Endogenous and environmental factors shaping growth rate variability in bivalves

Endogenous and environmental factors shaping growth rate variability in bivalves Physiological, histological and cellular assessment Maitane Pérez Cebrecos International Ph.D. Thesis - 2024 Faculty of Science and Technology Research Centre for Experimental Marine Biology and Biotechnology Plentzia, September 2024 Endogenous and environmental factors shaping growth rate variability in bivalves Physiological, histological and cellular assessment Maitane Pérez Cebrecos Supervisors: Irrintzi Ibarrola Bellido, Urtzi Izagirre Aramaiona This dissertation is submitted for the degree of Philosophiae Doctor (cc) 2024 Maitane Pérez Cebrecos (by-nc-sa 4.0) The following research work was funded by the University of the Basque Country (UPV/EHU) through the UPV/EHU Research Group grant (GIU21/028). It was also funded by the Basque Government through the Consolidated Research Group grant “Cell Biology in Environmental Toxicology” (CBET group, IT8010-B), and the pre-doctoral and mobility fellowships awarded to Maitane Pérez Cebrecos. ii iii Al que arreglaba paraguas. Al que se escondía en ellos. iv v A veces el destino se parece a una pequeña tempestad de arena que cambia de dirección sin cesar. Tú cambias de rumbo intentando evitarla. Y entonces la tormenta también cambia de dirección, siguiéndote a ti. Tú vuelves a cambiar de rumbo. Y la tormenta vuelve a cambiar de dirección, como antes. Y esto se repite una y otra vez. [...] Y la razón es que la tormenta no es algo que venga de lejos y que no guarde relación contigo. Esta tormenta, en definitiva eres tú. Es algo que se encuentra en tu interior. Lo único que puedes hacer es resignarte, meterte en ella de cabeza, taparte con fuerza los ojos y las orejas para que no se te llenen de arena e ir atravesándola paso a paso. Y en su interior no hay sol, ni luna, ni dirección, a veces ni siquiera existe el tiempo. Allí solo hay una arena blanca y fina, como polvo de huesos, danzando en lo alto del cielo. Imagínate una tormenta como ésta. Y cuando la tormenta de arena haya pasado, tú no comprenderás cómo has logrado cruzarla con vida. ¡No! Ni siquiera estarás seguro de que la tormenta haya cesado de verdad. Pero una cosa sí quedará clara. Y es que la persona que surja de la tormenta no será la misma persona que penetró en ella. Y ahí estriba el significado de la tormenta de arena. Haruki Murakami, Kafka en la orilla It’s easy to forget that questions don’t demand answers. They demand understanding. Patrick Rothfuss, The wise man’s fear vi xiii invisibles bajo el sol en busca de la luna. Nuestros mundos diferentes se entremezclaron y solaparon entre sí sutilmente, como cuando las aguas dulces y saladas se mezclan en la desembocadura de un río con el subir y bajar de la marea. Estos últimos meses habrían sido infinitamente más difíciles sin tu apoyo; me siento agradecida de que hayas sido parte de este último suspiro. Gracias por las conversaciones inspiradoras, las voces suaves, el tomate rallado, el yogur con fruta y miel, la búsqueda del tesoro en las orillas y el suave baile acompañado por la voz de Allen a la luz de la luna. Gracias por hacerme sentir comprendida, por el staccato, por la chispa. Gracias por cantar canciones que solo yo puedo escuchar, por ser el viento que espuma las olas de mi mar. El mar es el destino final del río, donde culmina su viaje y encuentra su descanso. Es la vasta inmensidad que lo acoge, donde sus aguas, después de recorrer montañas, valles y llanuras, se entregan por completo. Para el río, el mar es más que un simple final; es su propósito, el abrazo infinito que lo transforma y lo renueva, dando sentido a su existencia. Eso sois para mi vostros, mi familia. Aitite, Amama, Izeko, eskerrik asko por tener la puerta siempre abierta, por las historias del caserío, por las de Valencia. Grazas tamén aos desa terra na que os carballos e os abedures compiten polo espazo; onde o mar, xeneroso e indómito, desprega a súa forza e o seu misterio. Amama Emilia, grazas por vestir as miñas bromas coa túa risa. Grazas Carlos, Elsa, Leo e Antía, sodes o verán invencible no medio do inverno, sempre estades atentos a min, aínda sen facelovos fácil. Leo, Antía, os meus txikitines, grazas por ser esa terra mollada que cheira a esperanza, a paz inocente que aínda ignora aquelas cousas que fan estremecer a vida. Quérovos moito. Sin embargo, los que más merecen ser agradecidos son los de casa, Ama, Aita y Julen, por aguantarme, por apoyarme. Ama, gracias por enseñarme que uno siempre cuenta con el privilegio de la pausa, por darme el permiso hermoso de frenar. Gracias por enseñarme a que si tenía que hacer algo, debía tomarme mi tiempo y hacerlo bien. Gracias por las horas que pasamos en la ría. Llevo tu luz y tu olor por donde quiera que vaya. Aita, gracias por empeñarte en entender lo que hago, por tu humor, por el brillito de orgullo en tus ojos. Gracias por la intensidad, pese a que nos enfrente. Julen, a ti que iluminas mi camino, tus abrazos son el refugio que necesito cuando el mundo se tambalea. Gracias por tu profundidad, por tu risa contagiosa, tu empatía, tu admiración. Ojalá un día llegues a verte a través de mi mirada. Gracias por ser la estrellita que ilumina mi oscuro cielo. Todo lo que hago, todo, sería imposible sin vosotros. Los recuerdos que compartimos nunca se desvanecerán; como la sal en el mar, son ya parte de nosotros. xiv Acknowledgements Without its tributaries, the river would lack life and purpose. They enrich and stabilise it, preventing it from drying up, overflowing, or losing its way. Similarly, the written piece in your hands would not have the appearance and essence it has without the people I mention below, and I would like to thank them all. I hope I don’t forget anyone. Thanks to those who were and are noise in my silence, to those who are and were silence in my noise. The main contributors to the existence of this project are you, my supervisors, Irrintzi Ibarrola and Urtzi Izagirre. You planted the seed, nurtured the plant, and tended the flower. Thank you both for allowing yourselves to be deceived four years ago when I knocked on your door and you trusted in me. Thank you also for putting up with my extravagant ideas and for showing me the way through this maze. Irrintzi, thank you for the countless hours of data analysis and our many discussions on science and beyond. Thank you for infusing this text with elegance and rigour, always treating it with care and patience. You turn my whims into ideas. Urtzi, thank you for teaching me the importance of a well-crafted experimental design, of double reflections and key questions. Thank you for smoothing my edges and teaching me to pick my battles, for calming my nerves when doubts assailed me. You keep me from falling into the abyss; you are a safe nest on the cliff. A creature does not thrive outside its ecosystem, as it relies on the complex web of interactions and resources it provides. A thesis is no different. Without a supportive research group behind you, it would be really tough, if not impossible, to get through a research project. I would like to start by thanking the group of Energetic Physiology of Bivalve Mollusks at the Faculty of Science, UPV/EHU. Thank you, Iñaki, for your words of encouragement, for showing me that nothing is as important as it seems. Miren, you are a model of strength and resilience. Thank you for the behind-closed-doors conversations, for your understanding, and for your support; I know I can always count on you. Kris, thank you for the coffee-scented breaths, for your constant readiness, and for your persistence. Thank you, also, for bringing Alex into my world. Alex, thank you for the discussions on philosophy, history, and politics. I learn so much just by talking with you. Thank you for taking me seriously, even if sometimes you don’t understand me. I hope Ganeko someday realises how lucky he is to have you both. Xabi, thank you for agreeing to participate in the craziness of my thesis (even though you did not know where you were getting into), without you, the second chapter would not exist. Thank you for sharing endless hours in the lab with me, for the music, the xv walks, and the confidences. You were a small rest in the course of the river, a lake of serene waters where I could find calm. The river is born in the quiet of a spring, where the earth whispers and the water emerges in a delicate sigh. From the depths, hidden beneath the hills, it flows as a current that with each drop caresses the land, marking the beginning of a journey. You have been that spring for me, Dani. Without you, this would not have even started. You have been the architect of much of this thesis, especially the work that is not visible. Thank you for your dedication, your skill, for being that teacher who allows mistakes without judgement, with laughter and infinite patience. You taught me to handle all the machines and gadgets in the lab; and most importantly, to manage without them. If today I am capable of conceiving and executing experiments successfully, it is thanks to you (even if I end up soaked). I will always admire your problem-solving ability, your composure in facing challenges, and your inexhaustible generosity. Thank you for putting up with me, for indulging me, and for your friendship. I would like to thank the Animal Ecotoxicity and Water Quality group for their support, those on the other side of the door. Thank you, Maite and Pilar, for your affection, for perceiving me with a warmth I may not deserve. Maite, thank you for awakening in me a curiosity for birds. Pilar, thank you for your winged alphabet. I especially thank you, Iñigo, for appearing behind that door every morning. Thank you for the navigating conversations, for the endless stream of ideas that intertwine and transform, for teaching me everything I know about cinema. Thank you for introducing me to Sorrentino and for stopping me from opening a bakery in Burgos. Thank you for not needing me to explain my silence, for understanding what is not said. I cannot move forward without first thanking the riverside forest that appeared to embrace the river. Thank you to the wonderful people at the Plentzia Marine Station (Plentziako Itsas Estazioa - PiE, UPV/EHU) and, in particular, to the Cellular Biology in Environmental Toxicology group. I do not know what would have become of me if you had not appeared in the middle of my journey. Thank you, Ibon and Oihane, for being the first drops of the thaw, for giving me the opportunity to take my first steps in research. Thank you especially to you, Oihane, for your constant support and trust. Thanks also to you, Jon, Feli, Carlos, and Lorea, for keeping watch over the castle. Thank you for accepting jokes, for going along with them, and for making life easier for all of us. Lorea, thank you for your kindness in this final stage. Asier, thank you for the excursions to the breakwater and for all the help with the boxes. Only you (and your whistle) witnessed the look on my face when I xvi saw all those empty shells. Jon, I never thought it would be possible to get along with a physicist and, even less, to laugh so much. Thank you for being part of the Friday Tupperware team and for helping us (I think) understand what a moment is. Thanks to you, I have been able to delve into the amazing world of LaTeX; you are the bridge between the observable and the comprehensible. Nerea, Gorri, thank you for being the gentle mist that settles over the river; you have always had kind words for me and you are an example of effort and skill. Manu and Mutri, I thank you both for being the trees that, with their branches extended, bend towards the water like guardians, offering a canopy of shade that refreshes and mitigates the heat of the sun. Manu, if you did not exist, we would have to invent you. Thank you for your closeness, for the banter, for talking to us about everything, and for your generosity. You have made me feel welcome from day one. Mutri, thank you for sharing your experience, for your precision with words, but also for the tons of mussels, for lightening the mood, and for believing in me. Irune, thank you for ensuring the constant flow, for being the vital pulse that sustains the river on its journey. Without you, the river would lose its essence, and life along its banks would fade into silence. Or, to put it another way, what would we do without you? Without our double agent, as Denis would say. Thank you for the laughter, the knowing glances, your brilliance, and your dedication, for taking care of us even when we do not deserve it. Though not always visible, the roots are crucial for stabilising the riverbanks and protecting against erosion. Yes, that’s you, Pamela. Thank you for teaching me to see the world through your eyes, for showing me that there’s another way to do things, for sharing that sense of friendship and teamwork. For speaking openly, for being the mirror in which I like to recognise myself. You’re worth much more than you think, do not forget it. Tif and Tamer, I deeply appreciate your role as elder siblings, always ready to share a coffee and a conversation. Tif, you understand me better than anyone in certain aspects. Thank you for offering solace, for your concern, and for patiently enduring my clumsy attempts at speaking French. You are like a water lily that unfurls patiently from the depths of the river. Tamer, you are the hidden date among the fruit box, an unexpected treasure that brings joy and sweetness to the simplest of moments. Thank you for listening, for understanding, and for the shared uncertainties. We are truly fortunate to have you. Similar to a spring, yet entirely different, rain nourishes the river from a distinct origin, united in its purpose of giving life. Both are murmurs that keep the river vibrant, merging opposing worlds into a shared current. Each raindrop filters into the earth, replenishing hidden aquifers, which, like xvii discreet springs, continue to feed the river when the sky remains clear. You are that rain, Denis. You fell from the sky, ensuring that the waters flowed ceaselessly, even in the times of greatest drought. Thank you for making me laugh, especially when I take life too seriously. Thank you for including me, for considering me, for the samplings, the strandings (even with a skirt), the music, for the laughter, the tears, the hugs. I admire your sense of justice, your insight and intuition, and, of course, your rigorous work, without which much of this thesis would not be what it is. I feel very fortunate to have you close. A braided river is one that refuses to be contained, splitting into a myriad of bright currents that twist and turn, forever intertwining like the strands of a loose braid. In these rivers, the banks and channels are neither rigid nor fixed, but are in a constant state of change, shaped by the relentless flow of water. Flowing with a sense of urgency, braided rivers paint the landscape with their everchanging patterns. Collaborations in science are somewhat like this. I have had the great pleasure and wonderful fortune of spending time at the Cawthron Institute in Nelson, New Zealand. Many thanks to Zoë and Norman, my supervisors there, for welcoming me from the very moment Irrintzi picked up the phone. Thanks to all the staff with whom, to greater or lesser extent, I had the pleasure of working during my stay. Alyssa, Jolene, Carol, Jess, Jordan, Anne, Julien, Petra, Catherine, Cara, Chris, thank you for your professionalism and willingness; without you, I would not have been able to carry out those two seemingly impossible experiments. Tuiana, thank you for showing me that there are things that cannot be taught, for your warmth, for your serenity. I hope no one ever stops us from immersing ourselves in the river. Thanks also to you, Ellie, the seagrass girl, for the knowing laughter and your energy. Thanks, of course, to you, Natalí and Leo, my Chilean friends; not only for the comings and goings but also for your advice and encouragement, with or without beers. Cecilia, thank you for your kindness, for sharing my sense of humour, and for the cathartic moments. Martin and Mena, thank you both for crossing my path. Martin, you were the perfect host when I arrived; by the way, I owe you a breakfast. Mena, the connection was almost instant; thank you for your craziness, for the days we spent in Auckland, for the nonsensical laughter. Ha, do you remember that the initial goal was to talk about our projects? We still need to do that. Evidently, my adventure in the antipodes would not have been the same, not by a long shot, without you, Zoë and Reuben. I believe the three of us together formed a small, well-bonded family. Zoë, thank you for showing me how to be whole in everything I do, for teaching me that I must put all of myself into even the smallest things. Thank you also for your wonderful recipes, the nighttime xviii conversations, the life lessons. When a river changes its course, it not only adapts to the new contours of the land but also opens new paths of beauty and discovery. Zoë, you have changed the way I see the world; thank you for that gift. Reuben, the joy of the house, the sweet tooth, the little elf; thank you for your hugs, for sharing your inner universe with me, for introducing me to the unexpected world of Lego, for making me forget about work. Thank you both for being an indispensable support and for the trips without kitchen utensils. Thanks also to you, Jude and Ash, for your sparkle, warmth, and curiosity; how can humour be so similar even when we come from such distant places? Thanks to all four of you and the rest of the family, for being mine as well. In the river, stones play a role as subtle as it is vital. They are the silent guardians of the current, shapingtheriverbedwiththeirpresenceandcreatingenchantedhavensforaquaticlife. Bydisrupting the flow of water, the stones create a mosaic of swift and serene currents, where small creatures find their home. Ainara, you have always been that steadfast and stable rock. Thank you for being there, unconditionally, and I apologise for letting this thesis steal so much of our time. Not everyone reaches out when they’re hidden away, and you always manage to find me, even when I’m far away. The way to truly get to know each other is by sharing things that seem irrelevant, letting words flow freely and irresponsibly until we venture into risky territories. That’s how we got to know each other, Eneko. We have always danced with great care, not knowing exactly what music the other was listening to, not even sure if the other was dancing at all. Yet, we have shared so much. Thank you for enduring my thoughts on mussel shells, for the walks to the dam, and for always being there whenever I asked. I’m glad you took my advice to start a thesis. Itsaso, Maider, Iria, and Itxaso, the little blossoms of colour and joy that adorn the river. Itsaso, you are like the water crowfoot, the wise and silent one, whose white flowers float with a serenity that calms the waters, like a mentor guiding with patience and understanding. Thank you for your overwhelming insight and intelligence; you are the ray of sunshine peeking through the clouds. Maider, you are the lobelia, the inspiring visionary, with your vibrant and colourful flowers radiating energy and creativity. You have always been my hope and daily companion for years—thank you for Biolum, for the laughter, and for the trust; Amsterdam will always be our special memory. Iria, you are the water plantain, offering a delicate refuge and sustenance to those dwelling by the river with your heart-shaped leaves and floral spikes. You are the mother who watches over us but also knows when to be firm; your innocence is wonderful, and I would choose you again and again. Itxaso, you are the fireweed, in purple of course, bringing warmth and luminosity, shining even in the most xix adverse conditions. Thank you for sharing my silliness, for your strength, and for your steadfastness. Together, we make the most irredeemably hilarious cynical duo that can exist. Thank you for letting me be me. The four of us together share memories that will never leave our bones; like salt in the sea; they became part of us. Life is complicated, but when you have breakfast with your friends, talk about books and movies, share your anxieties, and although they don’t disappear, the world seems much kinder afterwards. Nagore, Mar, thank you for getting up early to have breakfast together. If I had to choose one thing to take away from this process, it would undoubtedly be you. You can wrap me in your gaze during my silences and defend me with a smile against my words. Thank you for showing me new ways of thinking and new perspectives on life. You are the best team I could have chosen. Mar, thank you for your wit, your sweetness, and your laughter that fills the room. It was a true pleasure discovering the secret of mussel larvae with you. Your attention and encouragement have been essential on more than one occasion. Thank you for being the invincible smile behind my tears, the unceasing calm amidst the chaos. The thesis will only be your beginning; I’m convinced a bright future awaits you. Nagore, I don’t know where to start, so I’ll simply say that we were fortunate when fate decided to bring us together, just when we were ready for it. Meeting you was like feeling a warm breeze under the shade of a tree in the middle of the summer. Thank you for everything —thank you for the connection, for being so unintentionally funny, for the harmony, and your honesty. You are my touchstone. Your judgement and excellent work will surely be reflected in your thesis. You know the steps, now dance it out. Having you both makes me happy because no matter how hard the world pushes against me, I know you’ll always be pushing back. It would not be fair or elegant to forget you, Nico, at this point. Thank you for your calmness, your perspective, and for being such a fan as I am of books and movies where “nothing happens”. After we all get together with a glass of wine or some IPAs, sitting by the riverbank, I walk away and return home with a small glowing ball of golden, radiant light in my chest. Hearing your laughter and support feels like wrapping yourself in a soft, dry, and warm towel after a cold bath in the river. Thank you, and thank you a thousand times over. Milan Kundera once suggested that perhaps a man and a woman find their closest connection simply in knowing the other exists. They are grateful for that existence and the knowledge of one another. In this simple awareness, they find happiness. I am grateful, laztana, I am grateful that you exist. Just that. Thank you for being the dragon who led me to its haven, guiding me with invisible wings xx beneath the sun in search of the moon. Our different worlds intertwined and overlapped subtly, like when fresh and saltwater blend at the mouth of a river with the rise and fall of the tide. These past months would have been immeasurably harder without your support; I am grateful that you were part of this final sigh. Thank you for the inspiring conversations, the soft voices, the grated tomato, the yogurt with fruit and honey, the treasure hunt along the shore, and the gentle dance to Allen’s voice in the moonlight. Thank you for making me feel understood, for the staccato, for the spark. Thank you for singing songs that only I can hear, for being the wind that froths the waves of my sea. The sea is the river’s final destination, the place where its journey culminates and it finds peace. It is the vast expanse that welcomes it, where its waters, after winding through mountains, valleys, and plains, surrender wholly. For the river, the sea is more than just an end; it is its purpose, the immense embrace that transforms and renews it, turning its long journey into something far greater and eternal. It gives meaning to its existence. Just as you, my family, do for me. Aitite, Amama, Izeko, thank you for keeping your door always open, for the stories of the farmhouse, for those of Valencia. My gratitude also extends to those on the land where oaks and alders vie for space, where the sea, generous and untamed, reveals its strength and mystery. Amama Emilia, thank you for adorning my jokes with your laughter. Thank you, Carlos, Elsa, Leo, and Antía, for being the unshakeable summer in the middle of winter. You’re always there for me, even when it’s not easy. Leo and Antía, my little ones, thank you for being that moist earth that smells of hope, that innocent peace still untouched by life’s harsher realities. I love you very much. But the ones who deserve the most thanks are those at home: Ama, Aita, and Julen, for putting up with me and supporting me. Ama, thank you for showing me the value of taking a pause, for giving me the beautiful gift of slowing down. Thank you for teaching me that if something needs to be done, it’s worth taking my time to do it right. I cherish the hours we spent by the estuary. Your light and scent go with me wherever I go. Aita, thank you for making the effort to understand what I do, for your humour, and for the pride that shines in your eyes. Thank you for your intensity, even when it challenges us. Julen, you light up my path, and your hugs are the refuge I need when the world feels shaky. Thank you for your depth, your infectious laughter, your empathy, and your admiration. I hope one day you see yourself through my eyes. Thank you for being the little star that brightens my darkest nights. Everything I do would be impossible without you. The memories we have made will never fade; like salt in the sea, they have become a part of us. xxi Contents General introduction 1 1 Bivalve lifestyle .................................... 2 2 Habitat differences in bivalve populations .................... 4 2.1 Environmental conditioning . . . . . . . . . . . . . . . . . . . . . . . . . 5 3 Organs involved in food acquisition and processing .............. 8 3.1 Thegill .................................... 8 3.1.1 Gill anatomy, histology and particle retention efficiency . . . . 8 3.1.2 Physiological parameters concerning the gill and their plasticity 10 3.2 Anatomy and histology of the digestive gland . . . . . . . . . . . . . . . . 12 4 Organs involved in energy usage and storage: mantle and gonad ....... 14 5 Energetic physiology and growth ......................... 17 5.1 Explanatory models for inter-individual growth-rate variability . . . . . 17 6 Factors affecting the capacity for energy acquisition .............. 19 6.1 Inter-individual differences in the filtering capacity . . . . . . . . . . . . 19 6.2 Inter-individual differences in digestive capacity . . . . . . . . . . . . . . 20 7 Factors affecting the energy expenditure ..................... 22 7.1 Standard metabolic rate . . . . . . . . . . . . . . . . . . . . . . . . . . . 22 7.2 Routinemetabolicrate............................ 23 7.3 Factors affecting the metabolic rate . . . . . . . . . . . . . . . . . . . . . 23 7.3.1 Body size. Allometry . . . . . . . . . . . . . . . . . . . . . . . 23 7.3.2 Physiological status . . . . . . . . . . . . . . . . . . . . . . . . 25 7.3.3 Genotype ............................. 26 7.3.4 Fatty acid composition and ROS production . . . . . . . . . . 27 Hypothesis and objectives 61 Hypothesis ...................................... 62 Objectives ....................................... 62 Chapter 1 63 1 Introduction ..................................... 65 2 Materials and methods ............................... 67 2.1 Collection of mussel seeds and experimental setup . . . . . . . . . . . . . 67 2.2 Biometry ................................... 68 General introduction 3 instance, bivalves are highly efficient at retaining phytoplankton and small organic detritus but less so with very fine particulate matter. Once captured, the particles are sorted and directed towards the mouth by the labial palps, an organ that takes part in rejecting unsuitable particles that will be expelled as pseudofaeces. The ability to sort and differentiate between particles is referred to as selection efficiency. These structures are covered with ciliated grooves and ridges that transport and sort particles based on size, shape, surface properties and possibly chemical composition (Beninger and St-Jean, 1997; Ward and Shumway, 2004). Desirable particles are moved towards the mouth, while undesirable ones are bound in mucus and expelled as pseudofeces. Labial palps can distinguish between nutritious particles (e.g., phytoplankton, organic detritus) and non-nutritious or harmful ones (e.g., silt, sand, debris). Edible particles are directed into the digestive system, where they are broken down and absorbed. The oesophagus is in charge of transporting food from the mouth to the stomach, necessary for mechanical and enzymatic digestion to begin. The stomach is also where the digestive enzymes secreted by the digestive gland are first activated and begin the breakdown of food particles into simpler molecules. The digestive gland consists of lobes located around the stomach connected by ducts that serves not only in the secretion of enzymes that facilitate extracellular digestion, but also is the primary site for nutrient absorption. Intracellular digestion also happens within the cells of digestive gland, further breaking down food particles that have been absorbed into these cells. The intestine extends from the stomach, often looping through the body before ending at the anus near the exhalant siphon. The lining of the intestine absorbs remaining nutrients, which are then transported into the circulatory system of bivalves. Moreover, the undigested material and waste is compacted in the intestine, which will be eventually expelled from the body. Consequently, the stomach, digestive gland and intestine are intricately connected, forming a highly efficient system for digestion and absorption. Efficient feeding and nutrient absorption are crucial for supporting both somatic (soft-tissue and shell) and reproductive (gonad) growth. The energy and nutrients obtained from feeding are shared between maintenance, growth and reproduction. For instance, nutrients can be used to produce and maintain soft tissues, including the mantle, gills, and muscles. The mantle tissue, in particular, plays an essential role in growth as it secretes the organic matrix components and carries out the deposition of calcium carbonate layers, aiding in overall body enlargement. Shell growth occurs at the margins of the mantle and is regulated by the availability of calcium and carbonate ions, as well as environmental factors. The mantle tissue is also fundamental in supporting gametogenesis as they are both closely interconnected and critical to the growth, reproduction and overall survival of the bivalves. Gonads are embedded within the mantle tissue 4 General introduction or closely associated with it, consisting of follicles where gamete development occurs. During periods of high food availability, bivalves can allocate sufficient nutrients and energy to both somatic and reproductive growth. In contrast, during periods of low food availability or environmental stress, bivalves may prioritise one type of growth over the other, often favouring survival (somatic maintenance) over reproduction. Hence, bivalves usually exhibit seasonal growth patterns, with somatic growth occurring during periods of high food availability and gonad development peaking before spawning seasons. After spawning, a period of somatic recovery usually follows, where energy is directed back to tissue and shell growth. A strong, well-maintained shell reduces the risk of predation and environmental damage, indirectly supporting reproductive success ensuring a safe environment for gametogenesis. The correlation between feeding efficiency, energy intake, and growth capacity underscores the development of growth phenotypes in bivalves. Efficient feeding mechanisms allow for greater energy intake, which directly supports growth and reproductive capacity. This intricate relationship between feeding processes and energy dynamics provides a foundational understanding of the ecological and physiological factors driving growth phenotypes in bivalves. 2 Habitat differences in bivalve populations Descendant individuals of the same spawning event, such as mussels or oysters, can end up inhabiting either the subtidal zone or different zones along the intertidal. This vertical zonation of the bivalve communities is especially relevant not only due to the different set of fluctuations and subsequent challenges that each zone subdues the animals to; but also, because, as long as they are sessile, they cannot move to evade the environmental stresses. Bivalves have been proven to display a wide range of compensatory physiological mechanisms that allow them to preserve the biological activity and growth in such a variable environment (Thompson and Bayne, 1974; Okumus and Stirling, 1994; Navarro et al., 1994; Pernet et al., 2007). In other words, bivalves possess a high level of physiological plasticity that results in a complex behaviour when dealing with the environmental fluctuations, which makes it interesting to test the development of fast and slow growing individuals under these conditions. The subtidal zone encompasses a wide range of depths, from the shallow subtidal areas near the low tide mark to deep-sea trenches and abyssal plains. The subtidal habitat is characterized by stable environmental conditions, including relatively constant temperature, salinity and water availability (Bertness et al., 1999). Water movement, driven by tides, currents and waves is a prominent feature of subtidal habitats (Bird et al., 2017), which influence nutrient availability, sediment transport and larval dispersal, shaping community structure and ecosystem dynamics (Denny et al., 2003; Thrush et al., 2008). General introduction 5 Bivalves living in intertidal regions are frequently exposed to large changes in their physical environment. Those environmental challenges, in addition, are often more pronounced and severe the upper in the intertidal. In fact, at increasingly higher levels on the shore, marine organisms will be experiencing increasingly longer periods of time spent in air, i.e., emersion. The shift between immersion and emersion is tough for bivalves, as seawater and air have very unalike, often contrary characteristics (Dejours, 1989). Therefore, animals exposed to long emersion times are exposed to desiccation stress, extreme temperatures, UV radiation and face difficulties with nitrogenous waste excretion (Nybakken, 1993; Moyle and Cech, 1996; Raffaelli and Hawkins, 1999; Wright and Turko, 2016). Furthermore, intertidal animals also frequently experience diel hypoxia (Richards, 2011; Schulte, 2022) and, in rocky intertidal zones, animals are also exposed to physical stress from wave action and/or ice disturbance (Raffaelli and Hawkins 1999). Moreover, due to the filter-feeding nature of bivalves, frequent emersion limits the time they have for feeding, which can reduce the amount of energy available for growth and reproduction (Bayne et al., 1988) that condition in turn the digestive cycles (Izagirre et al., 2008). 2.1 Environmental conditioning Subtidal environments are consistently submerged beneath the low tide mark, with minimal exposure to air. As a result, desiccation is not a direct concern for subtidal organisms, but it sure is for intertidal bivalves, due to the exposure to air during low tide. The most common adaptation of high intertidal animals against desiccation is avoiding water loss or reducing water loss rate when emerged (Leeuwis and Gamperl, 2022) by minimising the exposed surfaces, which is materialised as tightly closing their shells (Denny and Gaines, 2007; Gleason et al., 2017). Bivalves in the high intertidal zone experience, in general, much higher temperatures than those in the low intertidal or subtidal zones, both on a diurnal and seasonal basis (Petes et al., 2008; Fangue et al., 2011; Richards, 2011; Gleason et al., 2017; Monaco et al., 2017; Stickle et al., 2017). In fact, several physiological and biochemical mechanisms provide them with higher heat tolerance. For instance, some high intertidal molluscs have developed a higher temperature of cardiac failure (Dong and Williams, 2011) with a higher heat stability of the metabolic enzymes than their low intertidal relatives, driven by both phenotypic plasticity and evolution (Dong and Somero, 2009; Liao et al. 2021). Cooperatively, heat shock protein (Hsp) expression levels rise at the onset of cellular heat stress (Fangue et al., 2011). Hsp-s perform chaperon functions by stabilising other proteins, being not only thermoprotective during heat exposure in high intertidal organisms, but also being used as a preparative defence against stress (Roberts et al., 1997; Halpin et al., 2004; Gracey et al., 2008). This latter strategy involves the maintenance of high constitutive Hsp levels (Nakano and Iwama, 2002; Dong et al., 2008), which likely requires the allocation of energy (Hawkins, 1985; Houlihan, 1991), although the associated metabolic cost is likely outweighed by the benefits (Tomanek, 2010). 6 General introduction Compared to what is known about heat resilience-related adaptations in intertidal animals, information regarding the drivers of patterns of freezing tolerance is still limited. The freezing of body fluids is risky because ice crystals cause physical damage to delicate cell structures, and ice crystal growth leads to desiccation by removing intracellular water (Denny and Gaines, 2007). The compensating mechanisms in different mussel species comprise the deposition of ice-nucleating proteins in the extracellular space (Lundheim, 1997; Denny and Gaines, 2007), the accumulation of compatible organic osmolytes inside the cell (Storey, 1997) and even a gill-associated bacterium that serves as an ice-nucleating agent (Loomis and Zinser, 2001). Hypoxia can affect both intertidal and subtidal environments, albeit in different ways due to their distinct characteristics. In deeper subtidal habitats, bivalves may experience prolonged exposure to low oxygen concentrations (Espinosa et al., 2010). However, in the high tidal zone oxygen levels drop to values near zero during low tide, making animals to experience hypoxemia (i.e., internal hypoxia) when emerged, as a result of the collapse of the respiratory structures (Raffaelli and Hawkins, 1999; Wolcott and Wolcott, 2001; Turko et al., 2014). Therefore, intertidal bivalves are much more used to face hypoxia than subtidal ones. Relying on anaerobiosis to survive emersion is a major strategy in bivalves (Segura et al., 2015), even for those species that rely on gaping to enhance their aerial oxygen uptake (Bayne et al., 1976; Widdows and Shick, 1985; Zippay and Helmuth, 2012), as the retained oxygen is depleted within minutes once in emersion (Bayne et al., 1976; Zippay and Helmuth, 2012). Furthermore, there is also a trade-off between opening the shells to avoid hypoxia and closing them to avoid desiccation (Nicastro et al., 2010). The increased anaerobic ability is usual and persistent (Connor and Gracey, 2012; Gracey and Connor, 2016), and it might be achieved by being able to accumulate comparatively more anaerobic products (Gleason et al., 2017) or by increasing the amount of anaerobic fuel sources (Sokolova and Pörtner, 2001a). The disadvantage of this anaerobic strategy is that an oxygen debt must be repaid during re-immersion to allow for the aerobic processing of anaerobic end products, as seen in several bivalve species (Bayne et al., 1976; Widdows and Shick, 1985; Zippay and Helmuth, 2012). Precisely to avoid the oxygen debt, intertidal animals appear to use the strategy of metabolic depression to the greatest extent (e.g., Marshall and McQuaid, 1992; Sokolova and Pörtner, 2001a). In Mytilids this metabolic depression has been linked to bradycardia (Connor and Gracey, 2012; Curtis et al., 2000), which would reduce the oxygen requirements of the heart and the whole organism. Downregulation of overall protein synthesis, ion transport and lower enzyme activities (permanent or temporary) have also been observed in high intertidal animals (Storey and Storey, 1990; Panova and Johannesson, 2004; Sokolova and Pörtner, 2001b; Greenway and Storey, 2001; Ivanina et al., 2016), which might facilitate metabolic depression by reducing the energy demands. Another challengeforthe intertidalindividuals arethe broadfluctuations insalinity, which subtidalindividuals General introduction 7 do not face. The first coping mechanism relating to salinity challenges is behavioural, focusing on seeking shelter in a more favourable microhabitat, or reducing the amount of exposed surface-area (Segura et al., 2015), similar to behavioural defences against desiccation. Physiological mechanisms used to confront salinity stress involve regulating cellular volume by accumulating or catabolising intracellular organic osmolytes (Yancey, 2005). By contrast, changes in UV radiation levels affect both subtidal and intertidal habitats, although the intertidal zone still experiences more UV radiation (Peterson, 1991; Shick and Dunlap, 2002). Adaptations that are particular or unique to this type of stressor include the use of UV-absorptive pigments in the skin and mucus, and antioxidants that quench and deactivate reactive oxygen species (ROS) (Cockell and Knowland, 1999; Shick and Dunlap, 2002). Because of the breaking waves that are formed at the sea-to-land transition, animals in the intertidal zone experience considerably more wave action than those in the subtidal. However, wave action is not necessarily stressful and can even be beneficial, as it helps with the supply of oxygen and nutrients, in warmer climates offers some cooling, and certain predators (e.g., Carcinus maenas) may also be less abundant (e.g., Kitching et al., 1966; Hughes and Elner, 1979; Gibbs, 1993). Still, being swept away from the substrate by waves can have severe consequences: increasing vulnerability to subtidal predation or causing physical damage (Denny and Gaines, 2007). To avoid it, intertidal animals use several strategies to strongly adhere to the substrate: for example, by secreting byssus threads (Denny and Gaines, 2007). Conversely, subtidal individuals are subject to hydrodynamic forces such as currents, which can influence feeding efficiency, attachment strength and habitat suitability (Thrush et al., 2008). Predation can influence bivalve population dynamics, community structure, and ecosystem stability (Beck et al., 2011). The predation pressure in subtidal compared to intertidal habitats can vary based on a number of factors including predator species, habitat complexity and environmental conditions. However, the subtidal zone is an area with typically higher diversity and abundance of predators: sea stars, crabs, fish and drilling gastropods are more common and active in the subtidal, and can exert significant predation pressure on the bivalves inhabiting it (Freeman, 2007). In fact, predation pressure has been reported to be significantly more consistent and higher in subtidal zones due to the presence of a diverse predator assemblage and the stable environment that allows predators to be constantly active, leading to sustained predation pressure (Seed and Suchanek, 1992; Gosling, 2003). Disease outbreaks and parasite infestations can cause mortality, reduce reproductive output, and weaken bivalve populations (Lafferty et al., 2015). The prevalence of parasites in subtidal compared to intertidal individuals can vary depending on the environmental conditions, predator-prey interactions, and host physiology. Subtidal zones offer more stable environmental conditions, which may favour the survival and proliferation of certain parasite species. Actually, subtidal bivalves are susceptible to various diseases and 8 General introduction parasitic infections, including bacterial pathogens, protozoans, and parasitic flatworms (Cheng et al., 2016). In addition, the subtidal generally supports higher biomass and diversity of potential hosts, providing more opportunities for parasites to complete their life cycles (Poulin and Mouritsen, 2006). Concurrently, intertidal zones experience greater environmental fluctuations as mentioned above, which impose physiological stress not only on hosts but also on parasites. In the mussel Perna canaliculus a higher prevalence and intensity of infection by trematode parasites was found in the subtidal mussel population when compared to the intertidal population (Koprivnikar et al., 2010). In Mytilus edulis, however, it has been found that while some parasites were more prevalent in subtidal populations, others showed no significant difference between tidal zones (Bollache and Kopp, 2007). 3 Organs involved in food acquisition and processing 3.1 The gill 3.1.1 Gill anatomy, histology and particle retention efficiency Bivalves are filtering organisms and so the food acquisition process is borne by the gill and labial palps. The gill or ctenidia are found in the pallial cavity and consist of four pairs of demibranches formed by descending and ascending lamellae, suspended on each side of the body from a ctenidial axis. The ascending lamellae fuse to the mantle and visceral mass by ciliary or tissue unions. The plication of the lamellae to form large, vertically aligned aggregations of filaments is usually how the ctenidia achieve an overall increase in the surface area. In both mussels and oysters, the gill does not overtly function as an organ of selection (this function being much more the responsibility of the palps), and all currents are directed orally (Morton, 1983). However, the oyster gill is folded (“plicate”) and the folds contain three different types of filaments (ordinary, transitional and principal) (Yonge, 1926), so the gill is said to be heterohabdic (different shaped and sized gill filaments). These different filament types have a discrete division of tasks. The sides and crests of the plicae possess dorsally beating short cilia and ventrally beating long cilia, thus an inherent sorting mechanism is still present in the gills. Large particles are ventrally passed on the crests of the plicae to the marginal food grooves, which can close by apposition to all but the smallest materials, so that large particles may drop off onto the mantle for discharge as pseudofaeces (see Bayne, 2017 for review). In fact, particle selection by the ctenidia of two oyster species including Magallana gigas has been demonstrated (Ward et al., 1994b; Ward et al., 1998 a ). Nevertheless, histological studies and observations of surgically altered specimens suggest that the labial palps are important organs of particle selection in most bivalve species (Kellogg, 1915; Menzel, 1955; Nelson, General introduction 9 1960; Galtsoff, 1964; Jørgensen, 1966; Morton, 1969), including those species that utilize the ctenidium for particle selection (Ward et al., 1994b, 1998a). In Mytilacea, the ctenidia are homorhabdic (identical gill filaments) and non-plicate. All intercepted material is transported to the ventral groove in a homogeneous, intermediate viscosity mixture of mucopolisacarids, such that there is no distinction between the tasks of ingestion (feeding) and rejection (cleaning). In this case, ctenidia show a progressive loss of their selective function, except for the primary sorting that happens in the ventral marginal food grooves. The material is transferred, unusually, from the ventral marginal groove of the outer demibranch to that of the inner (Fankboner, 1971; Morton, 1983), being the gill ciliation almost wholly ventrally directed. Regardless of these specific details, it is clear that the sorting function primitively possessed by the gill is now the function of the labial palps, with a clear trend away from large, plicate ctenidia of more primitive bivalve lineages towards smaller, simpler ctenidia. The role of the gill cilia has been extensively studied (e.g., Ward et al., 1998; Riisgård and Larsen, 2010). According to the current view, the beating lateral cilia serve as the pump on the gill filaments (Bayne, 2017), a phenomenon that has been directly evidenced by Seo et al., (2014) in Mytilus galloprovincialis. These cilia are present along the sides of the filaments, creating currents that pull water into the pallial cavity, drive it through the interfilamentar spaces of the ctenidia, and out of the exhalant siphon or aperture (Rosa et al., 2018). They occur at intervals of between 2 to 3 µm and project outwards to dorm a stiff grid between filaments. They beat at right angles to the long axis of the filament, so that the particles they sieve are flicked onto the frontal cilia (Owen, 1974; Huges, 1975). Frontal cilia are present on the incurrent-facing surface of the filaments, which are responsible for creating surface currents and carrying the particles embedded in mucus to the ventral margins of the ctenidia (Rosa et al., 2018). However, the particles entering the pallial cavity are either directly intercepted by the frontal surface of the filaments or trapped by currents created by the laterofrontal cilia/cirri and then directed onto the frontal surface. As a general rule, each laterofrontal cirri arises from a single cell and consists of cilia arranged in two parallel rows, the number of cilia comprising each cirrus being a species-specific trait. In fact, mussels have a filibranchiate homorhabdic ctenidium with large compound laterofrontal cirri that could account for the reported high capture efficiency of particles in the 4 to 10 µm size range (Rosa et al., 2015). On the other hand, oysters have a pseudolamellibranchiate heterorhabdic ctenidium with developed laterofrontal cirri that are less complex than those of mytilids (Owen and McCrae, 1976; Ribelin and Collier, 1977), but generally have higher capture efficiency for particles greater than 3 µm than mussels. In Mytilidae, the so-called protolaterofrontal cilia occur between the frontal and laterofrontal cilia, smaller cilia closely packed in two alternating rows (Owen, 1978). In Ostreidae, Atkins (1938) described subsidiary paralaterofrontal cilia between the frontal and laterofrontal cilia, which have been proved to be essentially equal to the protolaterofrontal cilia of Mytilidae (Owen, 1978). The general appearance of a gill filament has been pictured in Fig. 1. 10 General introduction Lateral cilia Eu-latero-frontal cilia Latero-frontal cilia Frontal cilia Mucocyte cell Figure 1. General appearance of a gill filament in bivalves. Adapted from Owen and McCrae (1976). In spite of the hesitancy of MacGinitie (1941, 1945), Foster-Smith (1975), Vahl (1973) and Jørgensen (1975, 1976, 1981), that postulated mucus sheet to be the primary screen for particles, it seems evident now that the ciliary arrangement of the ctenidial filaments is the effective filter of the particles suspended in the water column. Although this may be aided by mucus secretion to make particles sticky (Tammes and Dral, 1955; Dral, 1967). It should be noted that the retaining efficiency of the particles in the gill depends largely on the size of the particles themselves. In general, capture efficiency increases non-linearly with increasing particle size to a maximum. Avoiding inter-specific differences, it is accepted that overall the retaining efficiency of the gill is close to 100 % when particles are larger than 3 µm in diameter, but it can cut down to values around 50 % in smaller sized particles (Mølenberg and Riisgård, 1978; Stuart and Klumpp, 1984; Riisgård, 1988; De Villiers and Allanson, 1988). Besides particle size, qualitative factors can also influence particle capture in the gills. For instance, equally sized particles of yet different chemical composition have been shown to be differently retained in experiments performed with oysters (Ostrea edulis) (Shumway et al., 1985), mussels (M. edulis) (Newell et al., 1989) and scallops (Placopecten magellanicus) (Lesser et al., 1991). 3.1.2 Physiological parameters concerning the gill and their plasticity The analysis of the activity carried out by the gill in the food particle acquisition is done by the determination of a series of parameters that are shown next. The clearance rate (CR: L·h -1 ) is the traditionally used parameter that describes the speed at which bivalves filter the water to acquire food particles from it. The clearance General introduction 11 rate is defined as the water volume that is totally particle-cleared per unit of time. The filtration rate (FR: mg·h -1 ) represents the total mass of retained or filtered particles in the gill per unit of time, and it is obtained as the result of the clearance rate and the concentration of the matter in suspension, provided that the retaining efficiency percentage of the particles in suspension reaches the 100 %. The rejection rate (RR: mg·h -1 ) represents the total mass of particles rejected in the form of pseudofaeces per unit of time. The quantity of ingested particles per unit of time or ingestion rate (IR: mg·h -1 ) is obtained out of the difference between filtration rate and rejection rate. In the absence of food rejection in the form of pseudofaeces, the filtration and ingestion rates are equal. As a rule, it has been observed that pre-ingestion processes of bivalves display an outstanding physiological plasticity that allows these organisms to adjust the clearance and rejection rates to the constant fluctuations of the diet characteristics or water temperature. The characteristics of the particulate matter in suspension, essentially the concentration and quality of organic percentage of it, exert a decisive effect upon the clearance rate of bivalves. On many occasions, under laboratory or natural conditions, it has been observed the existence of an inverse relationship between particle concentration and clearance rate (Winter, 1973, 1978; FosterSmith, 1975; Bayne and Newell, 1983; Galimany et al., 2011; Tamayo et al., 2016; Kang et al., 2016; Prieto et al., 2018). This reduction in clearance rate has been interpreted as a regulation mechanism of ingestion rate, the main virtue of which is probably to keep the gut passage time of food in adequate values to maintain high levels of absorption efficiency. The effect of the ration or the particle concentration depends largely on the quality or proportion of organic matter in the diet. Navarro et al., (1994) analysed the variation of the clearance and ingestion rates in the cockle Cerastoderma edule subdued to changes in the quality and concentration of food. They observed that the higher the quality of the diet, the higher the reduction in clearance rate that happened when increasing the food ration. In a later study, Navarro et al., (1996) determined the clearance rate of the mussel M. galloprovincialis fed with similar food rations of 5 diets with different organic contents (from 16 to 91 %) and observed a rise in clearance rate as the organic percentage of the diet declined to values of around 30 %, although the reduction in organic content to even lower values (from 30 to 16 %) gave rise to the opposite phenomenon, reducing the clearance rates. According to the authors, the interaction between quantity and quality of food upon the clearance rate is explained by the selection process and pre-ingestion rejection performed by the labial palps. The selection efficiency of the labial palps is highly dependent on the quality of the food in suspension (Iglesias et al., 1992; Urrutia et al., 1996; Hawkins et al., 1996). Under high quality diets, when the organic content of the diet is high, the pre-ingestion selection efficiency of the particles is limited, in such a way that the adjustment of the ingestion rate is done by modulating the clearance rate (Widdows et al., 1979; Bayne et al., 1989). 12 General introduction 3.2 Anatomy and histology of the digestive gland The bivalve alimentary system consists of a relatively short, flattened oesophagus opening into a complex stomach (Morton, 1983). The oesophagus is composed of a ciliated coverage epithelium interspersed with mucocytes that secrete acid and neutral mucopolysaccharides, even when the animal is not eating (Beninger and Le Pennec, 1991). The function of the oesophagus is not to digest but to transport the particles to the stomach. The crystalline style is projected from the back end of the stomach along it against the gastric shield. The ingested particles are mixed with the digestion enzymes released from the crystalline style (Gosling, 2008). From the stomach arise a number of openings into the digestive gland, the organ of absorption and intracellular digestion. The digestive diverticula comprise a series of blind-ending tubules (digestive alveoli) that communicate with the stomach via a system of ducts (Fig. 2). Inside the secondary ducts the flow is constant and bidirectional (Fig. 2): the particles go through the ducts and the alveoli to be digested and absorbed, while the wastes are expelled to the stomach and intestines. Digestive alveoli Non-ciliated secondary ducts Ciliated primary ducts Stomach Digestive alveoli Secondary ducts Excretory sphereExhalant duct Inhalant duct Free particles Main duct Figure 2. On the left, duct system of the digestive gland of bivalves. On the right, cross-section of the digestive gland of bivalves showing the absorption and intracellular digestion. Adapted from Owen (1955). The extracellular digestion of the food begins within the stomach but is not limited to it: the epithelial cells of the digestive ducts, the basophilic cells of the digestive tubules and the lining of the mid-gut also secrete enzymes into the lumen (Mathers, 1973; Palmer, 1979; Henry et al., 1991; Ibarrola et al., 2000). Absorption happens mainly in the digestive tubules (Fig. 3), although it also occurs in the stomach and mid-gut. The epithelium of the digestive alveoli are comprised of two cell types: digestive cells and basophiles (Morton, 1983)(Fig. 4). Duringnormal feedinganddigestion, thedigestivecellsarethe most abundantones(Marigómez et al., 1990; Zaldibar et al., 2008), columnar cells with a well-developed endolysosomal system that carry out General introduction 19 Metabolic efficiency model. The metabolic efficiency model holds that the differences in growth rate between individuals are based on the difference in the energy costs per unit of growth. In other words, in the efficiency of the energy investment in the synthesis process of new tissues. Less costs of growth in the individuals with higher growth rates have been described in an ample amount of studies (Toro and Vergara, 1998; Garton et al., 1984; Bayne and Hawkins, 1997; Bayne et al., 1999; Bayne 1999; 2000; Pace et al., 2006; Tamayo et al., 2011, 2013, 2014; Prieto et al., 2018, 2020). In addition, in most of these studies, the differences in growth costs are accompanied by differences related to energy acquisition capacity (acquisition model). Notwithstanding the above, and despite the studies focused on the characterization of the physiological basis responsible for the inter-individual differences in the growth rate of bivalves, there is still no agreement around the physiological causes of such variability. As it can be appreciated by the literature aforementioned, the use of different populations along with the heterogeneity of experimental designs might be the reason for the differences in the relative contribution that diverse authors have assigned to the physiological processes in the determination of the intraspecific differences in growth rate. Recently, in the series of experiments run by Prieto et al., (2018, 2019, 2020a,b) with M. galloprovincialis it has been shown that the differential energy balance between individuals selected under different nutritional conditions are higher and less dependant on the characteristics of the experimental diet in fast growing individuals than in slow growing mussels. The hypothesis that different experimental conditions may alter the physiological basis upon which the differential growth is sustained was also proved to be true, at least for different food availability and water temperature. Such a verification allows to indicate that the differences in growth rate do not obey to differences in just one physiological process, but to multiple physiological traits, the contribution of which to the promotion of inter-individual differences in growth rate depends upon the environmental characteristics in which individuals grow. From the experiments testing the different food availabilities, the authors defined what might be interpreted as two basic phenotypes of fast growing individuals in the mussel: i) those that display a higher innate capacity to acquire and process food – fast feeders, and ii) those that show a higher capacity to reduce the basal metabolic costs, which allows them to spend less energy in starvation periods – energy savers. Moreover, these two phenotypes are easily interchanged depending on the experimental conditions. 6 Factors affecting the capacity for energy acquisition 6.1 Inter-individual differences in the filtering capacity In mussels, differencesin inter-individualgrowthrates canbeachievedbya highercapacity ofsomeindividuals to acquire and process food, without resulting on either lower absorption efficiencies or higher metabolic rates (Prieto et al., 2018). However, the causes promoting such endogenous differences are not clear. Tamayo et al., (2011) and Prieto et al., (2018, 2020) found a close relationship between clearance rate and gill-surface 20 General introduction area in clams and mussels, respectively: individuals that were able to develop higher filtering rates were also the ones displaying larger gill-surface areas. Gill surface-area has been found to modulate according to exogenous factors, such as particle availability, composition and feeding time (Theisen, 1977; Essink et al., 1989; Franz, 1993; Payne et al., 1995; Honkoop, 2003; Dutertre et al., 2007; Prieto et al., 2018). This indicates that gill surface-area is submitted to a considerable phenotypic plasticity. Moreover, both inter-specific (Ibarrola et al., 2012) and size related intra-specific allometric-scaling differences (Meyhöfer, 1985; Riisgård, 1988; Jones et al., 1992; Pouvreau et al., 1999) in clearance rates are explained by corresponding differences in gill surface-areas (Honkoop et al., 2003). Hence, these studies set out the possibility that the differences in the filtering capacity might be related to anatomic differences: the size of the gills. In consequence, the gill seems to be an organ playing a major role in determining the inter-individual growth rate differences. Prieto et al., (2019) searched for candidate genes underlying the biological processes accounting for growth differences at the molecular level in the gills of M. galloprovincialis. They found 117 differentially expressed genes in fast and slow growing mussels, mainly related to differences in the response to stimulus, growth and cellular activity processes. Fast growing mussels showed up-regulation of myostatin, insulin like growthfactor, epidermal growth factor-like domain (EGF), and genes involved in the structure and functionality of connective tissue: laminin, fibulins and decorins. On the contrary, slow growing individuals showed up-regulation of a cell-counting factor that limits the maximum size of the multicellular structure, i.e., inhibition of developmental processes in the gill. Anaerobic metabolic pathways were also enhanced, a symptom of impairment in the aerobic ATP production of the gill. A few other studies (Wang et al., 2010; Saavedra et al., 2017; Zhang et al., 2019; Xie et al., 2020; Nie et al., 2021) on gill transcriptomic analysis of fast versus slow growing specimens have also shown that inter-individual growth rate differences imply large amounts of differentially expressed genes (DEG). The analysis of those DEG in these studies indicate that the differences in the genetic expressions codify for ribosomal proteins and enzymes involved, basically, in energy metabolism, protein synthesis and microtubular motor, rather growth-controlling genes. Indeed, Saavedra et al. (2017) specifically searched for differential expression of genes from the growth Control Gene Core in fast versus slow growing Ruditapes decussatus, but failed to find it. 6.2 Inter-individual differences in digestive capacity Absorption efficiency is influenced by the quality and composition of ingested organic matter. When food is abundant, bivalves may decrease their CR to prevent excessive shortage of gut passage time that could reduce the time available for food particle breakdown, digestion and absorption and hence food absorption efficiency. This allows them to process the available food more efficiently without wasting energy on filtering excessive General introduction 21 amounts of water (Bayne et al., 1993). In environments with low food availability, bivalves can increase their CR to maximize the intake of available nutrients, ensuring they meet their metabolic needs (Hawkins et al., 1996). Bivalves tend to have higher AE when consuming high-quality food sources rich in organic material, such as phytoplankton, compared to detritus or inorganic particles (Navarro et al., 1991; Bayne et al., 1993). This regulation ensures that the digestive organs are not overwhelmed, allowing for more efficient processing and absorption of nutrients (Iglesias et al., 1992). When the ingested material is high in organic content, bivalves can afford to lower their CR slightly to allow more time for digestion and absorption, thus increasing AE (Navarro et al., 1991). Conversely, if the food is low in organic content, maintaining or increasing CR can help ensure that enough organic matter is ingested to meet nutritional needs, even if AE is lower (Hawkins and Bayne, 1985). Given that a functional engagement exists between absorption efficiency and ingestion rate, the capacity to acquire more food would not necessarily result in higher absorption rates, unless there is also an increase in digestive capacity. Several studies (e.g., Ibarrola et al., 1998, 1999, 2000; Labarta et al., 2002; Fernández-Reiriz, 2004) proved acclimation processes in which the rise in enzyme activities allow for higher CR and ingestion rates, keeping the AE constant and notably increasing AR. Due to this adjustments, i.e., plasticity, of the digestive gland, it is reasonable to consider that such an adjustment can also differ between different growing phenotypes, the analysis of which would benefit from the histological approach. The digestive gland has receive little attention in the context of inter-individual growth differences. It is the main organ for intracellular digestion and absorption, but it is also the storage site for metabolic reserves and a participant in the transference of metabolic reserves to other organs (Cartier et al., 2004). Moreover, its morphological appearance has been proved to be of great plasticity under different food availability scenarios (e.g., Morton, 1983; Robinson et al., 1981; Robinson, 1983). In fact, the size of the digestive diverticula and their cellular volume is known to modulate (Ibarrola et al., 2000). However, there is no available data on whether this type of adjustments happen along with food acquisition capacity or different growth rates. Furthermore, experiments performed on differently growing Ruditapes decussatus clam individuals failed to find significant differences between fast and slow growing individuals in the standardized size of the digestive glands, protein content or specific cellulose activity (Tamayo et al., 2011). These studies provided the basic knowledge to understand the digestive regulation of bivalves but must be completed with morphological assessments that uphold the physiological performances of differentially growing individuals. 22 General introduction 7 Factors affecting the energy expenditure The processes that contribute to energy loss in bivalves are the excretion of nitrogenous waste (ammonium) and the energy invested in metabolism. Energy loss resulting from the excretion of ammonium in the urine is generally a minor proportion of the total energy loss in bivalves. It has been estimated to account for around 1-10 % of total metabolic expenditure. Since its influence on the energy balance is minor, it is a physiological parameter that is usually not considered in energy balance determinations (Bayne and Newell 1983; Bayne et al. 1987; Beiras et al. 1995). Therefore, in the present dissertation, we will be focusing solely on the metabolism. Within metabolic rate, two different levels have been stablished: the standard metabolic rate (SMR) and the routine metabolic rate (RMR). 7.1 Standard metabolic rate The standard metabolic rate corresponds to the self-maintenance costs of the organism for the cellular homeostasis and functional integrity. The processes that contribute to a great extent to the standard metabolic expenditure are basically three: i) the protein turnover (constant synthesis and degradation of cellular proteins), ii) the activity of the transmembrane sodium-potassium pump for the active transport of sodium and potassium, and iii) the proton leak through the mitochondrial membrane (Hawkins and Bayne, 1992). The protein turnover can contribute up to a 70 % to the standard metabolic rate in M. edulis (Hawkins and Bayne, 1985; Hawkins et al., 1986, 1989). In fact, the continuous adjustments in the genetic expression account for 9-13 J of energy per protein mg in Mytilus sp. and most animals (Hawkins et al., 1986; Morgan et al., 2000), which makes it the most important component of maintenance metabolism. The activity of the transmembrane sodium-potassium pump has been measured in many mammalian tissues and proved metabolically costly, accounting for around 20 % of the energy expenditure of tissues (Milligan and McBride, 1985; Clausen et al. 1991). In sea urchins (Strongylocentrotus purpuratus) the activity was indeed similar (18 %) for fed larvae, although it can be up to 60 % when starved (Leong, 1998). “Futile” proton cycling, i.e., proton leakage through the mitochondrial membrane, comes at a tremendous energetic cost. In mammals, it can represent 20 to 50 % of total basal metabolic rate (e.g., Brand et al., 1994; Rolfe et al., 1999). Similar to the contribution of Na+/K+ pump to the standard metabolic costs in non-mammals, there is very little evidence about the importance of proton cycling too. Brand et al. (1991) investigated hepatocytes from the bearded dragon, a lizard similar in mass and body temperature to a rat. The results suggested that mitochondrial proton cycling accounted for up to 30 % of respiration rate in the reptile cells, similar to the value in rat hepatocytes. General introduction 23 7.2 Routine metabolic rate The routine metabolic rate is used to define the metabolic activity of an organism under normal activity and feeding conditions. Therefore, the routine metabolism is the result of adding to the standard metabolic expenditures aforementioned the food acquisition, digestion, assimilation and storage expenditures, and those associated with growth, development and reproduction (Parry, 1983; Glazier, 2005). In bivalves, the costs of these processes are commonly referred to as costs of growth and due to the feeding strategy of these organisms, they conform a constant increase in relation to the standard metabolism, provided that the animal can feed itself. The costs of food acquisition, digestion, assimilation and storage expenditures, and those associated with growth, development and reproduction constitute the costs of growth in bivalves. Hawkins and Bayne divided the components of the routine metabolic rate in i) the costs of ciliary activity, ii) the costs of digestion and absorption processes and iii) the costs of growth. The costs of ciliary activity comprise the filtration process accomplished by the activity of the gills and labial palps, representing around 3 % of total metabolic expenditure (Silvester and Sleight, 1984; Jorgensen, 1986; Clemmesen and Jorgensen, 1987). The costs of digestion and absorption processes were measured by Widdows and Hawkins (1989) and constitute around 17 % of total metabolic costs. Additional metabolic costs related to digestion and absorption are metabolic faecal losses and nitrogenous compounds, although these are not metabolic expenditures per se, but rather energy that is not gained. Lastly, the costs of growth are the result of deducting the standard metabolic rate, the costs of ciliary activity, and the costs of digestion and absorption to the total metabolic rate. The costs of growth can be up to 34 % of the total metabolic expenditure and is basically the remnant energy invested in the synthesis or deposition of any kind of tissue: soft tissues (including storage tissue), byssus and shell. 7.3 Factors affecting the metabolic rate 7.3.1 Body size. Allometry The relationship between body size and metabolic rate has been the subject of study since the fundamental allometric relationship established for mammals and birds was extended to include a wide range of invertebrates, including molluscs (Hemmingsen, 1960; Zeuthen, 1947, 1953; von Bertalanffy, 1957). The broad intraspecific variability of the allometric mass exponents of metabolic rate is a biological phenomenon not yet fully understood (e.g., Glazier, 2018; Hatton et al., 2019; Escala, 2022; White et al., 2022). Within specific taxonomic groups, R–metabolic rate– often varies closely with M–body mass–, following a power function that can be described as: R=aMb where ais the scaling coefficient (or proportionality constant) and bis the scaling exponent (or logarithmic 24 General introduction slope). During the late 1800s and early 1900s, many biologists claimed that b was universally 2/3, the so-called ‘surface law’, based on the idea that metabolic resources, wastes and heat are exchanged across organismal surfaces following simple Euclidean geometry (Sarrus and Rameaux, 1839; Glazier, 2014). This belief was initially supported in various birds and mammals (Glazier, 2014), but around 1930s, several analyses of interspecific metabolic scaling caused Kleiber and other scientists to claim that a 3/4 exponent was universal or nearly so. The relationship between body size and metabolic rate is still a source of discussion considering that even thougha reasonable variation both within and among taxa is acknowledged for b value, it is unknown if these variations are deviations from the so-called general “¾-power law”, or whether there is no such law (Agutter and Wheatley, 2004). As explained before, the ¾-power law assumes a scaling exponent of 0.75 for virtually all organisms (e.g., Brown et al., 2004), despite the activity or metabolic level, giving the impression of a common underlying mechanistic origin (Savage et al., 2004). However, due to the broad assumptions of the law and the ample amount of examples in which the b value deviates from 0.75 (see Glazier, 2005), it has suffered harsh criticism (e.g., Bokma, 2004; Suarez et al., 2004; Glazier, 2005; Muller-Landau et al., 2006; White et al., 2007; Glazier, 2008; Glazier, 2009; Glazier, 2010; White, 2011; Carey et al., 2013), and it seems to be no longer acceptable (Glazier, 2022b). The variation in the metabolic scaling exponent is related to ecological (extrinsic) and biological/endogenous factors (intrinsic). Intrinsic effects include those exerted by (i) differences in body-temperature regulation strategies (i.e., endothermic vs. ectothermic animals) (Glazier, 2010; White et al., 2006, 2019; Bigman et al., 2021), (ii) activity level (Glazier, 2005, 2008, 2009, 2010, 2014; White et al., 2007), (iii) life cycle stages (Glazier, 2005; Glazier et al., 2015), (iv) sex (Glazier, 2005; Moffett et al., 2022), (v) genetic strains (Ketola and Kotiaho, 2012; Mathot et al., 2013; Matoo et al., 2019) and (vi) cellular growth modes (Kozlowski et al., 2003; Glazier, 2022a). Extrinsic factors, on the other hand, include temperature, pH, salinity, light intensity, predators, parasites, availability of resources as well as diet, habitat or ecological lifestyle (Lovegrove, 2000; Glazier, 2005, 2006, 2014, 2018, 2020; McKechnie et al., 2006; Jeyasingh, 2007; Killen et al., 2010; McFeeters et al., 2011; Glazier et al., 2011, 2020; Marsden et a., 2012; White and Kearney, 2013; Carey and Sigwart, 2014; Londono et al., 2015; Pequeno et al., 2017; Bushuev et al., 2018; Fossen et al., 2019; Rubalcaba et al., 2020; Gjoni et al., 2024). The effects of the ecological and endogenous factors affecting metabolic scaling is probably the consequence of phenotypic plasticity coming of either biological regulation or natural selection (Glazier, 2022b). In fact, biological scaling is more and more perceived as phenotypically plastic and evolutionarily pliant nowadays, rather than physically or developmentally constrained (e.g., Harte, 2002). As an answer to the acceptance of the metabolic scaling diversity, many multi-mechanistic models have been proposed to explain it (see Glazier, 2018 for review). However, only the metabolic-level boundaries (MLB) hypothesis proposed by Glazier (2005; 2010, 2014) seems to explain not only most of the variation among taxa but also amongst physiological states. General introduction 25 The MLB hypothesis describes how the observed values of b often fall between the theorized boundary values of 0.667 and 1. It explains how b varies when supply exceeds metabolic demand and when metabolic demand exceeds supply. The fluctuation of the scaling exponent between those end values might depend on metabolic rate, activity and ecological factors (Glazier, 2010). 7.3.2 Physiological status Costs of maintenance and growth change depending on the physiological status that can in turn vary in a short, medium or long term according to acclimatization processes. Continuous changes in environmental conditions like temperature, oxygen availability, salinity and water flow rates influence feeding efficiency and energy expenditure during food acquisition, digestion and assimilation (Widdows and Bayne, 1971). For instance, optimal temperatures enhance enzymatic activities involved in protein synthesis, reducing the energy required for these processes (Hochachka and Somero, 2002), while hypoxic conditions may increase the energy costs of protein synthesis as the individuals switch to less efficient anaerobic pathways (De Zwaan and Wijsman, 1976). All those factors also have an impact on food availability and nutritional quality, upon which the costs of food acquisition fundamentally depend on (e.g., Bayne and Worral, 1980). Fluctuations in diet composition also affect the digestion and assimilation efficiency, as well as enzyme production and activity (Ibarrola et al., 1998a,b, 1999, 2000; Kreeger and Newell, 2001). In fact, adequate and consistent food supply ensures that bivalves have the necessary resources for efficient protein production, reducing the metabolic costs associated with protein synthesis (Hawkins et al., 1985). However, nitrogen mismatches between food and body tissues must be compensated by physiological mechanisms for homeostatic nutrient regulation associated to protein biosynthesis and hydrolysis turnover rates in different tissues (Arranz et al, 2023). Exposure to pollutants and pathogen presence can also increase protein turnover rates as bivalves repair damaged proteins and maintain cellular homeostasis (Hochachka and Somero, 2002; Ivanina et al., 2010). Adaptations in the longer-term involve seasonal changes that happen concurrently with food availability. The way an organism is confronted with the seasonality does not only depend on the range in environmental dynamics, but also on the physiological responsiveness of the organism to these conditions. For example, a physiological response (i.e., change in the ingestion rate) to an increase in food concentration will be smaller if this change occurs within the range of the functional response of the organism than if it occurs outside of it. In utter dependency to seasonality and the concomitant food availability there is gametogenesis. In fact, it is commonplace to observe that for most marine and estuarine invertebrates gametogenesis is cyclical, with cycles occurring with an annual, monthly or lunar periodicity, and found in polar, temperate and in tropical species (Giese, 1959; Moore, 1972). The reproductive cycle also makes the costs of growth vary, as energy storage in the form of glycogen or lipids fluctuates depending on the reproductive stage, with increased 26 General introduction storage before spawning (Berthelin et al., 2000). Reproductive cycles can influence protein turnover rates, with increased demands for protein synthesis during gametogenesis and spawning (Gabbott, 1983). Furthermore, the energy cost of reproduction varies with the stage of gametogenesis, with significant energy diverted from somatic growth during spawning (Bayne, 1976). During the pre-reproductive stage, bivalves primarily allocate energy towards somatic growth and shell formation. Energy expenditure is relatively low since less energy is diverted to reproductive processes (Bayne and Worrall, 1980). During gametogenesis, bivalves begin to allocate significant energy towards the development of reproductive tissues. This shift results in a decrease in the energy available for somatic growth (Bayne, 1976). The spawning stage is characterized by the release of gametes, which is energetically demanding. This stage often sees the highest diversion of energy away from somatic growth towards reproductive effort, leaving very little for growth (Bayne and Newell, 1983). Following spawning, bivalves enter a recovery phase where energy allocation shifts back towards somatic growth and maintenance, although recovery of depleted energy reserves is a priority (Gabbott, 1975). 7.3.3 Genotype Correlations between allozyme multilocus heterozygosity and fitness-related characters in bivalve molluscs have been under study for decades (e.g., Koehn and Shumway, 1982; Foltz and Zouros, 1984; Koehn and Gaffney, 1984; Zouros and Foltz, 1987; Gentili and Beaumont, 1988; Koehn et al., 1988; Zouros et al., 1988; Hawkins et al., 1989; Volckaert and Zouros, 1989; Gaffney et al., 1990; Beaumont, 1991). When testing the reasons for such correlation, inconsistencies were found, which lead to two hypothesis: the “direct overdominance” hypothesis (Koehn and Shumway, 1982; Mitton, 1993) pointed at the enzymes as the direct responsible of the correlation and the “associative overdominance” hypothesis (Ohta, 1971; Zouros et al., 1980) postulated the allozymes to only be indicators of the genetic condition responsible for the correlation. Later, data obtained from studies on DNA markers favoured the associative overdominance hypothesis (Bierne et al., 1998, 2000; Coltman et al., 1998; Coulson et al., 1998; Pogson and Fevolden, 1998). Independent of the cause for the heterozygosity, heterozygous individuals would naturally express a wider basal range of effective proteins, allowing the avoidance of new enzyme production in the face of changes in the environment. Which means that different heterozygosity levels could ultimately be linked to different genotypes with a lower or higher efficiency in the protein turnover. In this context, studies considering differences in protein turnover ability suggest it as an important distinct feature between differentially growing individuals (Meyer and Manahan, 2010; Hedgecock et al., 2007; Hawkins and Bayne, 1992; Hawkins et al., 1986, 1997;; Wang et al., 2018; Xie et al., 2020; Zhang et al., 2021). Moreover, some bivalve genotypes are more efficient than others are in converting (i) nutrients into proteins (Toro et al., 2004) and (ii) ingested food into biomass, with optimized mechanisms for digestion and assimilation, allowing them to support rapid tissue growth (Filgueira et al., General introduction 27 2015). In fact, selective breeding for fast growth can enhance traits such as more efficient nutrient absorption and faster tissue growth (Vercaemer and Langdon, 2005). However, inter-individual differences in other processes might be responsible for the metabolic costs differences in the growing phenotypes. For instance, Saavedra et al., (2017) and Prieto et al., (2019) found in clams (R. philippinarum) and mussels (M. galloprovincialis), respectively, a differential gene expression in genes related to the immune system. Slow growing individuals showed over expression of genes involved in immune and defence typically expressed in response to different stress types (temperature, salinity, metal exposure or bacteria). 7.3.4 Fatty acid composition and ROS production Besides ATP production, mitochondria are involved in various signal transduction pathways and many other activities in the cell (e.g., Kastaniotis et al., 2017; Santulli et al., 2015; Pedersen, 1999; Prasad, 2011; Pattappa et al., 2011; Mistry et al., 2019). However, even in good conditions, the electron-transport chain localized in mitochondrial membranes is the major cellular site where oxygen is reduced, being the main source of reactive oxygen species (ROS) generation in the cell. ROS are therefore a collateral damage of the normal metabolism in the cell, a routine and necessary process that is hence inevitable. In consequence, ROS production is also directly proportional to cell activity (Tamura et al., 2020). Taking into account their high reactivity, these ROS can initiate free-radical processes and cause the destruction of membrane lipids, proteins, and damage to mitochondrial DNA (Krylatov et al., 2018). In fact, the accumulation of damages caused by these free radicals has been held accountable for the decrease in physiological functions that ultimately leads to the aging and death of the organism (Buttemer et al., 2010; Pamplona et al., 2011), which is known as the free radical theory (Harman, 1956). In bivalves, it has been recently proven the inverse correlation between ROS production and lifespan (Istomina et al., 2023). According to a recent viewpoint, the characteristics of the fatty acids in mitochondrial membranes may influence the rate of oxidative damage in cells, and thus lifespan (Hulber and Else, 1999; Barja, 2002; Pamplona et al., 2002; Hulbert et al., 2007). This correlation has also been demonstrated in various bivalve species (Munro and Blier, 2012; Rodríguez et al., 2019; Ungvari et al., 2016; Istomina et al., 2023). A higher cellular redox homeostasis is associated with lower levels of accumulated macromolecular damage, but not necessarily with greater antioxidant capacities nor specific activities (Ungvari et al., 2016), which means either a lower ROS production or less damage. The lipid composition of the cell membrane might also affect the metabolic expenditures. In the oyster C. gigas, for instance, a positive significant correlation has been described between the standard metabolism and the degree of phospholipid unsaturation in the membranes (Pernet et al., 2006, 2007, 2008). This suggest that a lower unsaturation level in the membranes allows for a lower proton leakage, 28 General introduction turning the metabolism into a more efficient one. Enhanced membrane and mitochondrial efficiency can lead to better growth performance, as more energy is available for biosynthetic processes and less is lost as heat or used in maintenance metabolism (Pörtner et al., 1999). Oxidative damage may be positively related to growth rate, due to the higher rate of ROS production that can accompany greater cellular activity. For example, transgenic mice that grow fast due to overexpression of growth hormone produce more ROS and have a greater incidence of lipid peroxidation (Rollo et al. 1996). Similarly, elevated growth rates have been recorded as causing both a reduction (Alonso-Alvarez et al., 2007) and an increase (De Block and Stoks, 2008) in antioxidant defences; these opposite trends were nonetheless both interpreted as indicating greater oxidative damage. It has been suggested that oxidative stress might play a key role as a constraint on, and cost of, growth (Schantz et al., 1999; Monaghan et al., 2009) and it has been measured in plants (Zhang et al., 2016), captive finches (Alonso-Alvarez et al., 2006), wild alpine marmots (Costantini et al., 2012) and barn swallows (Costantini, 2014). Yet inconsistent patterns have been reported for the relationship of growth with oxidative stress. Enhanced growth have been linked to higher antioxidant levels but increased oxidative damage in corvids (Salomons, 2009), sheep (Nussey et al. 2009), scallops (Guerra et al., 2012), coal tits (Stier et al., 2014). Reduced levels of antioxidants have been related to growth in great tits (Kilgas et al., 2010), and both raised and reduced antioxidant levels in coho salmon (Leggatt et al., 2007; Almroth et al., 2012), but other studies have found no effect (Rosa et al., 2008; Larcombe et al., 2010; Geiger et al., 2011). References Agutter, P. S. and Wheatley, D. N. (2004). Metabolic scaling: consensus or controversy?. Theoretical Biology and Medical Modelling, 1, 1-11. Almroth, B. C., Johnsson, J. I., Devlin, R. and Sturve, J. (2012). Oxidative stress in growth hormone transgenic coho salmon with compressed lifespan–a model for addressing aging. Free radical research, 46(10), 1183-1189. Alonso-Alvarez, C., Bertrand, S., Devevey, G., Prost, J., Faivre, B., Chastel, O. and Sorci, G. (2006). An experimental manipulation of life-history trajectories and resistance to oxidative stress. Evolution, 60(9), 1913-1924. Alonso-Alvarez, C., Bertrand, S., Faivre, B. and Sorci, G. (2007). Increased susceptibility to oxidative damage as a cost of accelerated somatic growth in zebra finches. Functional ecology, 21(5), 873-879. Arranz, K., Urrutxurtu, I., Martínez-Patiño, D. and Navarro, E. (2023). Growth and Physiological General introduction 35 Dral, A. D. G. (1967). The movements of the latero-frontal cilia and the mechanism of particle retention in the mussel. Netherlands Journal of Sea Research, 3, 391-422. Dutertre, M., Barillé, L., Haure, J., and Cognie, B. (2007). Functional responses associated with pallial organ variations in the Pacific oyster Crassostrea gigas (Thunberg, 1793). Journal of Experimental Marine Biology and Ecology, 352(1), 139-151. Earhart, M. L., Blanchard, T. S., Harman, A. A. and Schulte, P. M. (2022). Hypoxia and high temperature as interacting stressors: will plasticity promote resilience of fishes in a changing world?. The Biological Bulletin, 243(2), 149-170. Ekstrom, J. A., Suatoni, L., Cooley, S. R., Pendleton, L. H., Waldbusser, G. G., Cinner, J. E., ... and Portela, R. (2015). Vulnerability and adaptation of US shellfisheries to ocean acidification. Nature climate change, 5(3), 207-214. Escala, A. (2022). Universal relation for life-span energy consumption in living organisms: Insights for the origin of aging. Scientific Reports, 12(1), 2407. Espinosa, E. P., Perrigault, M. and Allam, B. (2010). Identification and molecular characterization of a mucosal lectin (MeML) from the blue mussel Mytilus edulis and its potential role in particle capture. Comparative Biochemistry and Physiology Part A: Molecular & Integrative Physiology, 156(4), 495-501. Essink, K., Tydeman, P., De Koning, F. and Kleef, H. L. (1989). On the adaptation of the mussel Mytilus edulis L. to different environmental suspended matter concentrations. Proceedings of the 21st EMBS Gdansk, 14–19, 41-51. Fangue, N. A., Osborne, E.J., Todgham, A. E. andSchulte, P. M.(2011). The onsettemperature ofthe heat-shock response and whole-organism thermal tolerance are tightly correlated in both laboratory-acclimated and field-acclimatized tidepool sculpins (Oligocottus maculosus).Physiological and Biochemical Zoology, 84(4), 341-352. Fankboner, P. V. (1971). The ciliary currents associated with feeding, digestion, and sediment removal in Adula (Botula) falcata Gould 1851. The Biological Bulletin, 140(1), 28-45. Fernández-Reiriz, M. J., Irisarri, J. and Labarta, U. (2016). Flexibility of physiological traits underlying interindividual growth differences in intertidal and subtidal mussels Mytilus galloprovincialis.PLoS One, 11(2), e0148245. Fernández-Reiriz, M. J., Labarta, U. and Navarro, J. M. (2004). Feeding and digestive response of Argopecten purpuratus to short-term variation in food quality and quantity. Aquaculture, 237(1-4), 347-364. 36 General introduction Filgueira, R., Comeau, L. A., Guyondet, T., McKindsey, C. W. and Byron, C. J. (2015). Modelling carrying capacity of bivalve aquaculture: a review of definitions and methods (pp. 1-33). Fisheries and Oceans Canada, Ecosystems and Oceans Science. Foltz, D. W. and Zouros, E. (1984). Possible explanations of heterozygote deficiency in bivalve molluscs. Malacologia, 25, 583–591. Fossen, E. I., Pelabon, C. and Einum, S. (2019). Genetic and environmental effects on the scaling of metabolic rate with body size. Journal of Experimental Biology, 222(7), jeb193243. Foster-Smith, R. L. (1975). The effect of concentration of suspension and inert material on the assimilation of algae by three bivalves. Journal of the Marine Biological Association of the United Kingdom, 55(2), 411-418. Foster-Smith, R. L. (1975). The effect of concentration of suspension on the filtration rates and pseudofaecal production for Mytilus edulis L., Cerastoderma edule (L.) and Venerupis pullastra (Montagu). Journal of Experimental Marine Biology and Ecology, 17(1), 1-22. Franz, D. R. (1993). Allometry of shell and body weight in relation to shore level in the intertidal bivalve Geukensia demissa (Bivalvia: Mytilidae). Journal of Experimental Marine Biology and Ecology, 174(2), 193-207. Freeman, A. S. (2007). Specificity of induced defenses in Mytilus edulis and asymmetrical predator deterrence. Marine Ecology Progress Series, 334, 145-153. Gabbott, P. A. (1975). Storage cycles in marine bivalve molluscs: a hypothesis concerning the relationship between glycogen metabolism and gametogenesis. In: Barnes, H.B. (Ed.) (1975). Ninth European Marine Biology Symposium. pp. 191-211. European Marine Biology Symposia, 9. Aberdeen University Press: Aberdeen. IX, 760 pp. Gabbott, P. A. (1983). Developmental and seasonal metabolic activities in marine molluscs. In The mollusca (pp. 165-217). Academic Press. Gaffney, P. M., Scott, T. M., Koehn, R. K. and Diehl, W. J. (1990). Interrelationships of heterozygosity, growth rate and heterozygote deficiencies in the coot clam, Mulinia lateralis. Genetics, 124(3), 687-699. Galimany, E., Ramón, M. and Ibarrola, I. (2011). Feeding behavior of the mussel Mytilus galloprovincialis (L.) in a Mediterranean estuary: a field study. Aquaculture, 314(1-4), 236-243. Galtsoff, P.S. 1964. The American oyster Crassostrea virginica Gmelin. Fisheries Bulletin, 64, Govern. Print. Office, Washington. 480 pp. Garton, D. W., Koehn, R. K. and Scott, T. M. (1984). Multiple-locus heterozygosity and the physiological General introduction 37 energetics of growth in the coot clam, Mulinia lateralis, from a natural population. Genetics, 108(2), 445-455. Geiger, P. C. and Gupte, A. A. (2011). Heat shock proteins are important mediators of skeletal muscle insulin sensitivity. Exercise and sport sciences reviews, 39(1), 34-42. Gentili, M. R. and Beaumont, A. R. (1988). Environmental stress, heterozygosity, and growth rate in Mytilus edulis L. Journal of Experimental Marine Biology and Ecology, 120(2), 145-153. Gestoso, I., Arenas, F., Rubal, M., Veiga, P., Peña, M. and Olabarria, C. (2013). Shifts from native to non-indigenous mussels: enhanced habitat complexity and its effects on faunal assemblages. Marine environmental research, 90, 85-95. Gibbs, P. E. (1993). Phenotypic changes in the progeny of Nucella lapillus (Gastropoda) transplanted from an exposed shore to sheltered inlets. Journal of Molluscan Studies, 59(2), 187-194. Giese, A. C. (1959). Annual reproductive cycles of marine invertebrates. Annual Review Physiology, 21, 547-576. Gjoni, V., Marchessaux, G., Glazier, D. S., Wesner, J. S., Bosch-Belmar, M., Mancuso, F. P., ... and Sarà, G. (2024). Metabolic scaling of an invasive mussel depends on temperature and chemical cues from an invasive predator. Biology Letters, 20(6), 20240066. Glazier, D. S. (2005). Beyond the ‘3/4-power law’: variation in the intra-and interspecific scaling of metabolic rate in animals. Biological reviews, 80(4), 611-662. Glazier, D. S. (2008). Effects of metabolic level on the body size scaling of metabolic rate in birds and mammals. Proceedings of the Royal Society B: Biological Sciences, 275(1641), 1405-1410. Glazier, D. S. (2009). Activity affects intraspecific body-size scaling of metabolic rate in ectothermic animals. Journal of Comparative Physiology B, 179, 821-828. Glazier, D. S. (2010). A unifying explanation for diverse metabolic scaling in animals and plants. Biological Reviews, 85(1), 111-138. Glazier, D. S. (2014). Metabolic scaling in complex living systems. Systems, 2(4), 451-540. Glazier, D. S. (2018). Rediscovering and reviving old observations and explanations of metabolic scaling in living systems. Systems, 6(1), 4. Glazier, D. S. (2022a). How metabolic rate relates to cell size. Biology, 11(8), 1106. Glazier, D. S. (2022b). Variable metabolic scaling breaks the law: from ‘Newtonian’to ‘Darwinian’approaches. Proceedings of the Royal Society B, 289(1985), 20221605. 38 General introduction Glazier, D. S., Hirst, A. G. and Atkinson, D. (2015). Shape shifting predicts ontogenetic changes in metabolic scaling in diverse aquatic invertebrates. Proceedings of the Royal Society B: Biological Sciences, 282(1802), 20142302. Gleason, L. U., Miller, L. P., Winnikoff, J. R., Somero, G. N., Yancey, P. H., Bratz, D. and Dowd, W. W. (2017). Thermal history and gape of individual Mytilus californianus correlate with oxidative damage and thermoprotective osmolytes. Journal of Experimental Biology, 220(22), 4292-4304. Gosling, E. (2008). Bivalve molluscs: biology, ecology and culture. John Wiley & Sons. Gracey, A. Y. and Connor, K. (2016). Transcriptional and metabolomic characterization of spontaneous metabolic cycles in Mytilus californianus under subtidal conditions. Marine Genomics, 30, 35-41. Gracey, A. Y., Chaney, M. L., Boomhower, J. P., Tyburczy, W. R., Connor, K. and Somero, G. N. (2008). Rhythms of gene expression in a fluctuating intertidal environment. Current Biology, 18(19), 1501-1507. Greenway, S. C. and Storey, K. B. (2001). Effects of seasonal change and prolonged anoxia on metabolic enzymes of Littorina littorea.Canadian journal of zoology, 79(5), 907-915. Guerra, C., Zenteno-Savín, T., Maeda-Martínez, A. N., Philipp, E. E. R. and Abele, D. (2012). Changes in oxidative stress parameters in relation to age, growth and reproduction in the short-lived catarina scallop Argopecten ventricosus reared in its natural environment. Comparative Biochemistry and Physiology Part A: Molecular & Integrative Physiology, 162(4), 421-430. Guo, X. and Allen Jr, S. K. (1994). Reproductive potential and genetics of triploid Pacific oysters, Crassostrea gigas (Thunberg). The Biological Bulletin, 187(3), 309-318. Guo, X., DeBrosse, G. A. and Allen Jr, S. K. (1996). All-triploid Pacific oysters (Crassostrea gigas Thunberg) produced by mating tetraploids and diploids. Aquaculture, 142(3-4), 149-161. Gutiérrez, J. L., Jones, C. G., Strayer, D. L. and Iribarne, O. O. (2003). Mollusks as ecosystem engineers: the role of shell production in aquatic habitats. Oikos, 101(1), 79-90. Halpin, P. M., Menge, B. A. and Hofmann, G. E. (2004). Experimental demonstration of plasticity in the heat shock response of the intertidal mussel Mytilus californianus.Marine Ecology Progress Series, 276, 137-145. Harman, D. (1956). Aging: The theory based on free radical and radiation chemistry with application to cancer and atherosclerosis. Rad. Lab. Calender Univ. Calif.-Berkeley, 3(3). Harte, J. (2002). Toward a synthesis of the Newtonian and Darwinian worldviews. Physics Today, 55(10), 29-34. General introduction 39 Hatton, I. A., Dobson, A. P., Storch, D., Galbraith, E. D. and Loreau, M. (2019). Linking scaling laws across eukaryotes. Proceedings of the National Academy of Sciences, 116(43), 21616-21622. Hawkins, A. J. and Bayne, B. L. (1991). Nutrition of marine mussels: factors influencing the relative utilisation of protein and energy. Aquaculture, 94(2-3), 177-196. Hawkins, A. J. and Day, A. J. (1996). The metabolic basis of genetic differences in growth efficiency among marine animals. Journal of Experimental Marine Biology and Ecology, 203(1), 93-115. Hawkins, A. J. and Day, A. J. (1999). Metabolic interrelations underlying the physiological and evolutionary advantages of genetic diversity. American Zoologist, 39(2), 401-411. Hawkins, A. J. S. and Bayne, B. L. (1985). Seasonal variation in the relative utilization of carbon and nitrogen by the mussel Mytilus edulis: budgets, conversion efficiencies and maintenance requirements. Marine ecology progress series. Oldendorf, 25(2), 181-188. Hawkins, A. J. S., Bayne, B. L., Day, A. J. and Denton, E. J. (1986). Protein turnover, physiological energetics and heterozygosity in the blue mussel, Mytilus edulis: the basis of variable age-specific growth. Proceedings of the Royal society of London. Series B. Biological sciences, 229(1255), 161-176. Hawkins, A. J. S., Salkeld, P. N., Bayne, B. L., Gnaiger, E. and Lowe, D. M. (1985). Feeding and resource allocation in the mussel Mytilus edulis: evidence for time-averaged optimization. Marine ecology progress series. Oldendorf, 20(3), 273-287. Hawkins, A. J. S., Smith, R. F. M., Bayne, B. L. and Heral, M. (1996). Novel observations underlying the fast growth of suspension-feeding shellfish in turbid environments: Mytilus edulis.Marine Ecology Progress Series, 131, 179-190. Hawkins, A. J. S., Widdows, J. and Bayne, B. L. (1989). The relevance of whole-body protein metabolism to measured costs of maintenance and growth in Mytilus edulis.Physiological Zoology, 62(3), 745-763. Hawkins, A. J., Smith, R. F., Bougrier, S., Bayne, B. L. and Héral, M. (1997). Manipulation of dietary conditions for maximal growth in mussels, Mytilus edulis, from the Marennes-Oléron Bay, France. Aquatic Living Resources, 10(1), 13-22. Hedgecock, D. and Davis, J. P. (2007). Heterosis for yield and crossbreeding of the Pacific oyster Crassostrea gigas.Aquaculture, 272, S17-S29. Hedgecock, D., Lin, J. Z., DeCola, S., Haudenschild, C. D., Meyer, E., Manahan, D. T. and Bowen, B. (2007). Transcriptomic analysis of growth heterosis in larval Pacific oysters (Crassostrea gigas). Proceedings of the National Academy of Sciences, 104(7), 2313-2318. 40 General introduction Hemmingsen (1960). Energy metabolism as related to body size and respiratory surfaces, and its evolution. Rep. Steno Mem. Hosp. Nord. Insulin Lab., 9, 3–110. Henry, M., Boucaud-Camou, E. and Lefort, Y. (1991). Functional micro-anatomy of the digestive gland of the scallop Pecten maximus (L.). Aquatic Living Resources, 4(3), 191-202. Hentschel, B. T. and Shimeta, J. (2008). Suspension feeders. In Encyclopedia of ecology, pp. 3437-3442. Amsterdam, The Netherlands: Elsevier Science Ltd. Hochachka, P. W. and Somero, G. N. (2002). Biochemical adaptation: mechanism and process in physiological evolution. Oxford university press. Honkoop, P. J. (2003). Flexibility of feeding traits and the distribution of marine benthic invertebrates, particularly bivalves. Fishery Research, 5. Honkoop, P. J. C., Bayne, B. L. and Drent, J. (2003). Flexibility of size of gills and palps in the Sydney rock oyster Saccostrea glomerata (Gould, 1850) and the Pacific oyster Crassostrea gigas (Thunberg, 1793). Journal of Experimental Marine Biology and Ecology, 282(1-2), 113-133. Houlihan, D. F., Livingstone, D. R., Lee, R. F. and Lee, R. F. (1991). Lipoproteins from the haemolymph and ovaries of marine invertebrates. Advances in Comparative and Environmental Physiology, 7, 187-207. Hughes, R. N. and Elner, R. W. (1979). Tactics of a predator, Carcinus maenas, and morphological responses of the prey, Nucella lapillus. The Journal of Animal Ecology, 65-78. Hughes, T.G. (1975). The sorting of food particles by Abra sp. (Bivalvia: Tellinacea). Journal of Experimental Marine Biology and Ecology, 20, 137 – 156. Hulbert, A. J. and Else, P. L. (1999). Membranes as possible pacemakers of metabolism. Journal of theoretical biology, 199(3), 257-274. Hulbert, A. J., Pamplona, R., Buffenstein, R. and Buttemer, W. A. (2007). Life and death: metabolic rate, membrane composition, and life span of animals. Physiological reviews, 87(4), 1175-1213. Ibarrola, I., Arambalza, U., Navarro, J. M., Urrutia, M. B. and Navarro, E. (2012). Allometric relationships in feeding and digestion in the Chilean mytilids Mytilus chilensis (Hupé), Choromytilus chorus (Molina) and Aulacomya ater (Molina): a comparative study. Journal of Experimental Marine Biology and Ecology, 426, 18-27. Ibarrola, I., Etxeberria, M., Iglesias, J. I. P., Urrutia, M. B. and Angulo, E. (2000). Acute and acclimated digestive responses of the cockle Cerastoderma edule (L.) to changes in the food quality and quantity: II. Enzymatic, cellular and tissular responses of the digestive gland. Journal of experimental marine biology and ecology, General introduction 41 252(2), 199-219. Ibarrola, I., Larretxea, X., Iglesias, J. I. P., Urrutia, M. B. and Navarro, E. (1998). Seasonal variation of digestive enzyme activities in the digestive gland and the crystalline style of the common cockle Cerastoderma edule.Comparative Biochemistry and Physiology Part A: Molecular & Integrative Physiology, 121(1), 25-34. Ibarrola, I., Navarro, E. and Iglesias, J. I. P. (1998). Short-term adaptation of digestive processes in the cockle Cerastoderma edule exposed to different food quantity and quality. Journal of Comparative Physiology B, 168, 32-40. Ibarrola, I., Navarro, E. and Urrutia, M. B. (2000). Acute and acclimated digestive responses of the cockle Cerastoderma edule (L.) to changes in food quality and quantity: I. Feeding and absorption of biochemical components. Journal of experimental marine biology and ecology, 252(2), 181-198. Ibarrola, I., Navarro, E., Iglesias, J. I. P. and Urrutia, M. B. (1999). Time-course of digestive-enzyme acclimation in the cockle Cerastoderma edule.Marine Biology, 135, 47-56. Iglesias, J. I. P., Navarro, E., Jorna, P. A. and Armentina, I. (1992). Feeding, particle selection and absorption in cockles Cerastoderma edule (L.) exposed to variable conditions of food concentration and quality. Journal of Experimental Marine Biology and Ecology, 162(2), 177-198. Istomina, A. A., Zhukovskaya, A. F., Mazeika, A. N., Barsova, E. A., Chelomin, V. P., Mazur, M. A., ... and Karpenko, A. A. (2023). The relationship between lifespan of marine bivalves and their fatty acids of mitochondria lipids. Biology, 12(6), 837. Ivanina, A. V., Eilers, S., Kurochkin, I. O., Chung, J. S., Techa, S., Piontkivska, H., ... and Sokolova, I. M. (2010). Effects of cadmium exposure and intermittent anoxia on nitric oxide metabolism in eastern oysters, Crassostrea virginica. Journal of Experimental Biology, 213(3), 433-444. Ivanina, A. V., Nesmelova, I., Leamy, L., Sokolov, E. P. and Sokolova, I. M. (2016). Intermittent hypoxia leads to functional reorganization of mitochondria and affects cellular bioenergetics in marine molluscs. Journal of Experimental Biology, 219(11), 1659-1674. Izagirre, U. and Marigómez, I. (2009). Lysosomal enlargement and lysosomal membrane destabilisation in mussel digestive cells measured by an integrative index. Environmental pollution, 157(5), 1544-1553. Jeyasingh, P. D. (2007). Plasticity in metabolic allometry: the role of dietary stoichiometry. Ecology Letters, 10(4), 282-289. Jones, C. G., Lawton, J. H. and Shachak, M. (1994). Organisms as ecosystem engineers. Oikos, 69, 373–386. Jones, H. D., Richards, O. G. and Southern, T. A. (1992). Gill dimensions, water pumping rate and body size in 42 General introduction the mussel Mytilus edulis L. Journal of Experimental Marine Biology and Ecology, 155(2), 213-237. Jorgensen, C. B. (1966). The biology of suspension feeding. Pergamon Press, Oxford. Jørgensen, C. B. (1976). Comparative studies on the function of gills in suspension feeding bivalves, with special reference to effects of serotonin. The Biological Bulletin, 151(2), 331-343. Jørgensen, C. B. (1981). A hydromechanical principle for particle retention in Mytilus edulis and other ciliary suspension feeders. Marine Biology, 61, 277-282. Jørgensen, C. B. (1996). Bivalve filter feeding revisited. Marine Ecology Progress Series, 142, 287-302. Jørgensen, C. B., Famme, P., Kristensen, H. S., Larsen, P. S., Møhlenberg, F. and Riisgård, H. U. (1986). The bivalve pump. Marine Ecology Progress Series, 69-77. Kang, H. Y., Lee, Y. J., Choi, K.S., Park, H. J., Yun, S. G.andKang, C. K.(2016). Combinedeffects of temperature and seston concentration on the physiological energetics of the Manila clam Ruditapes philippinarum. PLoS One, 11(3), e0152427. Kastaniotis, A. J., Autio, K. J., Kerätär, J. M., Monteuuis, G., Mäkelä, A. M., Nair, R. R., ... and Hiltunen, J. K. (2017). Mitochondrial fatty acid synthesis, fatty acids and mitochondrial physiology. Biochimica et Biophysica Acta (BBA)-Molecular and Cell Biology of Lipids, 1862(1), 39-48. Kellogg, J. L. (1915). Ciliary mechanisms of lamellibranchs with descriptions of anatomy. Journal of morphology, 26(4), 625-701. Ketola, T. and Kotiaho, J. S. (2012). Inbreeding depression in the effects of body mass on energy use. Biological Journal of the Linnean Society, 105(2), 309-317. Kilgas, P., Tilgar, V., Külavee, R., Saks, L., Hõrak, P. and Mänd, R. (2010). Antioxidant protection, immune function and growth of nestling great tits Parus major in relation to within-brood hierarchy. Comparative Biochemistry and Physiology Part B: Biochemistry and Molecular Biology, 157(3), 288-293. Killen, S. S., Atkinson, D. and Glazier, D. S. (2010). The intraspecific scaling of metabolic rate with body mass in fishes depends on lifestyle and temperature. Ecology letters, 13(2), 184-193. Kim, S. H. (2016). Ultrastructural studies on oocyte development and vitellogenesis associated with follicle cellsinfemale Scapharcasubcrenata (Pelecypoda: Arcidae)inWesternKorea. Development & Reproduction, 20(3), 227. Kim, S. H. and Chung, E. Y. (2014). Oogenesis and oocyte degeneration in Coecella chinensis (Bivalvia: Mesodesmatidae). The Korean Journal of Malacology, 30(4), 333-342. General introduction 43 Kim, S. H., Chung, E. Y. and Lee, K. Y. (2014). Oocyte degeneration associated with follicle cells in female Mactra chinensis (Bivalvia: Mactridae). Development & Reproduction, 18(4), 321. Kitching, J. A., Muntz, L. and Ebling, F. J. (1966). The ecology of Lough Ine. XV. The ecological significance of shell and body forms in Nucella. The Journal of Animal Ecology, 113-126. Klionsky, D. J. and Emr, S. D. (2000). Autophagy as a regulated pathway of cellular degradation. Science, 290(5497), 1717-1721. Koehn, R. K. and Gaffney, P. M. (1984). Genetic heterozygosity and growth rate in Mytilus edulis.Marine Biology, 82, 1-7. Koehn, R. K. and Shumway, S. E. (1982). A genetic/physiological explanation for differential growth rate among individuals of the American oyster Crassostrea virginica (Gmelin). Koehn, R. K., Diehl, W. J. and Scott, T. M. (1988). The differential contribution by individual enzymes of glycolysis and protein catabolism to the relationship between heterozygosity and growth rate in the coot clam, Mulinia lateralis. Genetics, 118(1), 121-130. Koprivnikar, J., Lim, D., Fu, C. and Brack, S. H. (2010). Effects of temperature, salinity, and pH on the survival and activity of marine cercariae. Parasitology Research, 106, 1167-1177. Kozłowski, J., Konarzewski, M. and Gawelczyk, A. T. (2003). Cell size as a link between noncoding DNA and metabolic rate scaling. Proceedings of the National Academy of Sciences, 100(24), 14080-14085. Kreeger, D. A. and Newell, R. I. (2001). Seasonal utilization of different seston carbon sources by the ribbed mussel, Geukensia demissa (Dillwyn) in a mid-Atlantic salt marsh. Journal of Experimental Marine Biology and Ecology, 260(1), 71-91. Krylatov, A. V., Maslov, L. N., Voronkov, N. S., Boshchenko, A. A., Popov, S. V., Gomez, L., ... and Downey, J. M. (2018). Reactive oxygen species as intracellular signalling molecules in the cardiovascular system. Current cardiology reviews, 14(4), 290-300. Labarta, U., Fernández-Reiriz, M., Navarro, J. and Velasco, A. (2002). Enzymatic digestive activity in epifaunal (Mytilus chilensis) and infaunal (Mulinia edulis) bivalves in response to changes in food regimes in a natural environment. Marine biology, 140, 669-676. Lafferty, K. D., DeLeo, G., Briggs, C. J., Dobson, A. P., Gross, T. and Kuris, A. M. (2015). A general consumerresource population model. Science, 349(6250), 854-857. Lambert, Y., Dutil, J-D. and Munro, J. (1994). Effects of intermediate and low salinity conditions on growth rate and food conversion of Atlantic cod (Gadus morhua).Canadian Journal of Fisheries and Aquatic Sciences, 44 General introduction 51, 1569-1576. Langton, R. W. (1975). Synchrony in the digestive diverticula of Mytilus edulis L. Journal of the Marine Biological Association of the United Kingdom, 55(1), 221-229. Larcombe, S. D., Mullen, W., Alexander, L. and Arnold, K. E. (2010). Dietary antioxidants, lipid peroxidation and plumage colouration in nestling blue tits Cyanistes caeruleus.Naturwissenschaften, 97, 903-913. Le Pennec, M., Beninger, P. G., Dorange, G. and Paulet, Y. M. (1991). Trophic sources and pathways to the developing gametes of Pecten maximus (Bivalvia: Pectinidae). Journal of the Marine Biological Association of the United Kingdom, 71(2), 451-463. Lee, I. S., Rho, B. J., Song, J. I., Kim, E. J. (1996). The concentrations of heavy metals in sediment, seawater and oyster (Crassostrea gigas) in coastal regions of industrial complex in Korea. Korean Journal of Ecology, 19, 261–270. Lee, K. Y. and Chung, E. Y. (2008). Ultrastructural studies of oogenesis and oocyte degeneration in female Ruditapes philippinarum (Bivalvia: Veneridae) from Gomso Bay, Korea. Development and Reproduction, 12(1), 41-49. Leeuwis, R. H. and Gamperl, A. K. (2022). Adaptations and plastic phenotypic responses of marine animals to the environmental challenges of the high intertidal zone. In Oceanography and Marine Biology (pp. 625-679). CRC Press. Leggatt, R. A., Brauner, C. J., Iwama, G. K. and Devlin, R. H. (2007). The glutathione antioxidant system is enhanced in growth hormone transgenic coho salmon (Oncorhynchus kisutch).Journal of Comparative Physiology B, 177, 413-422. Lekube, X., Cajaraville, M. P. and Marigómez, I. (2000). Use of polyclonal antibodies for the detection of changes induced by cadmium in lysosomes of aquatic organisms. Science of the total environment, 247(2-3), 201-212. Leong, P. K. K. (1998). Metabolic importance of sodium, potassium-ATPase activity during early development of marine invertebrates. University of Southern California. Lesser, M. P., Shumway, S. E., Cucci, T., Barter J. and Edwards, J. 1991. Size specific selection of phytoplankton by juvenile filter-feeding bivalves: comparison of the sea scallop Placopecten magellanicus (Gmelin, 1979) with Mya arenaria Linnaeus, 1758 and Mytilus edulis Linnaeus, 1758. In: Shumway, S. E. and P. A. Sandifer, editors. An International Compendium of Scallop Biology and Culture World Aquaculture Society. Baton Rouge, LA: World Aquaculture Society. pp. 341–346. General introduction 51 Journal of helminthology, 80(2), 183-191. Pouvreau, S., Jonquières, G. and Buestel, D. (1999). Filtration by the pearl oyster, Pinctada margaritifera, under conditions of low seston load and small particle size in a tropical lagoon habitat. Aquaculture, 176(3-4), 295-314. Prasad, S. S., Garg, A. and Agarwal, A. K. (2011). Enzymatic activities of the human AGPAT isoform 3 and isoform 5: localization of AGPAT5 to mitochondria [S]. Journal of lipid research, 52(3), 451-462. Prieto, D., Arranz, K., Urrutxurtu, I., Navarro, E., Urrutia, M. B. and Ibarrola, I. (2020). Variable Capacity for Acute and Chronic Thermal Compensation of Physiological Rates Contributes to Inter-Individual Differences in Growth Rate in Mussels (Mytilus galloprovincialis). Frontiers in Marine Science, 7, 577421. Prieto, D., Markaide, P., Urrutxurtu, I., Navarro, E., Artigaud, S., Fleury, E., ... and Urrutia, M. B. (2019). Gill transcriptomic analysis in fast-and slow-growing individuals of Mytilus galloprovincialis.Aquaculture, 511, 734242. Prieto, D., Tamayo, D., Urrutxurtu, I., Navarro, E., Ibarrola, I. and Urrutia, M. B. (2020). Nature more than nurture affects the growth rate of mussels. Scientific reports, 10(1), 3539. Prieto, D., Urrutxurtu, I., Navarro, E., Urrutia, M. B. and Ibarrola, I. (2018). Mytilus galloprovincialis fast growing phenotypes under different restrictive feeding conditions: Fast feeders and energy savers. Marine environmental research, 140, 114-125. Purchon, R. D. (1987). Classification and evolution of the Bivalvia: an analytical study. Philosophical Transactions of the Royal Society of London. B, Biological Sciences, 316(1177), 277-302. Raffaelli, D. and Hawkins, S. (1999) (eds.). Intertidal Ecology. Dordrecht, the Netherlands: Kluwer Academic Publishers, second edition. Ribelin, B. W. and Collier, A. (1977). Studies on the gill ciliation of the American oyster Crassostrea virginica (Gmelin). Journal of morphology, 151(3), 439-449. Richards, J. G. (2011). Physiological, behavioral and biochemical adaptations of intertidal fishes to hypoxia. Journal of Experimental Biology, 214(2), 191-199. Riisgård, H. U. (1988). Efficiency of particle retention and filtration rate in 6 species of Northeast American bivalves. Marine ecology progress series. Oldendorf, 45(3), 217-223. Riisgård, H. U. and Larsen, P. S. (2010). Particle capture mechanisms in suspension-feeding invertebrates. Marine Ecology Progress Series, 418, 255-293. Roberts, D. A., Hofmann, G. E. and Somero, G. N. (1997). Heat-shock protein expression in Mytilus 52 General introduction californianus: acclimatization (seasonal and tidal-height comparisons) and acclimation effects. The Biological Bulletin, 192(2), 309-320. Robinson, W. E. (1983). Assessment of bivalve intracellular digestion based on direct measurements. Journal of Molluscan Studies, 49(1), 1-8. Robinson, W. E., Pennington, M. R. and Langton, R. W. (1981). Variability of tubule types within the digestive glands of Mercenaria mercenaria (L.), Ostrea edulis L., and Mytilus edulis L. Journal of Experimental Marine Biology and Ecology, 54(3), 265-276. Rodríguez, M., G. Rebollar, P., Mattioli, S. and Castellini, C. (2019). n-3 PUFA sources (precursor/products): A review of current knowledge on rabbit. Animals, 9(10), 806. Rolfe, D. F., Newman, J. M., Buckingham, J. A., Clark, M. G and Brand, M. D. (1999). Contribution of mitochondrial proton leak to respiration rate in working skeletal muscle and liver and to SMR. American Journal of Physiology-Cell Physiology, 276(3), 692-699. Rollo, C. D., Carlson, J. and Sawada, M. (1996). Accelerated aging of giant transgenic mice is associated with elevated free radical processes. Canadian Journal of Zoology, 74(4), 606-620. Rosa, M., Ward, J. E. and Shumway, S. E. (2018). Selective capture and ingestion of particles by suspensionfeeding bivalve molluscs: a review. Journal of Shellfish Research, 37(4), 727-746. Rosa, M., Ward, J. E., Ouvrard, M., Holohan, B. A., Espinosa, E. P., Shumway, S. E. and Allam, B. (2015). Examining the physiological plasticity of particle capture by the blue mussel, Mytilus edulis (L.): Confounding factors and potential artifacts with studies utilizing natural seston. Journal of Experimental Marine Biology and Ecology, 473, 207-217. Rubalcaba, J. G., Verberk, W. C., Hendriks, A. J., Saris, B. and Woods, H. A. (2020). Oxygen limitation may affect the temperature and size dependence of metabolism in aquatic ectotherms. Proceedings of the National Academy of Sciences, 117(50), 31963-31968. Saavedra, C., Milan, M., Leite, R. B., Cordero, D., Patarnello, T., Cancela, M. L. and Bargelloni, L. (2017). A microarray study of carpet-shell clam (Ruditapes decussatus) shows common and organ-specific growthrelated gene expression differences in gills and digestive gland. Frontiers in Physiology, 8, 943. Salomons, H. M., Mulder, G. V., van de Zande, L., Haussmann, M. F., Linskens, M. H. and Verhulst, S. (2009). Telomere shortening and survival in free-living corvids. Proceedings of the Royal Society B: Biological Sciences, 276(1670), 3157-3165. Santulli, G., Xie, W., Reiken, S. R.and Marks, A.R.(2015). Mitochondrial calciumoverloadis akey determinant General introduction 53 in heart failure. Proceedings of the National Academy of Sciences, 112(36), 11389-11394. Sarà, G. and Pusceddu, A. (2008). Scope for growth of Mytilus galloprovincialis (Lmk., 1819) in oligotrophic coastal waters (Southern Tyrrhenian Sea, Italy). Marine Biology, 156, 117-126. Sarrus, R. and Rameaux, N. (1839). Mathématique appliquée à la physiologie. Bull Acad R Méd, 3, 1094-1100. Sastry, A. N. (1975). Physiology and ecology of reproduction in marine invertebrates. In "Physiological Ecology of Estuarine Organisms" (F. J. Vernberg, ed.), pp. 279-299. Univ. of South Carolina Press, Columbia. Savage, V. M., Gillooly, J. F., Brown, J. H., West, G. B. and Charnov, E. L. (2004). Effects of body size and temperature on population growth. The American Naturalist, 163(3), 429-441. Schantz, T. V., Bensch, S., Grahn, M., Hasselquist, D. and Wittzell, H. (1999). Good genes, oxidative stress and condition–dependent sexual signals. Proceedings of the Royal Society of London. Series B: Biological Sciences, 266(1414), 1-12. Seed, R. and Suchanek, T.H. (1992). Population and Community Ecology of Mytilus. In: Gosling, E., Ed., The Mussel Mytilus: Ecology, Physiology, Genetics and Culture, Elsevier, London, 87-169. Segura, C. J., Montory, J. A., Cubillos, V. M., Diederich, C. M., Pechenik, J. A. and Chaparro, O. R. (2015). Brooding strategy in fluctuating salinity environments: oxygen availability in the pallial cavity and metabolic stress in females and offspring in the Chilean oyster Ostrea chilensis. Journal of Comparative Physiology B, 185, 659-668. Seo, E., Ohishi, K., Maruyama, T., Imaizumi-Ohashi, Y., Murakami, M. and Seo, Y. (2014). Magnetic resonance imaging analysis of water flow in the mantle cavity of live Mytilus galloprovincialis.Journal of Experimental Biology, 217(13), 2277-2287. Shick, J. M. and Dunlap, W. C. (2002). Mycosporine-like amino acids and related gadusols: biosynthesis, accumulation, and UV-protective functions in aquatic organisms. Annual review of Physiology, 64(1), 223-262. Shirneshan, G., Bakhtiari, A. R., Kazemi, A., Mohamadi, M. and Kheirabadi, N. (2012). Oyster Saccostrea cucullata as a biomonitor for Hg contamination and the risk to humans on the coast of Qeshm Island, Persian Gulf, Iran. Bulletin of environmental contamination and toxicology, 88, 962-966. Shumway, S. E., Cucci, T. L., Newell, R. C. and Yentsch, C. M. (1985). Particle selection, ingestion, and absorption in filter-feeding bivalves. Journal of experimental marine biology and ecology, 91(1-2), 77-92. Silvester, N. R. and Sleigh, M. A. (1984). Hydrodynamic aspects of particle capture by Mytilus.Journal of the Marine Biological Association of the united Kingdom, 64(4), 859-879. 54 General introduction Sokolova, I. and Pörtner, H. O. (2001b). Temperature effects on key metabolic enzymes in Littorina saxatilis and L. obtusata from different latitudes and shore levels. Marine Biology, 139, 113-126. Sokolova, I. M. and Pörtner, H. O. (2001a). Physiological adaptations to high intertidal life involve improved water conservation abilities and metabolic rate depression in Littorina saxatilis. Marine Ecology Progress Series, 224, 171-186. Stickle, W. B., Carrington, E. and Hayford, H. (2017). Seasonal changes in the thermal regime and gastropod tolerance to temperature and desiccation stress in the rocky intertidal zone. Journal of experimental marine biology and ecology, 488, 83-91. Stier, A., Bize, P., Habold, C., Bouillaud, F., Massemin, S. and Criscuolo, F. (2014). Mitochondrial uncoupling prevents cold-induced oxidative stress: a case study using UCP1 knockout mice. Journal of Experimental Biology, 217(4), 624-630. Storey, K. B. (1997). Organic solutes in freezing tolerance. Comparative Biochemistry and Physiology Part A: Physiology, 117(3), 319-326. Storey, K. B. and Storey, J. M. (1990). Metabolic rate depression and biochemical adaptation in anaerobiosis, hibernation and estivation. The Quarterly Review of Biology, 65(2), 145-174. Stuart, V., & Klumpp, D. W. (1984). Evidence for food-resource partitioning by kelp-bed filter feeders. Marine ecology progress series. Oldendorf, 16(1), 27-37. Suarez, R. K., Darveau, C. A. and Childress, J. J. (2004). Metabolic scaling: a many-splendoured thing. Comparative Biochemistry and Physiology Part B: Biochemistry and Molecular Biology, 139(3), 531-541. Tamayo, D., Azpeitia, K., Markaide, P., Navarro, E.andIbarrola, I. (2016). Food regimemodulatesphysiological processes underlying size differentiation in juvenile intertidal mussels Mytilus galloprovincialis.Marine Biology, 163, 1-13. Tamayo, D., Ibarrola, I. and Navarro, E. (2013). Thermal dependence of clearance and metabolic rates in slow-and fast-growing spats of manila clam Ruditapes philippinarum.Journal of Comparative Physiology B, 183, 893-904. Tamayo, D., Ibarrola, I., Cigarría, J. and Navarro, E. (2015). The effect of food conditioning on feeding and growth responses to variable rations in fast and slow growing spat of the Manila clam (Ruditapes philippinarum). Journal of Experimental Marine Biology and Ecology, 471, 92-103. Tamayo, D., Ibarrola, I., Urrutia, M. B. and Navarro, E. (2011). The physiological basis for inter-individual growth variability in the spat of clams (Ruditapes philippinarum). Aquaculture, 321(1-2), 113-120. General introduction 55 Tamayo, D., Ibarrola, I., Urrutxurtu, I. and Navarro, E. (2014). Physiological basis of extreme growth rate differences in the spat of oyster (Crassostrea gigas). Marine biology, 161, 1627-1637. Tammes, P. N. L. and Dral, A. D. G. (1955). Observations on the straining of suspensions by mussels. Archives Néerlandaises de Zoologie, 11, 87-112. Tamura, Y., Kawano, S. and Endo, T. (2020). Lipid homeostasis in mitochondria. Biological Chemistry, 401(6-7), 821-833. Theisen, B. F. (1977). Feeding rate of Mytilus edulis L.(Bivalvia) from different parts of Danish waters in water of different turbidity. Ophelia, 16(2), 221-232. Thompson, I., Jones, D. S. and Dreibelbis, D. (1980). Annual internal growth banding and life history of the ocean quahog Arctica islandica (Mollusca: Bivalvia). Marine Biology, 57, 25-34. Thompson, R. J. and Bayne, B. L. (1974). Some relationships between growth, metabolism and food in the mussel Mytilus edulis.Marine Biology, 27, 317-326. Thrush, S. F., Halliday, J., Hewitt, J. E. and Lohrer, A. M. (2008). The effects of habitat loss, fragmentation, and community homogenization on resilience in estuaries. Ecological applications, 18(1), 12-21. Thrush, S. F., Hewitt, J. E., Hickey, C. W. and Kelly, S. (2008). Multiple stressor effects identified from species abundance distributions: interactions between urban contaminants and species habitat relationships. Journal of Experimental Marine Biology and Ecology, 366(1-2), 160-168. Tomanek, L. (2010). Variation in the heat shock response and its implication for predicting the effect of global climate change on species’ biogeographical distribution ranges and metabolic costs. Journal of Experimental Biology, 213(6), 971-979. Toro, J. E. and Vergara, A. M. (1998). Growth and Heterozygosity in a 12-Month-Old Cohort of Ostrea chilensis Obtained by Mass Spawning in the Laboratory. Marine Ecology, 19(4), 311-323. Toro, J. E., Aguila, P. and Vergara, A. M. (1996). Spatial variation in response to selection for live weight and shell length from data on individually tagged Chilean native oysters (Ostrea chilensis Philippi, 1845). Aquaculture, 146(1-2), 27-36. Toro, J., Innes, D. J. and Thompson, R. J. (2004). Genetic variation among life-history stages of mussels in a Mytilus edulis–M. trossulus hybrid zone. Marine Biology, 145, 713-725. Turko, A. J., Robertson, C. E., Bianchini, K., Freeman, M. and Wright, P. A. (2014). The amphibious fish Kryptolebias marmoratus uses different strategies to maintain oxygen delivery during aquatic hypoxia and air exposure. Journal of Experimental Biology, 217(22), 3988-3995. 56 General introduction Ungvari, Z. and Csiszar, A. (2016). Intracerebral microhemorrhages in aging: role of increased oxidative stress and mmp activation. Journal of International Society of Antioxidants in Nutrition & Health, 1(1). Urrutia, M. B., Iglesias, J. I. P., Navarro, E. and Prou, J. (1996). Feeding and absorption in Cerastoderma edule under environmental conditions in the bay of Marennesoleron (Western France). Journal of the Marine Biological Association of the United Kingdom, 76(2), 431-450. Vahl, O. (1973). Pumping and oxygen consumption rates of Mytilus edulis L. of different sizes. Ophelia, 12(1-2), 45-52. Vaisman, A. G., Marins, R. V. and Lacerda, L. D. D. (2005). Characterization of the mangrove oyster, Crassostrea rhizophorae, as a biomonitor for mercury in tropical estuarine systems, northeast Brazil. Bulletin of Environmental Contamination & Toxicology, 74(3). Volckaert, F. and Zouros, E. (1989). Allozyme and physiological variation in the scallop Placopecten magellanicus and a general model for the effects of heterozygosity on fitness in marine molluscs. Marine Biology, 103, 51-61. Von Bertalanffy, L. (1957). Quantitative laws in metabolism and growth. The quarterly review of biology, 32(3), 217-231. Waldbusser, G. G., Hales, B., Langdon, C. J., Haley, B. A., Schrader, P., Brunner, E. L., ... and Hutchinson, G. (2015). Ocean acidification has multiple modes of action on bivalve larvae. PloS one, 10(6), e0128376. Waldbusser, G. G., Powell, E. N. and Mann, R. (2013). Ecosystem effects of shell aggregations and cycling in coastal waters: an example of Chesapeake Bay oyster reefs. Ecology, 94(4), 895-903. Wang, H., Lv, J., Zeng, Q., Liu, Y., Xing, Q., Wang, S., ... and Bao, L. (2021). Genetic differentiation and selection signatures in two bay scallop (Argopecten irradians) breeds revealed by whole-genome resequencing analysis. Aquaculture, 543, 736944. Wang, X., Meng, X., Song, B., Qiu, X. and Liu, H. (2010). SNPs in the myostatin gene of the mollusc Chlamys farreri: association with growth traits. Comparative Biochemistry and Physiology Part B: Biochemistry and Molecular Biology, 155(3), 327-330. Ward, J. E. and Shumway, S. E. (2004). Separating the grain from the chaff: particle selection in suspension-and deposit-feeding bivalves. Journal of Experimental Marine Biology and Ecology, 300(1-2), 83-130. Ward, J.E., Levinton, J.S., Shumway, S.E. and Cucci, T. (1998a). Particle sorting in bivalves: in vivo determination of the pallial organs of selection. Marine Biology, 131, 283 – 292. Ward, J.E., Newell, R.I.E., Thompson, R.J. and MacDonald, B.A. (1994b). In vivo studies of suspension-feeding General introduction 57 processes in the eastern oyster Crassostrea virginica (Gmelin). Biological Bulletin, 186, 221 – 240. Warren, C. E. and Davis, G. E. (1967). Laboratory studies on the feeding, bioenergetics, and growth of fish. Weinstein, J.E. (1995). Fine-structure of the digestive tubule of the eastern oyster, Crassostrea virginica (Gmelin, 1791). Journal Shellfish Research, 14, 97-104. White, C. R. (2011). Allometric estimation of metabolic rates in animals. Comparative Biochemistry and Physiology Part A: Molecular & Integrative Physiology, 158(3), 346-357. White, C. R. and Kearney, M. R. (2013). Determinants of inter-specific variation in basal metabolic rate. Journal of Comparative physiology B, 183, 1-26. White, C. R., Alton, L. A., Bywater, C. L., Lombardi, E. J. and Marshall, D. J. (2022). Metabolic scaling is the product of life-history optimization. Science, 377(6608), 834-839. White, C. R., Cassey, P. and Blackburn, T. M. (2007). Allometric exponents do not support a universal metabolic allometry. Ecology, 88(2), 315-323. White, C. R., Marshall, D. J., Alton, L. A., Arnold, P. A., Beaman, J. E., Bywater, C. L., ... and Ortiz-Barrientos, D. (2019). The origin and maintenance of metabolic allometry in animals. Nature Ecology & Evolution, 3(4), 598-603. Widdows, J. and Bayne, B. L. (1971). Temperature acclimation of Mytilus edulis with reference to its energy budget. Journal of the Marine Biological Association of the United Kingdom, 51(4), 827-843. Widdows, J. and Hawkins, A. J. S. (1989). Partitioning of rate of heat dissipation by Mytilus edulis into maintenance, feeding, and growth components. Physiological Zoology, 62(3), 764-784. Widdows, J. and Shick, J. M. (1985). Physiological responses of Mytilus edulis and Cardium edule to aerial exposure. Marine Biology, 85(3), 217-232. Widdows, J., Fieth, P. and Worrall, C. M. (1979). Relationships between seston, available food and feeding activity in the common mussel Mytilus edulis.Marine Biology, 50(3), 195-207. Wildish, D. and Kristmanson, D. (1997). Benthic suspension feeders and flow. 409. Wilson, J. J., Grendler, J., Dunlap-Smith, A., Beal, B. F. and Page, S. T. (2016). Analysis of Gene Expression in an Inbred Line of Soft-Shell Clams (Mya arenaria) Displaying Growth Heterosis: Regulation of Structural Genes and the NOD2 Pathway. International journal of genomics, 2016(1), 6720947. Winter, J. E. (1973). The filtration rate of Mytilus edulis and its dependence on algal concentration, measured by a continuous automatic recording apparatus. Marine Biology, 22(4), 317-328. 58 General introduction Winter, J. E. (1978). A review on the knowledge of suspension-feeding in lamellibranchiate bivalves, with special reference to artificial aquaculture systems. Aquaculture, 13(1), 1-33. Wolcott, T. G. and Wolcott, D. L. (2001). Role of behavior in meeting osmotic challenges. American zoologist, 41(4), 795-806. Worrall, C. M. and Widdows, J. (1984). Investigation of factors influencing mortality in Mytilus edulis L. Marine Biology Letters, (2). Wright, P.A. and Turko, A.J. (2016). Amphibious fishes: evolution and phenotypic plasticity. Journal of Experimental Biology, 219, 2245–2259. Xie, X., Teng, W., Sun, X., Liang, M., Du, S., Zhu, S., ... and Wang, Q. (2020). Transcriptomic analysis of the ark shell Scapharca kagoshimensis: De novo assembly and identification of genes and pathways involved growth. Aquaculture reports, 18, 100522. Yancey, P. H. (2005). Organic osmolytes as compatible, metabolic and counteracting cytoprotectants in high osmolarity and other stresses. Journal of experimental biology, 208(15), 2819-2830. Yonge, C. M. (1926). XV.—the Digestive Diverticula in the Lamellibranchs. Earth and Environmental Science Transactions of The Royal Society of Edinburgh, 54(3), 703-718. Zaldibar, B., Cancio, I. and Marigómez, I. (2008). Epithelial cell renewal in the digestive gland and stomach of mussels, season, age and tidal regime related variations. Histology and histopathology. Zeuthen, E. (1947). Body size and metabolic rate in the animal kingdom with special regard to the marine micro-fauna. C. R. Lab. Carlsberg, Ser. Chim., 26, 17-161. Zeuthen, E. (1953). Oxygen uptake as related to body size in organisms. The Quarterly Review of Biology, 28(1), 1-12. Zhang, L., Xu, N., Liu, X., Onxayvieng, K., Liu, L., Tang, R. and Li, D. (2021). Exercise training accelerates UPS-and mTOR-mediated protein turnover of grass carp Ctenopharyngodon idella. Aquaculture, 545, 737252. Zhang, M., Smith, J. A. C., Harberd, N. P. and Jiang, C. (2016). The regulatory roles of ethylene and reactive oxygen species (ROS) in plant salt stress responses. Plant molecular biology, 91, 651-659. Zhang, Y., Li, J., Qin, Y., Zhou, Y., Zhang, Y. and Yu, Z. (2017). A comparative study of the survival, growth and gonad development of the diploid and triploid Hong Kong oyster, Crassostrea hongkongensis (Lam & Morton 2003). Aquaculture Research, 48(5), 2453-2462. General introduction 59 Zhang, Y., Zhang, Y., Wang, Z., Yan, X. and Yu, Z. (2014). Phenotypic trait analysis of diploid and triploid hybrids from female Crassostrea hongkongensis ×male C. gigas.Aquaculture, 434, 307-314. Zhang, Z., Li, A., Zhang, K., Wang, C., Wang, W., Zhang, G. and Li, L. (2023). Accelerated energy metabolism plays an important role in Heterosis and maternal effect of hybrids bred from southern and northern Suminoe oysters (Crassostrea ariakensis).Aquaculture, 566, 739214. Zheng, Z., Hao, R., Xiong, X., Jiao, Y., Deng, Y. and Du, X. (2019). Developmental characteristics of pearl oyster Pinctada fucata martensii: insight into key molecular events related to shell formation, settlement and metamorphosis. BMC genomics, 20, 1-11. Zippay, M. L. and Helmuth, B. (2012). Effects of temperature change on mussel, Mytilus. Integrative Zoology, 7(3), 312-327. Zouros, E. and Foltz, D. W. (1987). The use of allelic isozyme variation for the study of heterosis. Isozymes: Current Topics Biological Medical Research, 13, 1-59. Zouros, E., Romero-Dorey, M. and Mallet, A. L. (1988). Heterozygosity and growth in marine bivalves: further data and possible explanations. Evolution, 42(6), 1332-1341. Zouros, E., Singh, S. M. and Miles, H. E. (1980). Growth rate in oysters: an overdominant phenotype and its possible explanations. Evolution, 856-867. 60 General introduction Chapter 1: Differential tissue development compromising growth phenotypes 67 ration. However, if a better understanding of the growing patterns is pursued, research should be done on the implications of those physiological differences at other biological organisation levels. As stated above, variation in the growth of mussels has implications for both individual fitness and population dynamics. Comprehending such variation would be valuable for conservation and management and, therefore, wouldhelp improveaquaculture production(Kendall and Fox, 2002). Herewe tacklethe individualvariation in the growth of mussels from a multidisciplinary approach to obtain a holistic understanding of the organization and function of the growing patterns. The work aims to establish a connection between the physiological performances of the different growing profiles, and the tissue structure and cellular activity of the two main organs involved in energy acquisition and processing. 2 Materials and methods 2.1 Collection of mussel seeds and experimental setup Mussel seeds, Mytilus galloprovincialis, were collected in February 2020 from monolayer mussel beds growing in a rocky intertidal area located in Ibarrangelu (Biscay, Spain, 43°24’ N; 2°40’ W). Mussels were transferred to the laboratory in air-exposed wet containers at ambient temperature. At the laboratory, the shell length of all the individuals was measured with electronic calipers and 300 homogeneously sized individuals (shell length of 10.98 ±0.52 mm) were sorted for experiments and placed in a tank (50 L) at constant seawater salinity (33 PSU) and temperature (18 °C). The selected seeds were reared in the laboratory during a 3-month period under a constant food supply that consisted of a suspension of cultured algae Isochrysis galbana (T-Iso) constantly dosed at 20,000 cells · mL -1 . The concentration was maintained stable by frequently checking with a Coulter Multisizer 3 and homogeneity ensured with air circulation. During the rearing period, the tanks were cleaned up and seawater-renewed twice a week. When cleaned, mussels were separated from one another by gently cutting the byssus to avoid inter-individual competition for food. The first week of the rearing period, the clearance rate and the oxygen consumption was determined in 20 randomly selected individuals. Those same individuals were then dissected for histological analysis. The remaining set of mussel seeds was maintained for three months. After this period, the largest 40 (fast-growers – F), the 40 medium-sized mussels (intermediate growers – I) and the smallest 40 (slow-growers – S) were selected to be acclimatized under two different food-rations for two weeks. Half of the mussels (n = 20 for each growing condition) were fed with a high ration (50,000 cells · mL -1 ) and the other half with a low ration (10,000 cells ·mL-1). 68 Chapter 1: Differential tissue development compromising growth phenotypes After theacclimation period, 10individuals from eachgroup abovewere usedto measurethe maincomponents of the energy balance (clearance rate –CR– and routine metabolic rate –RMR–). Once the physiological measurements were completed, whole animal flesh (for the smallest individuals) and a cross section including mantle, gills and digestive gland (for the medium-size and largest mussels) were extracted for histological examination. The gills of 10 additional mussels from each of those six groups were frozen in liquid nitrogen and stored at - 80 °C for biochemical analysis. Figure 1. Shell-length distribution of the mussels upon arrival to the laboratory (initial size) and after three months (final size). The shaded areas delimit the size range of the selected F, I and S mussels; their corresponding shell-lengths (mm) and live weights (g) (mean ±standard deviation) are indicated. 2.2 Biometry The shell-lengths and live weights of individual mussels were measured once every two weeks using 0.05 mm accuracy calipers and a 0.01 mg accuracy balance. 2.3 Physiological parameters 2.3.1 Clearance rate (CR: L ·h-1) Clearance rate was measured by placing the mussels in experimental glass bottles of 250 mL with rounded edges, the flow rates of which were adjusted to obtain a reduction of 15–30 % on the particle concentration Chapter 1: Differential tissue development compromising growth phenotypes 69 compared with the control chamber. Samples of water in the outflow of individual and control chambers were taken every hour during 11–12 h. Thus, the CR of each individual was calculated as the mean value of 11–12 determinations during the whole day, and according to the expression proposed by Hildreth and Crisp (1976): CR =F·((Ci−C0)/Ci) where F is the flow rate (L · h -1 ), Ci is the particle concentration in the control outflow and C0 the particle concentration in the outflow of the experimental chamber. Particle concentrations were determined with a Counter Coulter Z1. 2.3.2 Metabolic expenditure (RMR: mL O2·h-1) Routine metabolic rate was assessed by measuring oxygen consumption. Mussels were removed from feeding chambers and introduced into respirometers of around 50 mL sealed with LDO oxygen probes connected to oximeters (HATCH HQ40d). Rates of oxygen consumption were computed from the decline in oxygen concentration in the chambers registered during 3–4 h, or until values decreased 20–30 % of initial baseline, every 5–10 min. A control chamber was used to check the stability of the oxygen concentration. 2.3.3 Size standardization of physiological rates CR and RMR were standardised to a common live weight of 1 g, according to the expression: YST D = (1/WEXP )b·YEXP in which YST D and YEXP represent, respectively, standard and experimental physiological rates and WEXP representstheexperimental liveweightoftheindividual. The power valuesused to scale physiological rates to body weight (b) were 0.58 (Bayne and Hawkins, 1997) for CR and 0.724 (Bayne et al., 1973) for RMR. 2.4 Gill surface-area (GA: mm2·g-1) Photographs of the gill of 20 mussels were taken with a digital camera and the surface area of the gills from each individual was calculated using ImageJ software (National Institutes of Health). As a means to ensure correct sizing, millimetric paper was placed under the mussel when taking the photograph. Data shown correspond to one side of the demibranch. Gill areas were standardised for an equivalent of 1 g live-weight mussel according to the formula: GAST D = (1/WEXP )b·GAEXP 70 Chapter 1: Differential tissue development compromising growth phenotypes where GAST D and GAEXP represent the standardized and experimental gill areas, respectively, and WEXP is the experimental live weight of the mussel. The power function used to scale gill area to live weight was 0.66 (Vahl, 1973; Hawkins and Bayne, 1992; Jones et al., 1992). 2.5 Histology The whole organisms or cross sections (n = 10 per experimental group) were fixed in seawater with 4 % formaldehyde, dehydrated in an ethanol bath series, paraffin-embedded using a Leica ASP3005 tissue processor and sectioned at 5 with a Leica RM2125RTS microtome. Paraffin sections were stained with two different staining procedures. On the one hand, hematoxylin-eosin (H/E) staining was used to analyze the digestive gland, gills and mantle. On the other hand, toluidine-eosin staining was employed to better discriminate basophilic cells in the digestive gland (Blanco-Rayón et al., 2019). 2.5.1 Digestive gland assessment The digestive tissue ratio (CTD), the changes in volume density of basophilic cells (VvBAS) and the atrophy of the epithelium of the digestive alveoli were measured. CTD and VvBAS were quantified through stereology, by counting three randomly selected fields in each slide at 40×objective (final magnification 400×) and employing a drawing tube attached to a light microscope. A simplified version of the Weibel graticule multipurpose test system M-168 (Weibel, 1989) was used to record the hits on basophilic cells (b), digestive cells (d), diverticular lumens (l) and interstitial connective tissue (c). CTD ratio was calculated as CTD = c/(b + d + l). VvBAS was computed following Delesse’s principle (Weibel, 1989), as VvBAS /VEP, where VvBAS is the volume of basophilic cells and VEP the volume of digestive gland epithelium. Following Kim et al. (2006), a grading from 0 to 4 was used to calculate the atrophy index of the digestive alveoli. In that classification, 0 means normal digestive diverticula with nearly occluded lumen; 1 means co-occurrence of normal and partially atrophied tubules of epithelium thickness greater than one-half of normal; 2 means digestive epithelium thickness half of normal; 3 means significantly atrophied tubules with digestive epithelium less than half as thick as normal, and 4 means that digestive epithelium is extremely thin and nearly all tubules are affected. 2.5.2 Adipogranular cell density The adipogranular (ADG) cell density was estimated as described by Bignell et al. (2008) using a grading system, where 0 means no ADG cells apparent within vesicular connective tissue, 1 means ADG cells can be seen but they appear to be scarce, 2 means ADG cells appear scattered throughout mantle tissue, 3 means Chapter 1: Differential tissue development compromising growth phenotypes 71 there is a marked increase in the abundance of ADG cells and some areas may not appear to show absolute consistency, and 4 means ADG cells can be seen to constitute the majority of connective tissue volume. 2.5.3 Gill structure To assess the gill structure a grading system was designed based on the frontal and latero-frontal cilia density and epithelium organization (Table 1). Normal cilia density in most lamella and well-organized epithelium was graded with the highest score. When average cilia density was less than normal in most lamella, but epithelium was still well organized, the scoring lowered to one. The scoring was the lowest when average cilia density was less than normal in nearly all lamella and the epithelium showed an evident disorganization. Table 1. Semi-quantitative scale for gill structure assessment. Score Description 0Frontal and latero-frontal cilia density is low, and cell damage and a disorganized epithelium is evident 1Frontal and latero-frontal cilia density is low but the epithelium is well organized 2Frontal and latero-frontal cilia density is high and the epithelium is well organized 2.6 Biochemical determinations in the gill Gills of 10 mussels from each of the six experimental groups were individually homogenised in 0.05 M potassium phosphate buffer (pH 7.0). The homogenate was centrifuged at 10,000 g for 20 min at 4 °C and the supernatants were stored at - 80 °C until analysis. The gill samples were analysed for glutathione S-transferase (GST), catalase (CAT) and cytochrome c oxidase (COX) enzymes. All enzyme activities were measured in 96-well plates using a microplate reader (TECAN Infinite 200), analysed using Magellan software (TECAN) and were expressed as a function of the protein concentration in the samples. The protein concentration was determined in triplicate according to Bradford’s method adapted to a microplate and using γ -bovine globulins as standard (Guilhermino et al., 1996). CAT activity was measured as degradation of hydrogen peroxide (H 2 O 2 , Fluka 95302) mediated by CAT at 240 nm (Claiborne, 1985). GST activity was measured as the formation rate of the conjugated substrate chlorodinitrobenzene-glutathione (CDNB-GSH) at 340 nm, according to Habig et al. 1974. When measuring COX activity, in brief, isolation and assay conditions were as follows: homogenization buffer: 25 mM potassium phosphate, pH 7.2, 10 µg/ml PMSF, 2 µg/ml aprotinin; assay: 20 mM potassium phosphate, pH 7.0, 16 µM reduced cytochrome c(II), 0.45 mM n-dodecyl-b-d-maltoside, 2 µg/ml antimycin A; acquisition wavelength: 550 nm. 72 Chapter 1: Differential tissue development compromising growth phenotypes 2.7 Statistical analysis Data was evaluated first for normality and homoscedasticity by means of Shapiro-Wilk and Levene’s test, respectively. In those cases where normality was not followed, data were logarithmically transformed after which normality was held. Significant effects exerted by growth-condition (F, I or S) and food ration (high or low) on physiological and histological measurements were analyzed employing a two-way ANOVA. As a post hoc Tukey (homogeneity of variances) or Games-Howell (no homogeneity of variances) tests were applied. Semi-quantitatively gathered data was analyzed through non-parametric tests. For Kruskal-Wallis, Dunn’s test was applied as post hoc. Statistical analyses were performed using IBM SPSS Statistics 25. Covariance analysis (ANCOVA; Zar, 2010) was used to test the significance of differences between regression coefficients for the different growth rates. 3 Results 3.1 Growth rate of fast and slow growers Inter-individual differences in the growth rates were evident enough after 3 months as to easily select fast, intermediate and slow growers. F individuals were 3.5 times heavier than S individuals were, and their shell length was almost 70 % larger than S mussels shells (Fig. 1). Indeed, if the growth rates (mm·day -1 ) of the selected mussels are computed by adjusting linear regression models to the variations of the mean values of shell lengths with time, the following equations arise: Fast growers: 0.163 (±0.002) x time (days) + 10.979 (±0.057), F = 8899.1, p < 0.001 Intermediate growers: 0.110 (±0.001) x time (days) + 10.979 (±0.036), F = 9218.2, p < 0.001 Slow growers: 0.052 (±0.001) x time (days) + 10.979 (±0.038), F = 1817.9, p < 0.001 Under maintenance conditions, fast growers grew an average of 0.163 mm· -1 , intermediate growers 0.110 mm· -1 and slow growers 0.052 mm· -1 . Analysis of covariance revealed significant differences for the slopes (slope test: F value = 1066.038, df = 1026, p < 0.05), and multiple comparison among slopes revealed that the three of them were statistically different from one another (bF vs. bS: q = 79.972, p < 0.05; bF vs. bI: q = 38.619, p < 0.05; bS vs. bI: q = 40.678, p < 0.05). Chapter 1: Differential tissue development compromising growth phenotypes 73 3.2 Physiological components of the energy balance 3.2.1 Clearance rate (CR: L ·h-1 ·g-1) Fast-growing individuals attained significantly 2 times higher CR values than their slow-growing counterparts did(0.429 ±0.19 L·h -1 ·g -1 vs. 0.216±0.12L ·h -1 ·g -1 , respectively), whileI individuals displayed intermediate values (0.321 ±0.15 L ·h -1 ·g -1 ) not different to those of F and S mussels (Fig. 2). For both food rations, the three growth-condition groups followed a quite similar pattern. CR values were significantly 2 times higher in the mussels fed with the low-concentrated ration (0.411 ±0.16 L ·h -1 ·g -1 ) when compared to the mussels fed the high food ration (0.233 ±0.15 L ·h -1 ·g -1 ). Accordingly, the two-way ANOVA showed in Fig. 2 indicates that both growth condition and ration, but not the interaction, exerted a significant effect on the CR of the mussels. The mean CR of mussels recorded during the first week of the experiment is shown in the figure for comparative purposes. Although no attempt of statistical testing has been made, the maintenance of mussels in the laboratory under the condition of continuous feeding exerted a positive effect upon the CR in F an I mussels, but not S mussels. 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1 CR (L · h-1) IS F I S Low High F Initial Figure 2. Clearance rate (L ·h -1 ·g -1 ) of fast (F: dark grey), intermediate (I: light grey) and slow (S: white) growing mussels for low-concentrated (maize yellow) and high-concentrated (blue) rations. The clearance rate from the initial determination is also depicted. Intervals indicate standard deviation. On the top, the two-way factor ANOVA testing significant effects of growth condition (F, I or S) and ration (Low or High) is shown. 74 Chapter 1: Differential tissue development compromising growth phenotypes 3.2.2 Routine metabolic rate (RMR: mL O2·h-1 ·g-1) Mean values of routine metabolic rate are plotted in Fig. 3. The oxygen consumption of mussels was found to decrease sharply during the rearing period. The mean RMR value was 0.09 ±0.017 mL O 2 ·h -1 ·g -1 during the first week at the laboratory and trebled that of the mean oxygen consumption recorded for selected F, I and S mussels: 0.03 ±0.005 mL O 2 ·h -1 ·g -1 . The two-factor ANOVA indicates that neither the growth condition nor the food ration factors exerted any significant effect on the RMR. 0.00 0.02 0.04 0.06 0.08 0.10 0.12 Media VO2(mL· h-1 ·g-1) Initial IS F I S Low High F Figure 3. Oxygen consumption (mL O 2· h -1· g -1 ) of fast (F: dark grey), medium (I: light grey) and slow (S: white) growing mussels for low-concentrated (maize yellow) and high-concentrated (shappire blue) rations. The oxygen consumption from the initial determination is also depicted. Intervals indicate standard deviation. On the top, the two-way factor ANOVA testing significant effects of growth condition (F, I or S) and ration (Low or High) is shown. 3.3 Gill surface-area (GA: mm2·g-1) Mean values (±SD) of the gill surface-area and the two-way factor ANOVA are shown in Fig. 4. The two-way ANOVA indicates that irrespective of the ration, there are differences among the gill surface-area values of the growing groups. Tukey test revealed that F mussels had significantly 40 % larger gill surface-area than S mussels (p < 0.001): average value of F growers is around 70 mm 2 ·g -1 , whereas that of S mussels about 40 mm 2 ·g -1 . The value of intermediate growers falls down to a mid-value of around 56 mm 2 ·g -1 , which is significantly different from the value of S mussels (p < 0.001), but not from that of F mussels (p = 0.077), according to post hoc tests. Chapter 1: Differential tissue development compromising growth phenotypes 75 Gill area (mm2· g-1) 0 20 40 60 80 100 120 . F I S blanc F I S IS F I S Low High F Figure 4. Gill surface-area (mm 2 ·g -1 ) of fast (F: dark grey), intermediate (I: light grey) and slow (S: white) growing mussels for low-concentrated (maize yellow) and high-concentrated (shappire blue) rations. Intervals indicate standard deviation. On the top, the two-way ANOVA testing significant effects of growth condition (F, I or S) and ration (Low or High) is shown. 3.4 Histological analysis of the digestive gland The results of the stereological analysis of the digestive gland of F, I and S mussels fed low and high food concentrations are compiled in Table 2, together with a summary of the two-factor analysis of variance. The initial values of each parameter are also shown. Table 2. Tissue-level biomarkers measured in fast (F), medium (I) and slow (S) growing mussels fed low and high concentrated food rations. CTD ratio: Connective to Digestive ratio; VvBAS : basophilic cell volume density. Mean values (±SD) are presented together with a summary of two-factor ANOVA testing significant effects of growth condition and experimental food-ration. N = 10 each experimental group. Initial values are shown on the left. Tissue-level Initial Growth Low concentration High concentration Source of interaction biomarkers group (10,000 cells·mL-1) (50,000 cells·mL-1) Mean (±SD) Mean (±SD) Growth condition Ration Interaction CTD ratio 0.071 (±0.07) F0.163 (±0.12) 0.173 (±0.11) DF = 2 DF = 1 DF = 2 I0.344 (±0.21) 0.119 (±0.08) F = 34.41 F = 11.34 F = 8.48 S0.638 (±0.61) 0.399 (±0.26) p = 0.000 p = 0.001 p = 0.000 VvBAS 0.213 (±0.06) F0.351 (±0.07) 0.241 (±0.06) DF = 2 DF = 1 DF = 2 I0.232 (±0.07) 0.288 (±0.07) F = 19.79 F = 3.67 F = 13.72 S0.401 (±0.12) 0.366 (±0.15) p = 0.000 p = 0.057 p = 0.000 76 Chapter 1: Differential tissue development compromising growth phenotypes 3.4.1 Connective-to-digestive (CTD) ratio of the digestive gland Growth condition, food ration and the interaction term exerted significant effects on the CTD ratio. Mean CTD in S mussels (0.518 ±0.44) was almost 3 times higher than that in fast (0.168 ±0.11) and intermediate (0.232 ±0.14) growers (Fig. 5: A,B), being that difference significant. The mussels fed low concentrated ration attained approximately 1.5 times higher CTD values (0.382 ±0.31) than mussels fed high food ration (0.230 ±0.15). However, ration affected the CTD values of both I and S mussels (Table 3) but not F mussels, thus resulting in a significant interaction. 3.4.2 Volume density of basophilic cells (VvBAS) Growth condition significantly affected VvBAS :post hoc Tukey test showed that S individuals had significantly lower values than F and I growers (S vs. F: p = 0.000; S vs. I: p = 0.000), being this last two statistically equal to each other (F vs. I: p = 0.089). Although there is an upward trend of the mean VvBAS value as the food ration decreases, the differences between rations did not achieve the significance (p = 0.057). The interaction term was found to be significant. 3.4.3 Atrophy index of digestive alveoli The mean values for the atrophy index of the digestive alveoli are presented in Fig. 6A, along with a summary of the K–W test. The test indicates the existence of significant differences in the atrophy index between mussels of different growth-condition: slow-growing mussels had significantly fewer adipogranular cells than fast and intermediate growers did (Dunn’s test results: F vs. S: p = 0.000; I vs. S: p = 0.016; F vs. I: p = 0.176) (Fig. 5: C,D). No effect was exerted by the ration factor. 3.5 Histological analysis of the gill In Table 3, the mean values for the semi-quantitative analysis of the gill appearance are shown. Growth category exerted a significant effect on gill structure index, where slow growers had a lower frontal and laterofrontal cilia density and a disorganized structure of the epithelium when compared to fast and intermediate growers (Dunn’s test results: S vs. F: p = 0.000; S vs. I: p = 0.004; F vs. I: p = 0.325) (Fig. 5: E,F). No significant differences were found between the gill appearances of mussels fed under different rations. Moreover, the initial value obtained is closer to that of F and I mussels than to that of S individuals. Chapter 1: Differential tissue development compromising growth phenotypes 83 The morphometric parameters included in the histological analysis reflect the digestive potential of the differentially growing organisms. In S mussels, the digestive diverticula were evidently reduced in number, and appeared scattered and surrounded by ample areas of connective tissue. A high CTD value indicates a loss of integrity of the digestive gland, which has been linked, among others, to poor nutritive status (Mújica et al., 2015). Actually, at a low food ration, the mean CTD value was significantly higher than at a high food ration. A lower proportion of digestive diverticula means a lower proportion of effective tissue to process food. The low number of digestive diverticula that S mussels have appear to display a high level of atrophy typically characterized by an extreme thinning of the digestive tubules, where the digestive cells are overly fragmented. Degeneration of digestive cells has been reported in several mollusk species subjected to environmental stress (e.g., Syasina et al., 1997), and both atrophy and changes in the morphology of the digestive alveoli constitute a non-specific response to stressful environmental conditions (Benito et al., 2019; Kim et al., 2006). Regarding the cell type composition of the diverticula, S mussels showed a significantly higher density of basophilic cells. Under good physiological conditions, the digestive cells outnumber the basophilic cells, which is the case for F and I mussels in this study under both food rations. In S mussels, conversely, the relative occurrence of basophilic cells is apparently augmented due to digestive cell loss, a condition that is typical when mussels are subdued to stressful situations (Soto et al., 2002; Zaldibar et al., 2008). Therefore, even though S mussels have not been subdued to any stress, and they have been kept under the same conditions that F growers, they still possess degeneration traits that resemble those seen in healthy animals experimentally or naturally stressed. Compared to slow growers, fast growers display a better-equipped digestive tissue to process food altogether. The inherent differences between growing groups are so demonstrated, supporting the physiological data. Understanding the process of inter-individual growth rate differentiation requires comparing the initial values and those recorded three months later, once the size-differentiation occurred, as suggested by FuentesSantos et al. (2018). Initial values of gill appearance are among the highest scores, whereas digestive tissue atrophy, CTD and VvBAS are among the lowest, thus indicating an optimal initial condition. Indeed, gonadal development was observed in the samples taken for the initial determination, which resulted in a massive spawning event after a few days in the laboratory. After laboratory conditioning, mussels reduced oxygen consumption, indicating a general improvement of the energy balance, a reduction that could be linked to the loss of gonadal tissue. It cannot be discarded as well a higher RMR at the beginning due to the acclimation to the laboratory. However, only F and I mussels increased their CR values. Histological analysis revealed that while F mussels maintained relatively similar values to the initial ones, S mussels have gill and digestive tissues that at some point started deteriorating. Actually, not only somatic growth was notably diminished, but also the accumulation of energy reserves: while in almost all F mussels adipogranular tissue was observed in the mantle (and even between the digestive diverticula), S mussels did not show such accumulation. In fact, the near absence of adipogranular tissue in S mussels was utterly independent of the ration, which goes along 84 Chapter 1: Differential tissue development compromising growth phenotypes with the aforementioned idea that not even a considerable increase in food concentration is sufficient for S mussels to make up for their deteriorated tissues. Although more studies should be performed to detail the underlying causes, the loss of functional digestive capacity in S mussels could be the consequence of the previously discussed constrain in the filtering activity or, alternatively, could stem from a cell-damage in the digestive gland similar to that observed in the gill. For the intermediate growers that show the behaviour of the bulk of the population, a trend is apparent: when mussels are fed a low food ration, I individuals remain halfway between the values displayed by F and S mussels; whereas at a high food ration I mussels almost match the values attained by F growers. In some parameters, that unalike behaviour is reflected statistically as an interaction. If the inter-individual differences recorded stemmed just from the S growers suffering a deterioration process, F and I growers should be expected to display similar performances and to have a similar appearance under the microscope. However, this is not the case. This may indicate that under conditions of high food availability, food ingestion of I mussels would not be compromised by their lower filtration ability. Hence, they would be even able to process and accumulate as many reserves as their F growing counterparts. It also brings forth the higher capacity that some mussels have to develop as F mussels even at low food rations. The histological and biochemical characterization in this study complements the physiological data that points at differences in the food-acquisition rates and metabolic costs as determinants for inter-individual growth variability. The structural and functional differences found in S mussels suggest that their degenerated tissues or damaged cells impede the proper acquisition, digestion and absorption of food. This results, as a consequence, in the inability to face any nutritional event. On the contrary, F mussels stand out for their plasticity since, by keeping their histological and biochemical parameters virtually constant, they are able to obtain energy in the most efficient way under any ration. This study serves as a starting point for field experiments testing the tissue and cellular organization of the different growing profiles in nature, including the effects that environmental conditions may impose. Furthermore, growth variability in nature is a major target of developing efficient aquaculture systems, and understanding the population dynamics will be relevant for such developments to happen. References Babarro, J. M., Fernández-Reiriz, M. J. and Labarta, U. (2000). Metabolism of the mussel Mytilus galloprovincialis from two origins in the Ría de Arousa (north-west Spain). Journal of Marine Biology Association UK, 80, 865–872. Bayne, B. L. and Hawkins, A. J. (1997). Protein metabolism, the costs of growth, and genomic heterozygosity: Chapter 1: Differential tissue development compromising growth phenotypes 85 experiments with the mussel Mytilus galloprovincialis Lmk. Physiological Zoology, 70, 391-402. Bayne, B. L., Hawkins, A. J. S. and Navarro, E. (1987). Feeding and digestion by the mussel Mytilus edulis L. (Bivalvia). Journal of Experimental Marine Biology and Ecology, 111, 1-22. Bayne, B. L., Hedgecock, D., McGoldrick, D. and Rees, R. (1999). Feeding behaviour and metabolic efficiency contribute to growth heterosis in Pacific oysters [Crassostrea gigas (Thunberg)]. Journal of Experimental Marine Biology and Ecology, 233, 115-130. Bayne, B. L., Svensson, S. and Nell, J. A. (1999). The physiological basis for faster growth in the Sydney rock oyster, Saccostrea commercialis.Biological Bulletin, 197, 377-387. Bayne, B. L., Thompson, R. J. and Widdows, J. (1973). "Some effects of temperature and food on the rate of oxygen consumption by Mytilus edulis L." in Effects of temperature on ectothermic organisms, ed. W. Wieser (Berlin, Heidelberg: Springer), 181-193. Benito, D., Ahvo, A., Nuutinen, J., Bilbao, D., Saenz, J., Etxebarria, N., Lekube, X., Izagirre, U., Lehtonen, K. K., Marigómez, I., Zaldibar, B. and Soto, M. (2019). Influence of season-depending ecological variables on biomarker baseline levels in mussels (Mytilus trossulus) from two Baltic Sea subregions. Science of Total Environment, 689, 1087-1103. Bignell, J. P., Dodge, M. J. Feist, S. W., Lyons, B., Martin, P. D., Taylor, N. G. H., Stone, D., Travalent, L. and Stentiford, G. D. (2008). Mussel histopathology, effects of season, disease and species. Aquatic Biology, 2, 1-15. Blanco-Rayón, E., Guilhermino, L., Irazola, M., Ivanina, A. V., Sokolova, I. M., Izagirre, U. and Marigómez, I. (2019). The influence of short-term experimental fasting on biomarker responsiveness in oil WAF exposed mussels. Aquatic Toxicology, 206, 164-175. Blanco-Rayón, E., Soto, M., Izagirre, U. and Marigómez, I. (2019). Enhanced discrimination of basophilic cells on mussel digestive gland tissue sections by means of toluidine-eosin staining. Journal Invertebrate Pathology, 161, 29-39. Brown, J. R. (1988). Multivariate analyses of the role of environmental factors and seasonal and site-related growth variation in the Pacific oyster, Crassostrea gigas.Marine Ecology Progress Series, 45, 225-236. Cartier, S., Pellerin, J.., Fournier, M., Tamigneaux, E., Girault, L. and Lemaire, N. (2004). Use of an index based on the blue mussel (Mytilus edulis and Mytilus trossulus) digestive gland weight to assess the nutritional quality of mussel farm sites. Aquaculture, 241, 633-654. Claiborne, A. (1985). "Catalase activity" in CRC Handbook of Methods for Oxygen Radical Research, ed. R. A. 86 Chapter 1: Differential tissue development compromising growth phenotypes Greenwald (Boca Raton, FL: CRC Press), 283-284. Fernández-Reiriz, M. J., Irisarri, J. and Labarta, U. (2016). Flexibility of physiological traits underlying interindividual growth differences in intertidal and subtidal mussels Mytilus galloprovincialis.PLoS One, 11, e0148245. Fuentes-Santos, I., Labarta, U. and Fernández-Reiriz, M. J. (2018). Characterizing individual variability in mussel (Mytilus galloprovincialis) growth and testing its physiological drivers using Functional Data Analysis. PLoS ONE, 13, e02059812. Gaffney, P. M. and Scott, T. M. (1984). Genetic heterozygosity and production traits in natural and hatchery populations of bivalves. Aquaculture, 42, 289-302. Gonçalves, J. M., Rocha, T., Mestre, N. C., Fonseca, T. G. and Bebianno, M. J. (2020). Assessing cadmium-based quantum dots effect on the gonads of the marine mussel Mytilus galloprovincialis.Marine Environmental Research, 156, 104904. Gu, Z., Shi, Y., Wang, Y. and Wang, A. (2011). Heritable characteristics in the pearl oyster Pinctada martensii: comparisons of growth and shell morphology of Chinese and Indian populations, and reciprocal crosses. Journal of Shellfish Research, 30, 241–246. Guilhermino, L., Lopes, M. C., Carvalho, A. P. and Soared, A. M.V. M. (1996). Inhibition of acetylcholinesterase activity as effect criterion in acute test with juvenile Daphnia magna.Chemosphere, 32, 727-738. Habig, W. H., Pabst, M. J. and Jakoby, W. B. (1974). Glutathione S-transferases. The first enzymatic step in mercapturic acid formation. Journal of Biological Chemistry, 249, 7130-7139. Hawkins, A. J. S. and Bayne, B. L. (1992). "Physiological processes, and the regulation of production" in The Mussel Mytilus: Ecology, Physiology, Genetics and Culture, ed. E. Gosling (Amsterdam: Elsevier Science Publishers), 171-222. Hayes, J. D. and McLellan, L. I. (1999). Glutathione and glutathione-dependent enzymes represent a coordinately regulated defense against oxidative stress. Free Radical Research, 31, 273-300. Hellou, J., Ross, N. W. and Moon, T. W. (2012). Glutathione, glutathione S-transferase, and glutathione conjugates, complementary markers of oxidative stress in aquatic biota. Environmental Scientific Pollution Research, 19, 2007-2023. Hildreth, D. I. and Crisp, D. J. (1976). A corrected formula for calculation of filtration rate of bivalve molluscs in an experimental flowing system. Journal of Marine Biological Association, 56, 111-120. Honkoop, P.J. C. (2003). Physiological costs of reproduction in the Sydney rock oyster Saccostrea glomerata. Chapter 1: Differential tissue development compromising growth phenotypes 87 Oecologia, 135, 176-183. Hüttemann, M., Lee, I., Samavati, L., Yu, H. and Doan, J. W. (2007). Regulation of mitochondrial oxidative phosphorylation through cell signalling. Biochimica et Biophysica Acta (BBA) - Molecular Cell Research, 1773, 1701-1720. Ibarrola, I., Etxeberria, M., Iglesias, J. I. P., Urrutia, M. B. and Angulo, E. (2000). Acute and acclimated digestive responses of the cockle Cerastoderma edule (L.) to changes in the food quality and quantity. II. Enzymatic, cellular and tissular responses of the digestive gland. Journal of Experimental Marine Biology and Ecology, 252, 199-219. IBM Corp. Released 2017. IBM SPSS Statistics for Windows, Version 25.0. Armonk, NY: IBM Corp. Jones, H. D., Richards, O. G. and Southern, T. A. (1992). Gill dimensions, water pumping rate and body size in the mussel Mytilus edulis L. Journal of Experimental Marine Biology and Ecology, 155, 213-237. Kendall, B. E. and Fox, G. A. (2002). Variation among individuals and reduced demographic stochasticity. Conservation Biology, 16, 109-116. Kim, Y., Ashton-Alcox, K. A. and Powell, E. N. (2006). Histological Techniques for Marine Bivalve Molluscs: Update. Silver Spring, MD. NOAA Technical Memorandum, 76 pp. Kratzer, E., Tian, Y., Sarich, N., Wu, T., Meliton, A., Leff, A. and Birukova, A. A. (2012). Oxidative stress contributes to lung injury and barrier dysfunction via microtubule destabilization. American Journal of Respiration Cell and Molecular Biology, 47, 688-697. Labarta, U., Fernández-Reiriz, M. J. and Babarro, J. M. (1997). Differences in physiological energetics between intertidal and raft cultivated mussels Mytilus galloprovincialis.Marine Ecology Progress Series, 152, 167-173. Li, Q., Wang, Q., Liu, S. and Kong, L. (2011). Selection response and realized heritability for growth in three stocks of the Pacific oyster Crassostrea gigas.Fishing Sciences, 77, 643–648. Mallet, A. L. and Haley, L. H. (1983). Growth rate and survival in pure population mating and crosses of the oyster Crassostrea virginica.Canadian Journal of Fishing and Aquatic Sciences, 40, 948–954. Manduzio, H., Rocher, B., Durand, F., Galap, C., Leboulenger, F. (2005). The point about oxidative stress in molluscs. Invertebrate Survival Journal, 2, 91-104. Morley, S. A., Lurman, G. J., Skepper, J. N., Pörtner, H-O. and Peck, L. S. (2009). Thermal plasticity of mitochondria: a latitudinal comparison between Southern Ocean molluscs. Comparative Biochemistry and Physiology Part A Molecular Integrative Physiology, 152, 423-430. 88 Chapter 1: Differential tissue development compromising growth phenotypes Morton, B. (1983). "Feeding and digestion in Bivalvia" in The Mollusca. Physiology Part 2: volume 4, eds. A. S. M. Saleuddin and K. M. Wilbur (Academic Press, Inc.), 77-82. Mújica, M., Sokolova, I.M., Izagirre, U. and Marigómez, I. (2015). Season-dependent effects of elevated temperature on stress biomarkers, energy metabolism and gamete development in mussels. Marine Environmental Research, 103, 1-10. Navarro, E., Iglesias, J. I. P. and Ortega, M. M. (1992). Natural sediment as a food source for the cockle Cerastodema edule (L): effect of variable particle concentration on feeding, digestion and the scope for growth. Journal of Experimental Marine Biology adn Ecology, 156, 69-87. Navarro, E., Iglesias, J. I. P., Ortega, M. M. and Larretxea, X. (1994). The basis for a functional response to variable food quantity and quality in cockles Cerastodema edule (Bivalvia, Cardiidae). Physiological Zoology, 67, 468-496. Ozkan, D., Dagdeviren, M., Katalay, S. and Guner, A. (2017). Multi-biomarker responses after exposure to pollution in the Mediterranean mussels (Mytilus galloprovincialis L.) in the Aegean coast of Turkey. Bulletin of Environmental Contamination and Toxicology, 98, 46-52. Pace, D. A., Marsh, A. G., Leong, P. K., Green, A. J., Hedgecock, D. and Manahan, D. T. (2006). Physiological bases of genetically determined variation in growth of marine invertebrate larvae: a study of growth heterosis in the bivalve Crassostrea gigas. Journal of Experimental Marine Biology and Ecology, 335, 188-209. Pampanin, D. M., Camus, L., Gomiero, A., Marangon, I., Volpato, E. and Nasci, C. (2005). Susceptibility to oxidative stress of mussels (Mytilus galloprovincialis) in the Venice Lagoon (Italy). Marine Pollution Bulletin, 50, 1548-1557. Pernet, F., Tremblay, R., Redjah, I., Sevigny, J. M. and Gionet, C. (2008). Physiological and biochemical traits correlate with differences in growth rate and temperature adaptation among groups of the eastern oyster Crassostrea virginica.Journal of Experimental Biology, 211, 969-977. Peters, R. H. (1983). The ecological implications of body size (Vol. 2). England: Cambridge University Press. Prieto, D., Markaide, P., Urrutxurtu, I., Navarro, E., Artigaud, S., Fleury, E., Ibarrola, I. and Urrutia, M. B. (2019). Gill transcriptomic analysis in fastand slow-growing individuals of Mytilus galloprovincialis. Aquaculture, 511, 734242. Prieto, D., Tamayo, D., Urrutxurtu, I., Navarro, E., Ibarrola, I. and Urrutia, M. B. (2020). Nature more than nurture affects the growth rate of mussels. Scientific Reports, 10, 1-13. Chapter 1: Differential tissue development compromising growth phenotypes 89 Prieto, D., Urrutxurtu, I., Navarro, E., Urrutia, M. B. and Ibarrola, I. (2018). Mytilus galloprovincialis fast growing phenotypes under different restrictive feeding conditions: Fast feeders and energy savers. Marine Environmental Research, 140, 114-125. Riisgård, H. U. and Larsen, P. (2010). Particle-capture mechanisms in suspension-feeding invertebrates. Marine Ecology Progress Series, 418, 255-293. Robinson, W. E. (1983). Assessment of bivalve intracellular digestion based on direct measurements. Journal of Molluscan Studies, 49, 1-8. Robinson, W. E., Michael, R. P. and Langton, R. W. (1981). Variability of tubule types within the digestive glands of Mercenaria mercenaria (L), Ostrea edulis L., and Mytilus edulis L. Journal of Experimental Biology and Ecology, 54, 265-276. Romèo, M., Mourgaud, Y., Geffard, A., Gnassia-Barelli, M., Amiard, J. C. and Budzinski, H. (2003). Multimarker approach in transplanted mussels for evaluating water quality in Charentes, France, coast areas exposed to different anthropogenic conditions. Environmental Toxicology, 18, 295-305. Seo, E., Ohishi, K. and Maruyama, T. (2014). Magnetic resonance imaging analysis of water flow in the mantle cavity of live Mytilus galloprovincialis.Journal of Experimental Biology, 217, 2277-2287. Sokolova, I. (2018). Mitochondrial adaptations to variable environments and their role in animal’s stress tolerance. ICB, 58, 519-531. Soto, M., Zaldibar, B., Cancio, I., Taylor, M. G., Turner, M., Morgan, A. J. and Marigómez, I. (2002). Subcellular distribution of cadmium and its cellular ligands in mussel digestive gland as revealed by combined autometallography and X-ray microprobe analysis. Histochemistry Journal, 34, 273-280. Storey, K. B. (1996). Oxidative stress: animal adaptations in nature. Brazilian Journal of Medical Biological Research, 29, 1715-1733. Syasina, I. G., Vaschenko, M. A. and Zhandan, P. M. (1997). Morphological alterations in the digestive diverticula of Mizuhipecten yessoensis (Bivalvia: Pectenidae) from polluted areas of Peter the Great Bay, Sea of Japan. Marine Environmental Research, 44, 85-98. Tamayo, D., Azpeitia, K., Markaide, P., Navarro, E.andIbarrola, I. (2016). Food regimemodulatesphysiological processes underlying size differentiation in juvenile intertidal mussels Mytilus galloprovincialis.Marine Biology, 163, 1-13. Tamayo, D., Ibarrola, I. and Navarro, E. (2013). Thermal dependence of clearance and metabolic rates in slow-and fast-growing spats of manila clam Ruditapes philippinarum.Journal of Comparative Physiology B, 90 Chapter 1: Differential tissue development compromising growth phenotypes 183, 893-904. Tamayo, D., Ibarrola, I., Cigarría, J. and Navarro, E. (2015). The effect of food conditioning on feeding and growth responses to variable rations in fast and slow growing spat of the Manila clam (Ruditapes philippinarum).Journal of Experimental Marine Biology and Ecology, 471, 92-103. Tamayo, D., Ibarrola, I., Urrutia, M. B. and Navarro, E. (2011). The physiological basis for inter-individual growth variability in the spat of clams (Ruditapes philippinarum).Aquaculture, 321, 113-120. Tamayo, D., Ibarrola, I., Urrutxurtu, I. and Navarro, E. (2014). Physiological basis of extreme growth rate differences in the spat of oyster (Crassostrea gigas).Marine Biology, 161, 1627-1637. Tamura, T., Yasuda, N., Shakuo, T., Kashiwagi, A., Martyn, J. A. J., Yokoyama, M. and Yasuhara, S. (2020). Microtubule defect involved in ‘mitophagy resistance’ under subacute oxidative stress - potential mechanism for cellular inflammation. bioRxiv. Toro, J. E. and Vergara, A. M. (1998). Growth and heterozygosity in a 12-month-old cohort of Ostrea chilensis obtained by mass spawning in the laboratory. Marine Ecology, 19, 311-323. Toro, J. E., Alcapan, A. C., Ojeda, J. A. and Vergara, A. M. (2004). Selection response for growth rate (Shell height and live weight) in the Chilean blue mussel (Mytilus chilensis Hupe 1854). Journal of Shellfish Research, 23, 753-758. Vahl, O. (1973). Pumping and oxygen consumption rates of Mytilus edulis L. of different sizes. Ophelia, 12, 45-52. Vincenzi, S., Mangel, M., Crivelli, A. J., Munch, S. and Skaug, H. J. (2014). Determining individual variation in growth and its implication for life-history and population processes using the empirical Bayes method. PLoS Computational Biology, 10, e1003828. Weibel, E. R. (1979). Stereological Methods: Vol 1. Practical Methods for Biological Morphometry. London. Academic Press. Zaldibar, B., Cancio, I. and Marigómez, I. (2008). Epithelial cell renewal in the digestive gland and stomach of mussels: season, age and tidal regime related variations. Histology and Histopathology, 23, 281-290. Zar, J. H. (2010). Biostatistical Analysis, 5th edition. Upper Saddle River, New Jersey. Pearson Prentice Hall. Zhang, J., Li, Q., Liu, S. and Yu, H. (2018). The effect of temperature on physiological energetics of a fastgrowing selective strain and a hatchery population of the Pacific oyster (Crassostrea gigas).Aquaculture Research, 49, 2844–2851. Chapter 2: Metabolic scaling: constitutive adaptation to tide level 91 Zhang, X., Ye, B., Gu, Z., Li, M., Yang, S., Wang, A. and Liu, C. (2021). Comparison in growth, feeding, and metabolism between a fast-growing selective strain and a cultured population of Pearl oyster (Pinctada fucata martensii).Frontiers in Marine Sciences, 8, 770702. ja 92 Chapter 2: Metabolic scaling: constitutive adaptation to tide level Chapter 2: Metabolic scaling: constitutive adaptation to tide level 99 2 Materials and methods 2.1 Collection of mussels and experimental setup 2.1.1 Season and tidal-regime experiment Two samplings were made to collect M. galloprovincialis mussels from the sheltered rocky shore of Plentzia (Biscay, Spain, 43º24’ N; 2º56’ W) (Fig. 1), coinciding with the autumn (November 2021) and spring (May 2022) seasons. Water temperature was around 15.5 ºC in both seasons and the phytoplankton concentration similar (Bilbao et al., 2021). In each sampling, mussels were collected at low tide (spring tides) from the intertidal (n = 30) and subtidal (n = 30) subpopulations, covering the broadest size-range possible: 21.6 – 67.0 mm and 22.4 – 65 mm for intertidal and subtidal tide regimes in November; 20.6 – 68.3 mm and 21.8 – 66.0 mm for intertidal and subtidal mussels in May. Therefore, four different experimental groups arose from the combination of the tidal regime (subtidal –S– vs. intertidal –I–) and sampling date (November –N– vs. May –M–): SN,IN,SMand IM. Figure 1. Sheltered sampling point in the Bay of Plentzia in Biscay (North of Spain). Mussels were transferred to the laboratory in air-exposed wet containers. On both occasions, the procedure followed identical protocols: intertidal and subtidal mussels were placed in two different tanks (50 L) at constant seawater salinity (33 PSU) and temperature (16 ºC). The next day upon arrival, the routine oxygen consumption of each individual was measured, while the standard oxygen consumption was recorded after 7 100 Chapter 2: Metabolic scaling: constitutive adaptation to tide level days of fasting. This period was established to be sufficient for mussels to minimize any energy cost derived from digestion processes (Prieto et al., 2018). 2.1.2 Acclimation experiment To understand the effects that acclimation to laboratory conditions might have on the metabolism of both tidal regimes, all mussels collected in November were kept in the laboratory for a period of 2 months individualized in independent chambers. Two tanks (50 L) were used for subtidal and intertidal mussels, respectively, maintained under constant seawater salinity (33 PSU) and temperature (16 ºC). The seawater was pump directly from a 12,000 L reservoir of natural seawater that is filtered through a biological filter and three subsequent fiberglass filters (100, 10 and 1 µm) before going into the recirculating water system in the laboratory. Constant food was supplied in the form of a combination of own-cultured Isochrysis galbana strain BMCC1 microalgae (Basque Microalgae Culture Collection from University of the Basque Country), and a commercial mixture (Shellfish Diet 1800®) of five marine microalgae (Isochrysis sp., Pavlova sp., Tetraselmis sp., Thalassiosira weissflogii and Thalassiosira pseudonana) constantly dosed at 20000 part · mL -1 . The concentration was kept stable by frequently checking with a Coulter Multisizer 3 and homogeneity ensured with air circulation. The tanks were cleaned and seawater renewed twice a week. No mortality events were recorded during the acclimation period. After the 2-month acclimation period to continuous immersion and feeding in the laboratory, routine and standard metabolic rates were again measured. For each tidal regime, two different data sets were obtained: an initial determination corresponding to the field conditions (F) and a final determination after maintenance in the laboratory (L). Consequently, four different experimental groups were obtained in this second experiment: SF,IF,SL, and IL. 2.2 Oxygen consumption 2.2.1 Routine oxygen consumption (VO2R: mL O2·h-1) Mussels were introduced into chambers ranging from 50 to 250 ml (according to mussel size) sealed with LDO oxygen probes connected to oxymeters (HATCH HQ40d) for the determination of routine oxygen consumption. The oxygen consumption rates were calculated from the decrease in oxygen concentration in the chambers recorded during 3-4 h, or until the values decreased 20-30 % of the initial baseline, every 5-10 minutes. A control chamber was used to check the stability of the oxygen concentration. 2.2.2 Standard oxygen consumption (VO2S: mL O2·h-1) Standard oxygen consumption was likewise recorded, except for the 7-day fasting period that mussels were subdued to before measurements were made. Chapter 2: Metabolic scaling: constitutive adaptation to tide level 101 2.3 Gill surface-area (GA: mm2·g-1) Gill surface-area measurements were only recorded for the mussels collected in May, as the mussels collected in November may not reflect field values after two months of acclimation in the laboratory. After the physiological experiments were concluded, all individuals were carefully dissected. A photograph of the internal tissues was taken with a digital camera and the surface-area of the gills of each individual was calculated using ImageJ software (Abràmoff et al., 2004). A rule was placed next to the mussel when taking the photograph for size correction. The data shown correspond to one side of the demibranch. 2.4 Shell dimensions Biometry and shell surface-area were calculated for all 30 mussels of each tidal regime in both experiments. In the case of the acclimation experiment, both measurements were taken on arrival in the laboratory and after 2 months of maintenance. The anterior-posterior (length), dorso-ventral (height) and lateral axis (width) of the shell were measured to the nearest 0.01 mm using digital dial calipers. The shell surface-area (mm 2 ) was obtained applying a formula resembling an ellipsoid-like shape proposed by Reimer and Tedengren (1996): SA =L·(H2+W2)0.5·0.5π where L, H and Ware respectively the length (mm), width (mm) and height (mm). 2.5 Condition index (CI) After both samplings, once physiological measurements were completed, the whole flesh of each animal was dissected and desiccated (24 hrs. 100 ºC) to obtain the flesh dry weight (FDW: mg). The dry weight of the shell (SDW: mg) was obtained after the flesh residues were carefully removed from the surface of the completely air-dried shell. The shells were weighed on a 0.01 mg accuracy balance, just as the live weight of the entire animal. Condition index (CI) was computed according to Davenport and Chen (1987): CI =FDW TDW where TDW represents the total dry weight of the mussel computed as FDW + SDW. 2.6 Statistical analysis Data were evaluated for normality and homoscedasticity using Shapiro-Wilk and Levene tests, respectively, prior to data analysis. Normal distribution of the residuals was checked by Normal P-P plots and the independence of the observations tested by Durbin-Watson tests. 102 Chapter 2: Metabolic scaling: constitutive adaptation to tide level Linear ordinary least squares regression analyses were performed to determine the values of the scaling exponents (b) and the coefficients (a) for each regression. Regressions were computed with log-transformed data of routine and standard oxygen consumption ( VO2R and VO2S ), live weight, gill surface-area shell length, shell surface-area and shell dry weight. Not-logarithmically transformed data of shell width, shell height and shell length were also fitted to linear regressions. Significant differences in scaling exponents and coefficients between regressions corresponding to each experimental group were tested using covariance procedures (ANCOVA) described by Zar (1999); briefly, if the null hypothesis ( H0 : equal slopes b1 = b2 = b3 ... = bk ) was rejected, multiple comparison t-test was performed to determine the significant differences between each pair of slopes. If H0 was accepted, a common slope ( bc ) was computed and the null hypothesis of equal intercepts ( a1 = a2 = a3 ... = ak ) was subsequently tested. If intercepts were not different, a common intercept ( ac ) and common regression were computed. Multiple comparison t-test was performed to determine the significant differences between each pair of elevations, in case they were different. Data resulting from each experiment was also assessed by multiple regression analysis (after observation independence and normality of residuals were checked) to sequentially identify the explanatory variables that were most closely associated with routine oxygen consumption and standard oxygen consumption (dependent variables). For the seasonality experiment, the explanatory variables were live weight (numeric), season (dummy variable; May = 0, November = 1), tide (dummy variable; subtidal = 0, intertidal = 1), 2-way interactions (live weight x season; live weight x tide; season x tide) and 3-way interaction. For the acclimation experiment, the explanatory variables were live weight (numeric), time (dummy variable; Field = 0, Laboratory = 1), tide (dummy variable; subtidal = 0, intertidal = 1), 2-way interactions (live weight x time; live weight x tide; time x tide) and 3-way interaction. The effect of season and tide factors on shell surface-area and condition index was analyzed with two-way factor ANOVA. Statistical analyzes were performed using IBM SPSS Statistics for Windows, Version 28.0 (IBM Corp., 2021). 3 Results 3.1 Season and tidal-regime experiment 3.1.1 Routine oxygen consumption (VO2R) The data of routine oxygen consumption for each experimental group plotted as a function of their respective live weight can be found in Fig. 2A. The resulting equations are summarised in Fig. 2A on the top right. Statistical comparisons between the four regression lines showed that the slopes differed from each other (Fig. 2A). The allometric exponent of the subtidal mussels was consistently higher than the allometric exponent of Chapter 2: Metabolic scaling: constitutive adaptation to tide level 103 the intertidal ones, notwithstanding the month. However, the slope of the intertidal population in November was significantly the lowest compared to the other three. The general equation relating routine oxygen consumption with live weight (W) and tide in the multiple regression analysis was the following (mean value ±SD): Replacing the dummy variables, the following regression models arose for subtidal (0) and intertidal (1) mussels taking together the values for November and May: Subtidal mussels: Log VO2= 0.875 (±0.045) log W - 1.733 (±0.054) Intertidal mussels: Log VO2= 0.670 (±0.056) log W - 1.552 (±0.068) The regression analysis of the model obtained the highest statistical significance ( R2 = 0.829, F = 186.426 and p < 0.001). 3.1.2 Standard oxygen consumption (VO2S) Data on standard oxygen consumption for each experimental group plotted as a function of their respective live weight can be found in Fig. 2B. On the top right of Fig. 2B, the resulting equations of such regressions are shown. For VO2S , no significant differences were found between slopes, therefore a common mass exponent ( bc = 0.644) was computed. However, mass-specific standard oxygen consumption was significantly lower in intertidal mussels and, therefore, ANCOVA showed significant differences in intercepts between tide levels (Fig. 2B - arecomp.). 3.1.3 Shell dimensions Width vs. length. The individual shell widths for each mussel group have been plotted in Fig. 3A as a function of their respective shell lengths. The resulting equations are shown on the top right of Fig. 3A. No significant differences were found among slopes and a common allometric exponent ( bc ) of 0.393 was obtained (Fig. 3A, bottom right). Conversely, elevations were significantly higher in intertidal mussels, regardless of the season (Fig. 3A, bottom right). Height vs. length. The individual shell heights for each mussel group have been plotted in Fig. 3B as a function of the respective shell lengths. No significant differences were found among slopes or elevations, giving rise to a common regression ( R2 = 0.959; p < 0.001; F = 2687.46) with an allometric exponent ( bcommon ) of 0.479 (±0.009) and a common elevation ( acommon ) of 4.539 (±0.457). The common regression exponent values are shown on the bottom right table of Fig. 3B. 104 Chapter 2: Metabolic scaling: constitutive adaptation to tide level Figure 2. Regression lines for the allometric relationships of the form Y = a ·Xb . (A) Logtransformed routine oxygen consumption vs. log-transformed weight; (B) log-transformed standard oxygen consumptionvs. logtransformed weight. On the top right of each figure, the allometric relationship is shown according to the expression: Y = a ·LWb , where LW is live weight. In case of a common b-value, the recomputed a-values are also shown (a recomp. ). On the bottom right, ANCOVA and post hoc tests. Shared letters (a, b or c) indicate no significant differences (p < 0.05). Purple and orange symbols distinguish tide levels (subtidal, intertidal), circles and triangles seasons (November, May). SN : purple circles; IN : orange circles; SM : purple triangles; IM: orange triangles. SDW vs. length. The individual shell dry weights for each mussel group have been plotted in Fig. 4A as a function of their respective shell lengths. The resulting equations are shown on the top right of Fig. 4A. No significant differences were found among slopes and a common allometric exponent (b common ) of 2.531 was obtained (Fig. 4A, bottom right). Conversely, elevations were significantly higher in intertidal mussels, regardless of the season (Fig. 4A, bottom right). Chapter 2: Metabolic scaling: constitutive adaptation to tide level 105 Figure 3. Regression lines for the allometric relationships of the form Y = bX - a. (A) Shell width (mm)vs. Shell length (mm); (B) Shell height (mm)vs. Shell length (mm). On the top right of each figure, the allometric relationship for the shell dimension against individual length is shown. In case of a common b-value, the recomputed a-values are also shown (a recomp. ). On the bottom right, ANCOVA and post hoc tests. Shared letters (a,b or c) indicate no significant differences (p < 0.05). Purple and orange symbols distinguish tide levels (Subtidal, Intertidal), circles and triangles seasons (November, May). SN : purple circles; IN : orange circles; SM: purple triangles; IM: orange triangles. SDW vs. surface-area. The individual shell dry weights for each mussel group have been plotted in Fig. 4B as a function of their respective shell surface-areas. The b-value corresponds to the effect that size exerts on the relationship between the two variables, whereas the a-value represent what could be considered the density of the shell. The resulting equations are shown on the top right of Fig. 4B. Each slope differed significantly from each other (Fig. 4B, bottom right), being the differences between mussel groups smaller as the size increases. Also the intercepts indicate that the density of the shell is virtually the same in the intertidal mussels 106 Chapter 2: Metabolic scaling: constitutive adaptation to tide level regardless of the season (for a common shell surface-area of 3.3 mm 2 : the a-value for IM is 0.777 and for IN is 0.703). However, the shell density of subtidal individuals increases over a 30 % in May compared to November (for a common shell surface-area of 3.3 mm2: the a-value for SMis 0.916 and for SNis 0.636). Figure 4. Regression lines for the allometric relationships of the form Y = a ·Xb . (A) Logtransformed shell dry weight (SDW) vs. log-transformed shell length; (B) log-transformed shell dry weight (SDW) vs. logtransformed shell surface-area. On the top right of each figure, the allometric relationship is shown according to the expression Y = a · LW b , where LW is live weight. In case of a common b-value, the recomputed a-values (a recomp. )are also shown. On the bottom right, ANCOVA and post hoc tests. Shared letters (a, b or c) indicate no significant differences (p < 0.05). Purple and orange symbols distinguish tide levels (subtidal, intertidal), circles and triangles seasons (November, May). SN : purple circles; IN : orange circles; SM : purple triangles; IM: orange triangles. Chapter 2: Metabolic scaling: constitutive adaptation to tide level 107 3.1.4 Condition index (CI) Subtidal mussels from both seasons had around 30 % higher CI (Fig. 5), according to the Tukey test. The two-way ANOVA showed tide level as the only factor significantly affecting CI values (Fig. 5, top right). 3.1.5 Gill surface-area (GA: mm2·g-1) Figure 6 shows the relationship between gill surface-area and shell length in subtidal and intertidal mussels. The ANCOVA analysis showed no differences between slopes (t = 0.103, df = 1, 54; p > 0.05), with a b common value of 1.955. However, the intercept of intertidal mussels was higher compared to the subtidal mussels (t = 3.125, df = 1, 54; p < 0.001). Figure 5. CI of subtidal and intertidal mussels for November and May. Shared letters indicate absence of statistical differences. On the top, the two-way factor ANOVA testing significant effects of season (November vs. May) and tide level (subtidal vs. intertidal). 3.2 Acclimation experiment 3.2.1 Routine oxygen consumption (VO2R) Routine oxygen consumptions for each mussel group are plotted as a function of their respective live weight in Fig. 7A and the resulting equations are summarised on the bottom right of the figure. The slopes of routine oxygen consumption and live weight differed from each other: intertidal mussels had lower allometric exponents, regardless of whether mussels were acclimated or not to laboratory conditions. Multiple regression analysis showed that live weight and tide explained 82 % of the variation in routine oxygen consumption. The resulting general equation was the following (mean value ±SD): 108 Chapter 2: Metabolic scaling: constitutive adaptation to tide level Replacing the dummy variables, the following regression models arose for subtidal (0) and intertidal (1) mussels: Subtidal mussels: Log VO2= 0.866 (±0.047) log W - 1.788 (±0.050) Intertidal mussels: Log VO2= 0.615 (±0.058) log W - 2.022 (±0.067) The regression analysis of the model obtained the highest statistical significance (R 2 = 0.820, F = 171.944 and p < 0.001). 3.2.2 Standard oxygen consumption (VO2S) The standard oxygen consumption data for each experimental group plotted as a function of their respective live weight can be found in Fig. 7B. On the top right of Fig. 7B, the resulting equations of such regressions are shown. For VO 2S , the regression slopes were not significantly different b c = 0.662), but the intercepts differed between the tide levels, with lower values for intertidal mussels (Fig. 7B, bottom right). Figure 6. Regression lines for the allometric relationships of the form Y = a · X b for gill surface-area against shell length. On the top right, the allometric relationship for the gill surface-area against individual length is shown. On the bottom right, ANCOVA and post hoc tests. Because a common b-value was accepted, the recomputed a-values a recomp. are also shown. Shared letters (a, b or c) indicate no significant differences (p < 0.05). Purple and orange symbols indicate values for subtidal and intertidal mussels, respectively. 4 Discussion The broad intraspecific variability of the allometric mass-exponents of metabolic rate is a biological phenomenon not yet fully understood (e.g., Glazier, 2018; Hatton et al., 2019; Escala, 2022; White et al., Chapter 2: Metabolic scaling: constitutive adaptation to tide level 115 doi:10.2307/3599357 Brown, J. H., Gillooly, J. F., Allen, A. P., Savage, V. M. and West, G. B. (2004). Toward a metabolic theory of ecology. Ecology, 85(7), 1771–1789. Burnett, N. P. and Belk, A. (2018). Compressive strength of Mytilus californianus shell is time-dependent and can influence the potential foraging strategies of predators. Marine Biology, 165, 1–9. Carey, N., Sigwart, J. D. and Richards, J. G. (2013). Economies of scaling: more evidence that allometry of metabolism is linked to activity, metabolic rate and habitat. Journal of Experimental Marine Biology and Ecology, 439, 7–14. Clark, M. S., Peck, L. S., Arivalagan, J., Backeljau, T., Berland, S., Cardoso, J. C., Caurcel, C., Chapelle, G., De Noia, M. and Dupont, S. (2020). Deciphering mollusc shell production: the roles of genetic mechanisms through to ecology, aquaculture and biomimetics. Biological Reviews, 95(6), 1812–1837. Clark, M. S., Thorne, M. A., King, M., Hipperson, H., Hoffman, J. I. and Peck, L. S. (2018). Life in the intertidal: cellular responses, methylation and epigenetics. Functional Ecology, 32(8), 1982–1994. Connor, K. M. and Gracey, A. Y. (2012). High-resolution analysis of metabolic cycles in the intertidal mussel Mytilus californianus.American Journal of Physiology and Regulating Integrative Comparative Physiology, 302(1), R103–R111. Cordero-Rivera, A., Ondina, P., Outeiro, A., Amaro, R. and San Miguel, E. (2022). Allometry in the freshwater Pearl mussel (Margaritifera margaritifera L.): mussels tend to grow flatter at higher water speed. Malacologia, 64(2), 257-267. da Silva, J. K. L., Garcia, G. J. and Barbosa, L. A. (2006). Allometric scaling laws of metabolism. Physiology Life Reviews, 3(4), 229–261. Davenport, J. and Chen, X. (1987). A comparison of methods for the assessment of condition in the mussel (Mytilus edulis l.). Journal of Molluscan Studies, 53(3), 293–297. Escala, A. (2022). Universal relation for life-span energy consumption in living organisms: insights for the origin of aging. Scientific Reports, 12, 2407. Fernández-Reiriz, M. J., Irisarri, J. and Labarta, U. (2016). Flexibility of Physiological Traits Underlying Inter-Individual Growth Differences in Intertidal and Subtidal Mussels Mytilus galloprovincialis.PloS ONE, 11(2), e0148245. Fitzer, S. C., Zhu, W., Tanner, K. E., Phoenix, V. R., Kamenos, N. A. and Cusack, M. (2015). Ocean acidification alters the material properties of Mytilus edulis shells. Journal of The Royal Society Interface, 12(103), 116 Chapter 2: Metabolic scaling: constitutive adaptation to tide level 20141227. Franz, D. R. (1993). Allometry of shell and body weight in relation to shore level in the intertidal bivalve Geukensia demissa (Bivalvia: Mytilidae). Journal of Experimental Marine Biology and Ecology, 174(2), 193-207. Freites, L., Labarta, U. and Fernández-Reiriz, M. J. (2002). Evolution of fatty acid profiles of subtidal and rocky shore mussel seed (Mytilus galloprovincialis, Lmk.). Influence of environmental parameters. Journal of Experimental Marine Biology and Ecology, 268(2), 185–204. Glazier, D. S. (2005). Beyond the ‘3/4-power law’: variation in the intra-and interspecific scaling of metabolic rate in animals. Biological Reviews, 80(4), 611–662. Glazier, D. S. (2008). Effects of metabolic level on the body size scaling of metabolic rate in birds and mammals. Proceedings of the Royal Society B: Biological Sciences, 275(1641), 1405–1410. Glazier, D. S. (2009). Activity affects intraspecific body-size scaling of metabolic rate in ectothermic animals. Journal of Comparative Physiology B: Biochemistry Systems and Environmental Physiology, 179, 821–828. Glazier, D. S. (2010). A unifying explanation for diverse metabolic scaling in animals and plants. Biological Reviews, 85(1), 111–138. Glazier, D. S. (2015). Is metabolic rate a universal ‘pacemaker’ for biological processes? Biological Reviews, 90(2), 377-407. Glazier, D. S. (2018). Rediscovering and Reviving Old Observations and Explanations of Metabolic Scaling in Living Systems. Systems, 6(1), 4. Glazier, D. S. (2022a). How metabolic rate relates to cell size. Biology, 11(8), 1106. Glazier, D. S. (2022b). Variable metabolic scaling breaks the law: from ‘Newtonian’ to ‘Darwinian’ approaches. Proceedings of the Royal Society B: Biological Sciences, 289(1985), 20221605. doi: 10.1098/rspb.2022.1605 Gleason, L. U., Miller, L. P., Winnikoff, J. R., Somero, G. N., Yancey, P. H., Bratz, D. and Dowd, W. W. (2017). Thermal history and gape of individual Mytilus californianus correlate with oxidative damage and thermoprotective osmolytes. Journal of Experimental Biology, 220(22), 4292–4304. Gracey, A. Y. and Connor, K. (2016). Transcriptional and metabolomic characterization of spontaneous metabolic cycles in Mytilus californianus under subtidal conditions. Marine Genomics, 30, 35–41. Harley, C. D., Denny, M. W., Mach, K. J. and Miller, L. P. (2009). Thermal stress and morphological adaptations in limpets. Functional Ecology, pages 292–301. Chapter 2: Metabolic scaling: constitutive adaptation to tide level 117 Hatton, I. A., Dobson, A. P., Storch, D., Galbraith, E. D. and Loreau, M. (2019). Linking scaling laws across eukaryotes. PNaS, 116(43), 21616-21622. Hawkins, A. J. S., Navarro, E. and Iglesias, J. I. P. (1990). Comparative allometries of gut-passage time, gut content and metabolic faecal loss in Mytilus edulis and Cerastoderma edule.Marine Biology, 105, 197-204. Hemmingsen (1960). Energy metabolism as related to body size and respiratory surfaces, and its evolution. Rep. Steno Mem. Hosp. Nord. Insulin Lab., 9, 3–110. Hirst, A. G., Glazier, D. S. and Atkinson, D. (2014). Body shape shifting during growth permits tests that distinguish between competing geometric theories of metabolic scaling. Ecological Letters, 17(10), 12741281. Ibarrola, I., Arranz, K., Markaide, P. and Navarro, E.(2022). Metabolic sizescaling reflectsgrowthperformance effects on age-size relationships in mussels (Mytilus galloprovincialis). PLoS ONE, 17(9), e0268053. IBM Corp. Released 2021. IBM SPSS Statistics for Windows, Version 28.0. Armonk, NY: IBM Corp. Jensen, M. A., Fitzgibbon, Q. P., Carter, C. G. and Adams, L. R. (2013). Effect of body mass and activity on the metabolic rate and ammonia-n excretion of the spiny lobster Sagmariasus verreauxi during ontogeny. Comparative Biochemistry Physiology Part A Molecular Integrative Physiology, 166(1), 191–198. Jones, H. D., Richards, O. G. and Southern, T. A. (1992). Gill dimensions, water pumping rate and body size in the mussel Mytilus edulis.Journal of Experimental Marine Biology and Ecology, 155(2), 213–237. Kleiber, M. et al. (1932). Body size and metabolism. Hilgardia, 6(11), 315–353. Kozlowski, J., Konarzewski, M. and Gawelczyk, A. T. (2003). Cell size as a link between noncoding DNA and metabolic rate scaling. PNAS, 100(24), 14080-14085. Kozlowski, J., Konarzewski, M. and Gawelczyk, A. T. (2020). Coevolution of body size and metabolic rate in vertebrates: a life-history perspective. Biological Reviews, 95(5), 1393-1417. Leeuwis, R. H. J. and Gamperl, A. K. (2022). Adaptations and plastic phenotypic responses of marine animals to the environmental challenges of the high intertidal zone. In S. J. Hawkins, A.L. Allcock, A.E. Bates, M. Byrne, A.J. Evans, L.B. Firth, A.J. Lemasson, C. Lucas, E.M. Marzinelli, P.J. Mumby, B.D. Russell, J. Sharples, I.P. Smith, S.E. Swearer and P.A. Todd. (Eds.) Oceanography and Marine Biology (pp. 625-679). CRC Press. Mandic, M. and Regan, M. D. (2018). Can variation among hypoxic environments explain why different fish species use different hypoxic survival strategies? Journal of Experimental Biology, 221(21), jeb161349. Marsden, I. D., Shumway, S. E. and Padilla, D. K. (2012). Does size matter? The effects of body size and 118 Chapter 2: Metabolic scaling: constitutive adaptation to tide level declining oxygen tension on oxygen uptake in gastropods. Journal of Marine Biology Association, 92(7), 1603-1617. McArley, T. J., Hickey, A. J., Wallace, L., Kunzmann, A. and Herbert, N. A. (2019). Intertidal triplefin fishes have a lower critical oxygen tension (p crit), higher maximal aerobic capacity, and higher tissue glycogen stores than their subtidal counterparts. Journal of Comparative Physiology B: Biochemistry Systems and Environmental Physiology, 189(3-4), 399–411. Muller-Landau, H. C., Condit, R. S., Chave, J., Thomas, S. C., Bohlman, S. A., Bunyavejchewin, S., ... and Ashton, P. (2006). Testing metabolic ecology theory for allometric scaling of tree size, growth and mortality in tropical forests. Ecological Letters, 9(5), 575–588. Nicastro, K. R., Zardi, G. I., McQuaid, C. D., Stephens, L., Radloff, S. and Blatch, G. L. (2010). The role of gaping behaviour in habitat partitioning between coexisting intertidal mussels. BMC Ecology, 10, 1–11. Nuñez, J. D., Fernández Iriarte, P., Ocampo, E. H., Madrid, E. and Cledón, M. (2018). Genetic and morphophysiological differentiation in a limpet population across an intertidal gradient. Helgoland Marine Research, 72, 1–10. O’Connor, M. P., Kemp, S. J., Agosta, S. J., Hansen, F., Sieg, A. E., Wallace, B. P., McNair, J. N. and Dunham, A. E. (2007). Reconsidering the mechanistic basis of the metabolic theory of ecology. Oikos, 116(6), 1058–1072. Parry, G. D. (1983). The influence of the cost of growth on ectotherm metabolism. Journal of Theoretical Biology, 101(3), 453-477. Pérez-Cebrecos, M., Prieto, D., Blanco-Rayón, E., Izagirre, U. and Ibarrola, I. (2022). Differential tissue development compromising the growth rate and physiological performances of mussel. Marine Environmental Research, 180, 105725. Prieto, D., Tamayo, D., Urrutxurtu, I., Navarro, E., Ibarrola, I. and Urrutia, M. (2020). Nature more than nurture affects the growth rate of mussels. Scientific Reports, 10(1), 1– 13. Prieto, D., Urrutxurtu, I., Navarro, E., Urrutia, M. and Ibarrola, I. (2018). Mytilus galloprovincialis fast growing phenotypes under different restrictive feeding conditions: Fast feeders and energy savers. Marine Environmental Research, 140, 114–125. Reimer, O. and Tedengren, M. (1996). Phenotypical improvement of morphological defences in the mussel Mytilus edulis induced by exposure to the predator Asterias rubens.Oikos, 75(3), 383-390. Sarà, G. and Pusceddu, A. (2008). Scope for growth of Mytilus galloprovincialis (Lmk., 1819) in oligotrophic Chapter 2: Metabolic scaling: constitutive adaptation to tide level 119 coastal waters (southern Tyrrhenian sea, Italy). Marine Biology, 156, 117–126. Savage, V. M., Gillooly, J. F., Woodruff, W. H., West, G. B., Allen, A. P., Enquist, B. J. and Brown, J. H. (2004). The predominance of quarter-power scaling in biology. Functional Ecology, 18(2), 257–282. Sokolova, I. and Pörtner, H. (2001). Temperature effects on key metabolic enzymes in Littorina saxatilis and L. obtusata from different latitudes and shore levels. Marine Biology, 139, 113–126. Sprung, M. (1984). Physiological energetics of mussel larvae (Mytilus edulis). 111. Respiration. Marine Ecology Progress Series, 18, 171. Staikou, A. E. (1999). Shell temperature, activity and resistance to desiccation in the polymorphic land snail Cepaea vindobonensis.Journal of Molluscan Studies, 65(2), 171-184. Steffani, C. N. and Branch, G. M. (2003). Growth rate, condition, and shell shape of Mytilus galloprovincialis: responses to wave exposure. Marine Ecology Progress Series, 246, 197–209. Suarez, R. K., Darveau, C. A. and Childress, J. J. (2004). Metabolic scaling: a manysplendoured thing. Comparative Biochemistry and Physiology B, Biochemical Molecular Biology, 139(3), 531–541. Tagliarolo, M., Clavier, J., Chauvaud, L., Koken, M. and Grall, J. (2012). Metabolism in blue mussel: intertidal and subtidal beds compared. Aquatic Biology, 17, 167-180. Tamayo, D., Azpeitia, K., Markaide, P., Navarro, E.andIbarrola, I. (2016). Food regimemodulatesphysiological processes underlying size differentiation in juvenile intertidal mussels Mytilus galloprovincialis.Marine Biology, 163, 1–13. Tokeshi, M., Ota, N. and Kawai, T. (2000). A comparative study of morphometry in shell-bearing molluscs. Journal of Zoology, 251(1), 31-38. Toone, T. A., Hillman, J. R., Benjamin, E. D., Handley, S. and Jeffs, A. (2023). Out of their depth: The successful use of cultured subtidal mussels for intertidal restoration. Conservative Science Practices, 5(4), e12914. Weihe, E. and Abele, D. (2008). Differences in the physiological response of inter-and subtidal antarctic limpets Nacella concinna to aerial exposure. Aquatic Biology, 4(2), 155– 166. White, C. R. (2011). Allometric estimation of metabolic rates in animals. Comparative Biochemical Physiology Part A Molecular Integrative Physiology, 158(3), 346– 357. White, C. R., Alton, L. A., Bywater, C. L., Lombardi, E. J. and Marshall, D. J. (2022). Metabolic scaling is the product of life-history optimization. Evolutionary Ecology, 377(6608), 834-839. White, C. R., Phillips, N. F. and Seymour, R. S. (2006). The scaling and temperature dependence of vertebrate 120 Chapter 3: Tidel level shapes growth-rate phenotypes metabolism. Biological Letters, 2(1), 125–127. Williams, E. E. and Somero, G. N. (1996). Seasonal-, Tidal-Cycleand Microhabitat-Related Variation in Membrane Order of Phospholipid Vesicles from Gills of the Intertidal Mussel Mytilus californianus. Journal of Experimental Biology, 199(7), 1587-1596. Winter, J. E. (1978). A review on the knowledge of suspension-feeding in lamellibranchiate bivalves, with special reference to artificial aquaculture systems. Aquaculture, 13(1), 1-33. Zar, J. H. (1999). Biostatistical analysis. Pearson Education India. ja Chapter 3 Tide level shapes the growth phenotypes of Mytilus galloprovincialis under field rearing conditions Mar y rocas de San Esteban, Asturias (1903) – Joaquín Sorolla 122 Chapter 3: Tidel level shapes growth-rate phenotypes Resumen Las diferencias derivadas de la eficiencia de los mecanismos fisiológicos involucrados en la adquisición de energía son una de las causas de las diferencias inter-individuales en tasa de crecimiento bajo condiciones de laboratorio enmejillones. También en ellaboratorio, las tasas demetabolismo más bajasson el factorclave para la aparición del fenotipo de crecimiento rápido cuando la disponibilidad de comida es baja. Ningún estudio ha intentado analizar cómo se desarrollan los diferentes fenotipos bajo condiciones de campo comparables, pero que implican diferentes escenarios tróficos. Dos grupos de 300 mejillones (12.16 ± 1.10 mm cada uno) fueron colocados en dos cajas ancladas al espigón a < 1 y 2.5 metros sobre la línea de marea: intermareal bajo (L) y alto (H). Tras 6 meses, se obtuvieron fenotipos de crecimiento rápido (F), intermedio (I) y lento (S) en cada uno de los niveles mareales, que fueron empleados para experimentos de alimentación y la medición del balance energético, así como el área branquial, el índice de estructura branquial y el peso seco de la concha. Bajo ambos regímenes mareales, los mejillones S mostraron una densidad ciliar menor en branquias y conchas más densas que los F. En L, los mejillones S casi alcanzaron las abilidades de adquisición de comida y absorción de los F, pero redujeron su distribución de energía hacia el crecimiento somático, incluso a expensas de reducir su área branquial, en aras de otros requerimientos energéticos, como conchas más pesadas, crecimiento gonadal o actividad antioxidante. En H, las diferencias en tasa de crecimiento se explican con el modelo de adquisición de energía, pero sin estar acompañado de diferencias en área branquial. Estos resultados no están en correspondencia con estudios previos que trabajan con condiciones restrictivas, los cuales sugieren una capacidad mayor de los F para reducir su tasa metabólica. Los beneficios de invertir en un área branquial mayor no compensan las desventajas que ello supone en el campo. Laburpena Muskuiluetan, banakoen arteko hazkuntza-tasa ezberdintasunak azaltzen dira energia lorpenean parte hartzen duten fisiologia-mekanismoen efizientzia-desberdintasunen arabera, laborategi baldintzetan. Baita laborategian, metabolismo-tasa baxuagoak gakoak dira hazkuntza azkarreko fenotipoa ager dadin janari eskuragarritasun baxupean. Ikerketa bat ere ez du aztertu zelan garatzen diren fenotipo ezberdinak balizko egoera trofiko ezberdinak dituzten landa-egoera alderagarrietan. 300 muskuiludun bi multzo (12.16 ± 1.10 mm bakoitzak) sartu ziren olatu-hormara ainguratutako bi kutxatan, marea-lerrotik < 1 eta 2.5 metrotara: marearteko baxua (L) eta altua (H). Sei hilabete geroago, marearteko maila bakoitzean hazkuntza azkarreko (F), tarteko (I) eta baxuko (S) fenotipoak lortu ziren, elikadura esperimentuak eta energia-balantzea neurtzeko erabili zirenak, baita brankia-azalera, brankia egituraren indizea eta maskorraren pisu lehorra neurtzeko ere. Marearteko maila bakoitzean, S muskuiluek brankietako zilio-dentsitate baxuagoa eta maskor lodiagoak agertu zituzten. L egoeran, S muskuiluek ia lortu zituzten F muskuiluen janari-eskuratze Chapter 3: Tidel level shapes growth-rate phenotypes 123 eta xurgapen gaitasunak, baina hazkuntza somatikoari energia gutxiago esleitzen diote, brankia-azalera murriztearen kontura, beste energia-eskarien alde, esaterako, maskor pisutsuagoak, gonada-hazkuntza edo aktibitate antioxidatzailea. H egoeran, hazkuntza-tasa ezberdintasunak azaltzen dira janari eskuragarritasun modeloaren arabera, brankia-azalerarekin parekatuta ez zegoena. Emaitza hauek ez datoz bat egoera murriztaileetan egindako ikerketekin, F muskuiluek metabolismoa murrizteko duten gaitasuna azpimarratu dutenak. Brankia-azaleran inbertitzeak dakartzan abantailak ez dute konpentsatzen landa egoeran dakartzan desabantailekin. Abstract Differences deriving from the efficiency of the physiological mechanisms involved in the energy acquisition are one of the underlying causes for inter-individual growth-rate differences under laboratory conditions in mussels. Also in the laboratory, lower metabolic rates are the key factor for the appearance of the fast growing phenotype under low food availability. No study has attempt to analyse how the different phenotypes develop under comparable field conditions with yet different trophic scenarios. Two sets of 300 mussels (12.16 ± 1.10 mm, each) were placed in two cages anchored to the breakwater at < 1 and 2.5 metres above the tide line: low (L) and high (H) intertidal. After 6 months, fast (F), intermediate (I) and slow (S) growing phenotypes were obtained in each tide level, which were used for feeding experiments and the measurement of the energy balance, as well as the gill surface-area, gill structure index, and shell dry weight. Under both tidal heights, S growers were found to have lower gill cilia density and denser shells than F growers. In L, S mussels almost caught up the food acquisition and absorption abilities of F, but they reduce the energy allocation to somatic growth, even at the expense of reducing their gill surface-area, for the sake of other energetic requests, such as heavier shells, gonadal growth or antioxidant activity. In H, growth rate differences are explained by the energy acquisition model not coupled with differences in gill surface-areas. These results are not in correspondence with previous studies working with restrictive conditions, which suggested a higher capacity of fast growers to reduce their metabolic rate. The benefits of investing in gill surface-area do not make up for the disadvantages that it implies in the field. 124 Chapter 3: Tidel level shapes growth-rate phenotypes Tide level shapes the growth phenotypes of Mytilus galloprovincialis under field rearing conditions 1 Introduction The temperate shelf waters of the Northeast Atlantic Ocean, in which the southern region of the Bay of Biscay is included, are widely dispersed with populations of the Mediterranean mussel (M. galloprovincialis) (Garmendia et al., 2011; Marigómez et al., 2007; Martínez-Pita et al., 2012). Most of the studies conducted in this region have been focused on the characterization of reproductive cycles (i.e., Garmendia et al., 2010; Ortiz-Zarragoitia et al., 2011; Azpeitia et al., 2017) or in the use of mussels as biomarkers for environmental pollution (Franco et al., 2002; Marigómez et al., 2004; Izagirre and Marigómez, 2009; Jimeno-Romero et al., 2009; Solaun et al., 2013). However, the growing patterns and its implications have not been the focal point of the studies performed with mussels in this area. Azpeitia et al. (2016, 2018) did analyse the growth patterns of M. galloprovincialis in the Bay of Biscay, but with mussels cultured in the open ocean. In the present study, the use of cages anchored to a breakwater allowed the analysis of mussel growth under field conditions in the estuary at two different tidal regimes, on the basis of a homogenously sized population of mussel spat. Natural populations of M. galloprovincialis in the Bay of Biscay experience short-term tidal fluctuations in food availability and composition. The aerial exposure has the most noticeable impact on the intertidal zone, which restricts the time available for food consumption, while forcing the use of metabolic energy on adjusting the responses against hypoxia, desiccation and temperature extremes (Fitzgerald et al., 2012; Leeuwis and Gamperl, 2022). Also tideand wind-driven water movements cause the resuspension of bottom sediments that promote the increment of particle concentration and the dilution of the available phytoplankton (Bayne, 1993). The ability of bivalves to control food-processing rates – either by rejecting poorer quality particles or by changing clearance rates – determines how they are impacted by such variations in particle concentration and quality (Thompson and Bayne, 1974; Bayne et al., 1989; Hawkins et al., 1996; Navarro et al., 1994, 1996; Navarro and Widdows, 1997). Precisely the differences that derive from the efficiency of the physiological mechanisms involved in the energy acquisition (water pumping, particle capture and retention, organic particle selection, and particle hydrolysis and absorption) are one of the underlying causes for inter-individual growth-rate differences. This differential capacity is considered within the acquisition model proposed by Bayne et al., 1999, that condensed the results of studies on the differential growth in three explanatory, yet not-mutually exclusive, models. Besides the acquisition model, two other models might also explain the inter-individual growth rate differences in bivalves. The metabolic efficiency model holds that the efficiency of energy investment in the General discussion 227 In the present study, both in mussels and oysters, and either under laboratory or field conditions, feeding rate and metabolic efficiency showed up as the most important factors in the development of a fast growing phenotype, which has been found to be facilitated by a higher capacity to acquire food that does not imply a higher metabolic expenditure (Chapters 1, 3 and 5). In other words, in all the conditions studied, fast growth was achieved by a combination of the acquisition model and metabolic efficiency model (sensu Bayne, 1999). Innate inter-individual differences in the ability to acquire and process food had been shown on many occasions. The studies by Tamayo et al. (2011, 2013, 2014, 2015, 2016) and Prieto et al. (2018, 2019, 2020 a,b ) settled the idea that inter-individual differences in feeding abilities were determined by the gill surface-area. Under laboratory (Chapter 1) and field conditions at the low intertidal (Chapter 3) we found that slow growing mussels displayed a smaller gill surface-area than fast growing mussels in most scenarios, which indicates a reduced energy allocation towards the filtering structures. Under high intertidal field conditions though, no such a pattern was found, since both fast and slow growing individuals showed similar gill surface-areas (Chapter 3). This indicates that the plasticity of the gill-surface area in relation to growth rate does not seem to be as straightforward or obvious as previously thought. We have demonstrated that under laboratory conditions, when the potentially negative factors that may affect the gill are taken out of the equation (high temperatures, desiccation, oxygen deprivation), the individuals with surplus energy tend to invest in this tissue, as it is advantageous for a better food acquisition. Therefore, the gill becomes a key organ for differential growth phenotypes to develop. However, in nature, the energy is not invested to develop this organ, since the energy disadvantages that a larger exposed surface could bring about might exceed the benefits. One of the outcomes of the present research has been to delve into this idea that size-related inter-individual differences in food acquisition are profusely interconnected with corresponding differences in the gill, albeit providing more dimension to the well-established idea that the gill surface-area is one of the major drivers for the development of different growing phenotypes. In fact, despite the recognised importance of the gill in the research-context of inter-individual growth-rates, there was a knowledge-gap preventing the conduct of an integrated analysis of the growth assessment. The deep analysis performed of the gill structure at tissue level revealed que completa la relevancia de la branquia en la parte de adquisicion del modelo, no es el area sino su funcionalidad provided with additional information that has been so far overlooked in this type of analysis. Ademas hemos desarrollado este indice que puede usarse como herramienta en futuros research developed the gill-structure index as a good indicator of the density of lateral (drivers of the water flow) and latero-frontal cilia (in charge of particle capture and transporting). Thus, the gill structure index represents the density and robustness of the gill ciliary equipment. Although little information is available, it appears that the size of the gill possesses some plasticity, as there is evidence of alteration in the relative size of this organ in response to environmental variation (Tendengren et 228 General discussion al., 1990; Honkoop et al., 2003; Dutertre et al., 2017; Capelle et al., 2021). However, there is no information regarding the possibility of modifying the density of gill cilia in response to alterations of environmental conditions. We found that neither the seasonal factor nor the tidal level affect the gill structure index (Chapter 4), which is only different between fast and slow growing individuals, reinforcing the notion that cilia density is a determining factor in endogenous differences in growth rate. Therefore, histological evidence reported herein confirms a clear relationship between cilia density and growth rate: slow growing individuals consistently showed less cilia and a poorer epithelial structure than fast growers did in their gills. This seems to be related as well to a higher cellular damage that may impede the building of the ciliary mesh. This relationship seems to be a regular pattern in mussels (both under laboratory –Chapter 1–, and field conditions –Chapters 3 and 4–), and oysters (Chapter 5), which confirms that the morpho-functional disparity of the gills is ubiquitous and endogenous for the growing phenotypes. The functioning of the digestive and absorptive organs constitutes a second factor that can potentially shape the differences in the food processing between fast and slow grower individuals, thus completing the physiological basis of the acquisition model. In this study, after the analysis of the proportion of tissues and atrophy in the digestive gland it has been proved that superimposed to the natural variations in the indexes, there was a strong difference between fast and slow growing mussels: slow growers had more atrophied digestive tubules than fast growing mussels in both seasons and tide levels (Chapter 4). Those differences were even more intense between fast and slow growing mussels reared in the laboratory (Chapter 1). Digestive tubules were evidently atrophied and reduced in number, appearing scattered and surrounded by ample areas of connective tissue in slow growers, which means a lower proportion of effective tissue to process food. These findings pave the way for further research and new research lines to detail the underlying causes of the inter-individual differences in digestive capacity. For instance, to understand if the loss of functional digestive capacity in slow growing mussels is the consequence of the previously discussed constrain in the filtering activity or, alternatively, could stem from a cell-damage in the digestive gland similar to that observed in the gill. Even more so when, in contrast to mussels, no differences were found in oysters (Chapter 5). The differences in growth rate between fast and slow growing oysters were much smaller than in mussels. In fact, the oysters analysed in Chapter 5 were 1 year-old adults, during the course of which fast growers grew two times more in length than slow growers. Contrastingly, the mussels analysed in Chapters 1, 3 and 4, were juveniles that developed even larger differences in length in a much shorter period of time of only 3 (in the laboratory – Chapter 1), 6 and 12 months (in the field – Chapters 3 and 4). Thus, it might not be discarded that rather than inter-specific differences alone, such a disparity of results between mussels and oyster could reflect the differences in the growth rate gap between fast and slow growing individuals. Another essential component of the physiological basis for differences in growth phenotypes potential is metabolic efficiency. As aforementioned, the development of higher clearance and absorption rates in fast General discussion 229 individuals did not result in higher routine metabolic rates, indicating that fast individuals have a higher metabolic efficiency. Under different food concentrations, fast growers with higher feeding rates showed a 30 % higher COX activity in their gills, hence indicating higher mitochondrial activity. Yet their oxygen consumption values were the same to those obtained by slow growers. On the one hand, COX activity was only measured in the gills, and it is only representative of the mitochondrial respiration, whereas the oxygen consumption is an estimation that takes into account all the tissues of the individual. On the other hand, lack of concordance between VO 2 and COX activity might indicate that larger amounts of oxygen molecules in slow growers are not coupled to aerobic mitochondrial respiration and ATP synthesis. Since this would be indicative of a lower oxidative capacity of mitochondria, it would explain per se the inter-individual differences in metabolic efficiency. Those oxygen molecules could be futilely lost in the detrimental production of reactive oxygen species (ROS). In fact, a higher ROS production in slow growing individuals would be consistent with the fact that their antioxidant enzyme activities (catalase and glutathione S-transferase) in the gill are two times higher than in fast growing mussels. Furthermore, both antioxidant activities increased even more under low food rations, where a higher ciliary beating is demanded. A potential avenue for further investigation would be to directly analyse ATP production through the use of histochemistry techniques on ATPase enzymes. An examination of the energy balances associated with cellular and mitochondrial energy utilisation would also be a valuable addition to the research. As evidence of this lack of acquisition and metabolic efficiency in slow growers, it has been demonstrated in Chapter 1 under identical laboratory conditions that the accumulation of reserves in the form of adipogranular cells are significantly limited in slow growers, since the accumulation of energy reserves is directly correlated to the clearance rate. Furthermore, the adipogranular cells conform a storage tissue characterised by an abundant protein synthesis, which necessitates a high ATP production to be employed for cellular work. This production may be less efficient in slow growers due to the presumably lower oxidative capacity of their mitochondria, as previously discussed. To further elaborate the metabolic efficiency model is fundamental to consider the differences in energy requirements of the immune system between differentially growing phenotypes. A couple of studies (Saavedra et al., 2017; Prieto et al., 2019) have addressed the differential genetic expression in individuals selected as fast and slow growers under laboratory conditions. Those studies showed that genes involved in the immune response were over-expressed in slow growing individuals, suggesting a higher activity of the immune system. The characteristics of the immunity for the different growing phenotypes have been analysed in oysters in the present study (Chapter 5), leading to the conclusion that slow growing individuals possess the same cell concentration with yet less viability. This implies the need of increasing the haematopoiesis. This dataset indicates that slow growers likely require a higher metabolic demand in the maintenance of their immune system, a higher investment of assimilated energy in keeping the immune function. Furthermore, 230 General discussion although not significant, the haemocytes of slow growing oysters displayed a higher production of ROS, which implies higher costs of growth and that would be coherent with the previously mentioned lower COX and higher antioxidant activities in the gills of slow growing individuals of M. galloprovincialis (Chapter 1). ROS production in the haemocytes is subject to large inter-individual variability, although further research is needed as we only measured it in triploid individuals (Chapter 5). Still strongly suggests that the efficiency of the immunological role of haemocytes is a plastic-enough physiological trait that may contribute to inter-individual differences in growth capacity. When differences in the potential of the immune system are considered in the context of growth disparities, one may ponder the possibility that slow growth is simply the consequence of organisms being unhealthy. In this study, the segregation of fast and slow growing organisms in the field allowed the development of the growing phenotypes under natural conditions that include the presence of parasites, among many other environmental hazards. We found that fast growing mussels have a higher parasitic load than slow growing individuals, which categorically rejects the possibility of inter-individual growth rate differences being related to differential health status. A greater food acquisition per unit of time and a larger clearance area (i.e., larger gills) unavoidably implies a higher exposure to the environment by fast growers, since, indeed, they do nothing but increase the probability of parasite encounter and subsequent infection (Chapter 4). Yet a greater parasitic load does not prevent them from obtaining the highest values of SFG and growth rates. This can only mean that fast growers have high tolerance to parasitic infection, reinforcing the notion that their immune system is more capable. The opposite is found in slow growers, which, as a consequence of their less-effective organs, decrease their food consumption and absorption, reducing in exchange their exposure to the environment. Fortuitously, a lower exposure might protect them against parasitic infection, not only minimising the parasitic intensities, but also limiting the trophic resources available for parasites. Furthermore, given that the immune system of slow growers seems to be considerably less robust and less effective, such limitation in parasite loading highly likely increases their chances for survival. Thus far, it has become quite clear that differences in growth rate are based on distinctive features concerning the different levels of biological organisation, which explain in depth the acquisition and the metabolic efficiency models. Actually, the comprehensive interpretation of our data suggests that both models are inextricably linked by a primary cause that is related to genuine differences between individuals. Less efficient mitochondria in the gills of slow growers would lead to a lower aerobic ATP synthesis in the cells and a higher production of reactive oxygen species, which could cause cell damage in the gill. This affects the structure of the organ disabling its potential to develop a sufficiently capable ciliary network for proper food acquisition. As a result, the animal is unable to obtain enough energy from the environment, leading to a reduced growth rate. In addition, this consubstantial nature of the acquisition and metabolic efficiency models seems to occur in any of the tested conditions in the laboratory and in the field; along seasons (gonadal development), and at General discussion 231 different tidal levels. However, in the field, the situation becomes more complex and the constraints on the specific metabolic efficiencies of slow growers may necessitate specific adaptations affecting both energy acquisition and energy redistribution that requires a careful case-by-case analysis. As previously stated, in laboratory conditions where animals were provided with a restricted amount of food, fast growers developed by means of an enhanced capacity to minimise standard energy expenditure (Tamayo et al., 2016; Prieto et al., 2018). Our findings have demonstrated that this energy saver phenotype does not occur in natural conditions with trophic limitation (high intertidal), most probably because in the field there are numerous other factors besides food that require high energy levels for maintenance. Costly processes such as somatic maintenance and repair, reproduction, and growth compete for resources and when energy is not at its highest it is impossible to maximise allocation to them all, so trade-offs must happen. Hence, the third model of energy redistribution (i.e., allocation model) may also be implicated in the development of the diverse growth phenotypes, aiding in the understanding of inter-individual growth rate variability. The panorama of the mussels reared at low intertidal analysed in May (Chapters 3 and 4) directly confronts us with this possibility. This is the only case with no clear behaviour of acquisition and metabolic efficiency models, as in fact both fast and slow growers filtered similarly and obtained not different SFG values. This can only indicate that in slow growers a substantial part of the assimilated energy would be invested in tissue production that is either released to the environment (gamete or byssus production) or trapped in the shell. Shell growth has been demonstrated to be a plastic component in mussels since shell density and shape was found to change along seasons and tide levels (Chapter 2). In spite of the variability of this morphological trait, no differences were observed between the shell traits of fast and slow growing mussels (Chapter 4), although there is an intrinsic allometric difficulty when analysing such attributes. The only differences in shell were found not in their morphology but in their composition between the shells of fast and slow growing oysters in Chapter 5. Fast growing oysters showed a much higher accumulation of organic matter in their shells, which might in fact indicate a higher energy investment. Still, it should be noted that oyster and mussel shells are different in their attributes. Oyster shells are much more irregular, much rougher or rugged, and corrugated compared to mussel shells, which are more uniform, smooth and possess a more organised internal structure. Differential shell characteristics are likely related with their biology, as while mussels are attached to rocks using byssus threads, oysters are cemented to hard substrates using their own shell material as cement and they need to adjust the shell-shape to the available space in the complex three-dimensional lattice of the oyster bed. In addition, oyster shells are generally more fragile and prone to fracture than mussel shells, which may require greater energy investments in their regeneration. This process necessitates higher frequencies of periostracum production (solely composed of organic matter) and probably benefits from the accumulation of higher organic matter percentage in the layers of the organic matrix that serve as a basis for the deposition 232 General discussion of calcium carbonate crystals in the shell (Watabe, 1984; Falini et al., 1996; Choi and Kim, 2000). Further research would be interesting to analyse if this difference in organic matter production happens also in mussels and, consequently, a different energy investment. Gonadal development and spawning are submitted to endocrine control in bivalves (see Osada and Matsumoto 2016, for review). The histological analysis described in Chapter 4 has shown the existence of clear differences in the intensity of follicle atresia between fast and slow growing mussels. Higher atresia levels in fast growers indicate that they are able to recover a substantial part of their gonadal investment. Atresia is considered to be a response to unfavourable environmental conditions, a physiological regulatory mechanism controlling the number ofoocytes tobespawned (Benninger, 2017)andallowing thereallocation ofenergyfrom reproduction towards somatic growth, defence and repair mechanisms to ensure survival (Gagné et al., 2011, Vazquez et al., 2021). By eliminating non-viable oocytes, (turning on atresia processes), mussels can redirect energy and resources to maintaining healthier oocytes or other physiological functions, contributing to general energy efficiency (Gustafsson et al., 2019). Although excessive atresia can lead to a significant reduction in the overall reproductive output (Pérez et al., 2015), it also ensures that only the most viable oocytes are retained, enhancing the likelihood of successful fertilisation and offspring survival (Lowe et al., 2015). In our study (Chapter 4), follicular atresia levels and the differences in atresia levels between fast and slow growing mussels were found to be higher at the high intertidal cage, i.e., at the most energetically constraining environment. Besides affecting the gonadal/somatic tissue investment ratio, atresia intensity probably affects the pace of gonadal development. For instance, given the reduced capacity to reabsorb gonadal tissue in slow growing individuals, the scarce surplus energy assimilated by these organismswould be preferentially allocated towards gonadal production, thus accelerating gamete production and spawning. Indeed, the histological analysis of the gamete developmental stages (Chapter 4) appear to support the idea that slow growers at high tide level display an earlier reproduction timing than fast growers. Prioritising the allocation of energy into gonadal development forces slow growing individuals to release gametes over a shorter period of time and earlier in the season. The shortening of reproductive time might perhaps be beneficial to slow growing individuals since it might potentially allow conservation of energy for physiological defences for longer periods of time. The differences in atresia levels between differentially growing phenotypes during the reproductive period recorded in this study strongly support the possibility that atresia processes regulating gonadal/somatic allocation of energy might be a determining factor in the occurrence of inter-individual differences in growth rate. Beninger (2017) has indicated that “atresia is a widespread, yet seldom identified phenomenon in marine bivalves, which probably affects previous and current data on fecundity and reproductive effort both in wild and culture populations” and has considered to be an exciting field of future research. In November, at both tidal levels, fast and slow growing mussels diverge significantly in three physiological traits: condition index, gill structure index and standard metabolic rate. Fast growing mussel specimens General discussion 233 have higher levels of these three parameters than their slow growing counterparts, a difference that was much more pronounced in the low intertidal. These results show that under highly stressful environmental circumstances caused by low food availability and high presence of parasites, fast growth is linked not only to the maintenance of a high cilia-density in the gill but also to the possession of a higher standard metabolic expenditure. Since the mussels are at resting reproductive period and have elevated intensities of parasite infection, it seems likely that the increased standard metabolic rate displayed by fast growing specimens represents an extra energy investment in the maintenance of a more effective or active immune system, meaning appropriate rates of haemocyte synthesis and maintenance. In fact, the need for a higher energy investment in defence mechanisms to fight parasite loading impedes the occurrence of the energy saver phenotype that it does emerge under aseptic laboratory rearing conditions. To put it briefly, a higher gill structure index guarantees a greater and more efficient food acquisition (i.e., enhanced acquisition and metabolic efficiency models), allowing the gain of an energy surplus that can be redirected towards efficient defence processes (allocation model). Consequently, in this instance, the skilfully woven assembly of the three energetic models working together predictably shapes the development of the different growing phenotypes. References Bayne, B. L. (1999). Physiological components of growth differences between individual oysters (Crassostrea gigas) and a comparison with Saccostrea commercialis. Physiological and biochemical zoology, 72(6), 705-713. Beninger, P. G. (2017). Caveat observator: the many faces of pre-spawning atresia in marine bivalve reproductive cycles. Marine Biology, 164(8), 163. Capelle, J. J., Hartog, E., van den Bogaart, L., Jansen, H. M. and Wijsman, J. W. (2021). Adaptation of gill-palp ratio by mussels after transplantation to culture plots with different seston conditions. Aquaculture, 541, 736794. Choi, C. S. and Kim, Y. W. (2000). A study of the correlation between organic matrices and nanocomposite materials in oyster shell formation. Biomaterials, 21(3), 213-222. Dutertre, M., Ernande, B., Haure, J. and Barillé, L. (2017). Spatial and temporal adjustments in gill and palp size in the oyster Crassostrea gigas. Journal of Molluscan Studies, 83(1), 11-18. Falini, G., Albeck, S., Weiner, S. and Addadi, L. (1996). Control of aragonite or calcite polymorphism by mollusk shell macromolecules. Science, 271(5245), 67-69. Gagné, F., Bouchard, B., André, C., Farcy, E. and Fournier, M. (2011). Evidence of feminization in wild Elliptio complanata mussels in the receiving waters downstream of a municipal effluent outfall. Comparative 234 General discussion Biochemistry and Physiology Part C: Toxicology and Pharmacology, 153(1), 99-106. Honkoop, P. J. C., Bayne, B. L. and Drent, J. (2003). Flexibility of size of gills and palps in the Sydney rock oyster Saccostrea glomerata (Gould, 1850) and the Pacific oyster Crassostrea gigas (Thunberg, 1793). Journal of Experimental Marine Biology and Ecology, 282(1-2), 113-133. Prieto, D., Arranz, K., Urrutxurtu, I., Navarro, E., Urrutia, M. B. and Ibarrola, I. (2020b). Variable Capacity for Acute and Chronic Thermal Compensation of Physiological Rates Contributes to Inter-Individual Differences in Growth Rate in Mussels (Mytilus galloprovincialis). Frontiers in Marine Science, 7, 577421. Prieto, D., Markaide, P., Urrutxurtu, I., Navarro, E., Artigaud, S., Fleury, E., ... and Urrutia, M. B. (2019). Gill transcriptomic analysis in fast-and slow-growing individuals of Mytilus galloprovincialis. Aquaculture, 511, 734242. Prieto, D., Tamayo, D., Urrutxurtu, I., Navarro, E., Ibarrola, I. and Urrutia, M. B. (2020). Nature more than nurture affects the growth rate of mussels. Scientific reports, 10(1), 3539. Prieto, D., Urrutxurtu, I., Navarro, E., Urrutia, M. B. and Ibarrola, I. (2018). Mytilus galloprovincialis fast growing phenotypes under different restrictive feeding conditions: Fast feeders and energy savers. Marine environmental research, 140, 114-125. Saavedra, C., Milan, M., Leite, R. B., Cordero, D., Patarnello, T., Cancela, M. L. and Bargelloni, L. (2017). A microarray study of carpet-shell clam (Ruditapes decussatus) shows common and organ-specific growthrelated gene expression differences in gills and digestive gland. Frontiers in Physiology, 8, 943. Sokolova, I. (2018). Mitochondrial adaptations to variable environments and their role in animals’ stress tolerance. Integrative and Comparative Biology, 58(3), 519-531. Tamayo, D., Azpeitia, K., Markaide, P., Navarro, E.andIbarrola, I. (2016). Food regimemodulatesphysiological processes underlying size differentiation in juvenile intertidal mussels Mytilus galloprovincialis. Marine Biology, 163, 1-13. Tamayo, D., Ibarrola, I. and Navarro, E. (2013). Thermal dependence of clearance and metabolic rates in slow-and fast-growing spats of manila clam Ruditapes philippinarum. Journal of Comparative Physiology B, 183, 893-904. Tamayo, D., Ibarrola, I., Cigarría, J. and Navarro, E. (2015). The effect of food conditioning on feeding and growth responses to variable rations in fast and slow growing spat of the Manila clam (Ruditapes philippinarum). Journal of Experimental Marine Biology and Ecology, 471, 92-103. Tamayo, D., Ibarrola, I., Urrutia, M. B. and Navarro, E. (2011). The physiological basis for inter-individual General discussion 235 growth variability in the spat of clams (Ruditapes philippinarum). Aquaculture, 321(1-2), 113-120. Tamayo, D., Ibarrola, I., Urrutxurtu, I. and Navarro, E. (2014). Physiological basis of extreme growth rate differences in the spat of oyster (Crassostrea gigas). Marine biology, 161, 1627-1637. Tedengren, M., André, C., Johannesson, K. and Kautsky, N. (1990). Genotypic and phenotypic differences between Baltic and North Sea populations of Mytilus edulis evaluated through reciprocal transplantations. III. Physiology. Marine ecology progress series, 221-227. Watabe, N. and Pan, C. M. (1984). Phosphatic shell formation in atremate brachiopods. American Zoologist, 24(4), 977-985. 236 General discussion Conclusions 1. The gill surface-area is a key factor for the development of inter-individual growth rate differences under laboratory rearing conditions. The relationship between gill-surface area and growth rate under field rearing conditions is not as strong as in the laboratory, and is not as decisive for the development of the different growth phenotypes. 2. A clear relationship between cilia density and growth rate is confirmed, the phenotypes with the lowest growth rates always display less cilia and a poorer epithelial structure than those with the highest growth rates. This factor is in every circumstance and without exception different in fast and slow growers, setting up as a pivotal factor in the development of the growing phenotypes. That could be related to a higher cellular damage that may impede the building of the ciliary mesh. 3. The acquisition and metabolic efficiency models are intrinsically linked by a primordial cause involving the reduced mitochondrial oxidative capacity of slow growers, resulting in an increased ROS production and provoking metabolic damage. This would cause structural damage to the gill weakening its capacity for food acquisition, resulting in reduced energy incorporation. 4. The slow growing phenotype has a lower capacity of digestion and/or absorption than the fast growing phenotype, regardless of the food ration: less proportion of effective digestive tissue in their digestive gland, as well as higher atrophy in the digestive tubules. Without the limitation in food acquisition at high food ration, this difference could be crucial for the development of the growing phenotypes, in which having a better-developed filtration mechanism does not imply a functional advantage. 5. The natural environment makes the allometric relationship of the metabolism change. A cause-effect relationship between habitats and scaling exponents can be established, demonstrating that different standardisation values for metabolic rate need to be used when working with populations of different habitats. For intertidal mussels the scaling exponent is always around 2/3 (0.66), whereas subtidal mussels increase the scaling exponent from 0.64 to 0.87 when activity is developed. 6. Under restrictive trophic conditions in the field (high intertidal), fast growers did not develop through a lowered standard metabolic rate (energy savers), but through increased acquisition and the metabolic efficiency models. However, in the field, those two models are complemented by the allocation model when shaping the different growth phenotypes. The energy allocation materialises in the unrestrained gamete release of slow growers and a much higher capacity of fast growers for gamete reabsorption. The reabsorption allows fast growers not to waste the energy invested in such an expensive tissue and to redirect it to somatic growth.