2 M3 Prorocentrum gracile x Protoperidinium conicum x Protoperidinium divergens x Protoperidinium spp. x x x x Pyrocystis lunula x Pyrophacus steini x Pyrophacus horologium x Scripsiella trochoidea x x x x Torodinium robustum x x Dinoflagellate Cyst x x

Chlorophyt Schroederia setigera x Scenedesmus sp. x

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ANEXO 1. Supplementary Tables

Supplementary Table 4. Study 3, NE Atlantic. List of benthic diatom species* per season and maerl bed. M1a=Keraliou bank, autumn 2008; M1= Keraliou bank, summer 2009; M2=Rozegat, summer 2009; M3= Pen Ar Vir; M4 = Loumergat, summer 2009.

Species M1a M1 M2 M3 M4 Diatoms Achnantes longipes x x x x x Achtinoptychus senarius x x x x Achtinoptychus splendens? x Amphora hyalina x x x x Amphora sp.1 x x x x x Amphora sp.2 x x x x x Asterionella formosa x x Bacillaria paradoxa x x x x x Caloneis crassa x x Campylodiscus sp. x x x x x Climacosphenia moniligera x x x x Cocconeis scutellum x x x x x Coscinodiscus sp. x Cylindrotheca closterium x x x x Cymbella sp. x x x x x Diploneis bomboides x x x x x Diploneis didyma x x x x x Diploneis oestrupii x x x x Diploneis smithii x x Entomoneis sp. x x x x x Fallacia/Lyrella sp. x x x x Flagilaria virescens? x Gomphonema sp. x Grammatophora marina x x x x x Gyrosigma sp. x x x x x Hantzschia sp. x x x Haslea crucigera x x Licmophora sp. x x x x x Melosira nummuloides x x x Navicula spp. <20 µm x x x x x Navicula spp. >40 µm x x x x x Navicula spp. 20-40 µm x x x x x Navicula radiosa ? x Navicula ramosissima x x x x Navicula rhyncocephala x x Nitzschia angularis x Nitzschia longissima x x x x x Nitzschia reversa x x

(Continues)

157 ANEXO 1. Supplementary Tables

Supplementary Table 4 (Continues)

M1a M1 M2 M3 M4 Nitzschia sigmoidea x x x x x Nitzschia palea? x x Odontella sp. x x x Oestrupia ergadensis x Paralia sulcata x x x x x Parlibellus delognei x x x x x Petroneis marina x x x Pinnularia sp. x x x x Pinnularia viridis x x x x Pleurosigma angulatum x x x x Pleurosigma elongatum x x x x x Pleurosigma salinarum? x Pleurosigma sp. x x x x Podocystis adriatica x x Podosira sp. x Pseudo-nitzschia delicatissima x x x Pseudo-nitzschia multistriata x x x x Pseudo-nitzschia pungens x x Pseudo-nitzschia seriata x x x Pseudo-nitzschia sp. x x x Rhabdonema arcuatum x x x x x Rhoicosphenia abbreviata x x x Stauroneis sp. x x Striatella unipunctata x x x x Surirella smithii x x Surirella sp. x Synedra capitata x Synedra gaillonii var macilenta x x x x x Synedra sp. x x x x x Thalassionema frauenfeldii x x x Triceratium sp. x x x x x Toxarium undulatum x x x x x

158

ANEXO 2

ANEXO 2. Photographs

Photographs

In this ANEXO 2, a sample of the diversity and beauty of the species of microalgae observed throughout the Study 1 (Caribbean), 2 (Mediterranean), and 3 (NE Atlantic) of the present work of thesis is reported. Photographs (not in scale) were taken through an inverted microscope or a scanning electron microscope.

I would like to thank Dr. Antonio Cruzado (CEAB-CSIC), Dr. Zoila Velásquez (CEAB-CSIC), and Dr. Beatriz Beker (Centre d'Océanologie de Marseille) for letting me use the inverted microscopes and their bibliography, Dr. Manuel Maldonado for providing me with his camera, Dr. Gérard Sinquin of the Plataforme d’Imagerie et de Mesures en Microscopie (Université de Bretagne Occidentale) for the pictures realized with the scanning electron microscope.

161

ANEXO 2. Photographs

Study 1. Belize, Caribbean

162

ANEXO 2. Photographs

Photo 1. Caribbean. Diatoms. Coscinodiscus radiatus

Photo 2. Caribbean. Diatoms. Licmophora tincta

163

ANEXO 2. Photographs

Photo 3. Caribbean. Diatoms. Chaetoceros affinis var. circinalis

Photo 4. Caribbean. Diatoms. Chaetoceros lorenzianus

164

ANEXO 2. Photographs

Photo 5. Caribbean. Diatoms. Thalassionema nitzschioides

Photo 6. Caribbean. Diatoms. Striatella unipunctata

165

ANEXO 2. Photographs

Photo 7. Caribbean. Diatoms. Entomoneis paludosa

Photo 8. Caribbean. Diatoms. Campylodiscus fastuosus

166

ANEXO 2. Photographs

Photo 9. Caribbean. Diatoms. Climacosphenia moniligera

Photo 10. Caribbean. Diatoms. Tropidoneis lepidoptera

167

ANEXO 2. Photographs

Photo 11. Caribbean. Diatoms. Toxarium undulatum

Photo 12. Caribbean. Diatoms. Biddulphia alternans

168

ANEXO 2. Photographs

Photo 13. Caribbean. An example of a mangrove-habitat assemblage, with numerous Prorocentrum spp. and coccolitophorids

Photo 14. Caribbean. Dinoflagellates. Oxytoxum scolopax

169

ANEXO 2. Photographs

Photo 15. Caribbean. Dinoflagellates. Plagiodinium belizeanum

Photo 16. Caribbean. Dinoflagellates. Prorocentrum mexicanum (on the right)

170

ANEXO 2. Photographs

Photo 17. Caribbean. Dinoflagellates. Ornithocercus magnificus

Photo 18. Caribbean. Dinoflagellates. Ceratocorys horrida

171

ANEXO 2. Photographs

Photo 19. Caribbean. Dinoflagellates. Neoceratium lineatum

Photo 20. Caribbean. Dinoflagellates. Scripsiella trochoidea

172

ANEXO 2. Photographs

Study 2. Blanes, NW Mediterranean

173

ANEXO 2. Photographs

Photo 21. Mediterranean. Diatoms. Chaetoceros decipiens and Rhizosolenia setigera

Photo 22. Mediterranean. Diatoms. Chaetoceros dadayi

174

ANEXO 2. Photographs

Photo 23. Mediterranean. Diatoms. Bacteriastrum hyalinum

Photo 24. Mediterranean. Diatoms. Bacteriastrum elongatum

175

ANEXO 2. Photographs

Photo 25. Mediterranean. Diatoms. Asterionellopsis glacialis

Photo 26. Mediterranean. Diatoms. Guinardia flaccida

176

ANEXO 2. Photographs

Photo 27. Mediterranean. Diatoms. Lauderia annulata

Photo 28. Mediterranean. Diatoms. Dactyosoloen mediterraneus and Leptocylindrus danicus

177

ANEXO 2. Photographs

Photo 29. Mediterranean. Diatoms. Guinardia striata

Photo 30. Mediterranean. Dinoflagellates. Dinophysis caudata

178

ANEXO 2. Photographs

Photo 31. Mediterranean. Dinoflagellates. Corytodinium tessellatum

Photo 32. Mediterranean. Chlorophyt. Schroederia setigera

179

ANEXO 2. Photographs

Study 3. Bay of Brest, NE Atlantic

180

ANEXO 2. Photographs

Photo 33. NE Atlantic. SEM detail of a maerl thallus, with epiphytic macroalgae and diatoms

Photo 34. NE Atlantic. Benthic diatom assemblage associated to maerl

181

ANEXO 2. Photographs

Photo 35. NE Atlantic. Benthic diatoms associated to maerl and detritus (note the Coscinodiscus sp. frustule)

Photo 36. NE Atlantic. Benthic diatoms associated to maerl and detritus (note the sponge spicules)

182

ANEXO 2. Photographs

Photo 37. NE Atlantic. Benthic diatoms (Amphora sp.) associated to maerl and detritus (note the sponge spicules)

Photo 38. NE Atlantic. Benthic diatoms (e.g., Amphora sp., Cocconeis scutellum, Melosira nummuloides) associated to maerl

183

ANEXO 2. Photographs

Photo 39. NE Atlantic. Melosira nummuloides on maerl

Photo 40. NE Atlantic. Ampora sp. on maerl

184

ANEXO 2. Photographs

Photo 41. NE Atlantic. Diploneis bomboides on maerl

Photo 42. NE Atlantic. Gyrosigma sp. on maerl

185