E T Université

Laboratoires

Soraya Álvarez-Codesal

Cara A Faillace

Alexandre Garreau

Elvire Bestion

Alexis D Synodinos

José M Montoya

Louane Matos

Bénédicte Lalot

José M Montoya

Jose M Montoya

Synodinos, A.D J M Montoya

Ecological and evolutionary implications of warming on consumer-resource dynamics xii

Keywords: climate warming, consumer-resource interactions, interaction strength, phytoplankton physiology, temperature dependence, thermal performance curves, zooplankton physiology

e general objective of this PhD thesis is to understand the ecological and evolutionary e ects of temperature on both resource and consumer species and their interactions. is will allow for improved prediction of temperature changes to community dynamics to help us to better forecast the consequences of di erent climatic warming scenarios. To do so, this thesis is organised in 4 chapters, each addressing thermal dependencies, and evolutionary responses, of di erent constituent parameters of consumer-resource models. In chapter 1, I explore the thermal dependencies of the parameter `f` referred to as the e ect of the consumer on the resource by measuring the e ect of temperature on the interaction strength and the balance between energy gain and loss of two consumer-resource pairs. In chapter 2, I aim to understand evolutionary responses of `f`, measured again as interaction strength, in conjunction with the energetic balances for populations of consumers and resources that have experienced long-term (i.e., 13 years) exposure to experimental warming. In chapter 3, I examine ecological and evolutionary responses of resource growth rate, r, nutrient acquisition, and its carrying capacity, K, across a temperature gradient using contrasting populations of two resource species that di er in their thermal background history. In chapter 4, I investigate thermal dependencies of mortality in consumers, measured as survival rates across two temporal scales, in acute and life-long exposures to temperature. In addition, in this chapter I evaluate whether changes in demographic traits (e.g., fecundity) exhibited a compensatory relationship that explained di erences observed in survival between unevolved and evolved populations of the consumer across temperatures. Chapter 1 and 2 focused on resources, consumers, and their interaction, and Chapter 3 and 4 on resources and consumers respectively. While the rst chapter only considers ecological responses to warming, the remaining chapters consider both ecological and evolutionary responses to changing temperatures. Here, I use an empirical approach employing di erent populations of species collected and isolated from two semi-natural freshwater communities that di ered in their long-term thermal histories.

In this thesis I showed that we can scale up from physiological responses of species to improve our understanding of warming e ects on species interactions. Additionally, this approach can provide insights about the consequences of evolution on interactions among species through changes to their physiology. Finally, I demonstrated that for a more complete understanding we need to consider how trade-o s and compensation across the life history of an organism can either constrain or enable evolutionary responses to temperature, ultimately in uencing the responses of species and communities to climate warming.

Résumé

L' objectif général de cette thèse est de comprendre les e ets écologiques et évolutifs de la température sur les espèces ressources et consommatrices et leurs interactions. Cela permettra d'améliorer la prédiction des changements de température sur la dynamique des communautés pour nous aider à mieux prévoir les conséquences de di érents scénarios de réchau ement climatique. Pour ce faire, cette thèse est organisée en 4 chapitres, chacun abordant les dépendances thermiques, et les réponses évolutives, des di érents paramètres constitutifs des modèles consommation-ressource. Dans le chapitre 1, j' explore les dépendances thermiques du paramètre `f` appelé e et du consommateur sur la ressource en mesurant l' e et de la température sur la force d'interaction et l' équilibre entre gain et perte d' énergie de deux paires consommateur-ressource. Dans le chapitre 2, je vise à comprendre les réponses évolutives de `f`, mesurées à nouveau comme force d'interaction, en conjonction avec les bilans énergétiques pour les populations de consommateurs et de ressources qui ont subi une exposition à long terme (c' est-à-dire 13 ans) au réchau ement expérimental. Dans le chapitre 3, j' examine les réponses écologiques et évolutives du taux de croissance des ressources, r, de l'acquisition des nutriments et de sa capacité de charge, K, à travers un gradient de température en utilisant des populations contrastées de deux espèces ressources qui di èrent dans leur histoire de fond thermique. Dans le chapitre 4, j' étudie les dépendances thermiques de la mortalité chez les consommateurs, mesurées en tant que taux de survie sur deux échelles temporelles, lors d' expositions aiguës et permanentes à la température. De plus, dans ce chapitre, j' évalue si les changements dans les caractéristiques démographiques (par exemple, la fécondité) présentaient une relation compensatoire qui expliquait les di érences observées dans la survie entre les populations non évoluées et évoluées du consommateur à travers les températures. Les chapitres 1 et 2 se sont concentrés sur les ressources, les consommateurs et leur interaction, et les chapitres 3 et 4 sur les ressources et les consommateurs respectivement. Alors que le premier chapitre ne considère que les réponses écologiques au réchau ement, les chapitres restants considèrent à la fois les réponses écologiques et évolutives aux changements de température. Ici, j'utilise une approche empirique utilisant di érentes populations d' espèces collectées et isolées de deux communautés d' eau douce semi-naturelles qui di èrent dans leurs histoires thermiques à long terme.

En résumé, dans cette thèse, j'ai montré que nous pouvons passer à l' échelle des réponses physiologiques des espèces pour améliorer notre compréhension des e ets du réchau ement sur les interactions entre espèces. De plus, cette approche peut fournir des informations sur les conséquences de l' évolution sur les interactions entre les espèces par le biais de modi cations de leur physiologie. En n, j'ai démontré que pour une compréhension plus complète, nous devons considérer comment les compromis et la compensation tout au long de la vie d'un organisme peuvent soit contraindre, soit permettre des réponses évolutives à la température, in uençant nalement les réponses des espèces et des communautés au réchau ement climatique.

First, I would like to thank my supervisor Jose M. Montoya for giving me the great opportunity to be part of the FRAGCLIM project at the Station d'Ecologie éorique et Expérimentale (SETE) in Moulis. I am extremely grateful for everything he has taught me in the eld of ecology, to have a critical mind and particularly to look beyond the detail, with a more general perspective. I hope I was able to take advantage of all his knowledge to be able to apply it in the best productive way. is thesis has also been possible in large part to my co-supervisor Cara A. Faillace. ank you for always being there, for being a great supervisor and a great friend. She has always been available to discuss any idea, answer questions or plan experiments. We have experienced intense periods of laboratory experiments together, challenging, but also extremely inspiring and fun. I will not forget the days when the lab got to tropical temperature conditions or when the oor got ooded because of the cooling system. All the trips we made together for eld sampling, sample processing and conferences abroad gave me the opportunity to discover the great scientist and a wonderful person. I hope our paths cross some time again in the future.

Second, I want to thank all my colleagues from the FRAGCLIM (and related) project: Alexandre, Elvire, Alexis, Vinicius, Dani, Arnaud Sentis, Louane and Bénédicte. Being part of the FRAGCLIM team has been awesome. It has been one of the most intellectually stimulating and challenging activities of my life. We always had freedom to propose ideas, methodologies and discuss all kinds of laboratory and eld materials. Coming from the eld of aquatic ecology focused on monitoring and eld sampling, it has been a joy to have the most advanced materials always available in the lab. I will never forget the trip to Dorset in January 2019. e intense hours of ltering, sample processing and seeing countless di erent taxa of algae, ciliates, protists, amoebas... etc., with Cara, Jose, Alexandre and Elvire. e pints of beer in the pub a erwards never taste so good and the great thing is that this trip brought us all much closer together ever since.

All the experiments presented in this thesis would not be possible without the work and dedication of Alexandre. I want to thank him for always understanding me exceptionally in each laboratory manipulation and experiment. Even when things were not looking good, he always found a way to solve problems with the best attitude. It has been a pleasure working with him. Additionally, Elvire has not only given me enormous help and support in all experiments of this thesis, particularly with the cytometer, but she has also been my "guru" and inspiration for data analysis using all kinds of packages of the R-statistical so ware. She has stimulated my desire to learn and improve my analytical skills. Alexis, Dani and Vinicius, for being always there to provide support and listening to all my doubts and fears. Louane and Bénédicte, your superb work in the lab and the experience being for the rst time a mentor of a master student was one of the most rewarding tasks of my PhD.

I owe a huge amount to all the people that in one way or another supported technically my project. I thank the J.I. Jones laboratory, Genoveva Estevan, and John Davy-Bowker for helping with plankton sampling and isolation in Dorset, UK, Dr Antonio Guillén Oterino for aiding with Daphnia identi cation, David Pecqueur for helping with full algal isolation at the CNRS Arago Laboratory in Banyuls-sur-Mer and Cristina Diez Vives for helping with the con rmation of algal-sequencing data. An important person to mentioned in regards to general laboratory support and experimental discussion is Michelle Huet. e COVID-19 sanitary lock-down measures put in place in March 2020 severely hampered my experiments, leading to a signi cant delay in data collection for all my thesis chapters. e immense work carried out by Michelle Huet during the lock-down permitted the survival of all clonal populations of both algae and Daphnia. Without her work and commitment over this period I would not be presenting anything gathered in this PhD manuscript. I cannot thank you enough for that. Merci beaucoup Michelle!!!! I would like to also thank additional people from SETE who helped me get through the last four years, providing technical and/or personal support: Julie, Nuria, Diego, Vini, Laurane, Dalila, Jade, Severine, Murielle, Marine, Soonmi, Michael, Rick, Rebeca, Eloise, Allan, Laura, Camille, David, Yuval, Kirsten, Aisha, Keoni, Azenor and Jeremy. Without the people at the station, these years would have been nowhere near as enjoyable. We shared co ees and worries, all kinds of halva, vegie lunches at the CBTM, frisbee, parties at la casa de la cumbia and hikes.

Finally, I would like to thank my friends and family. Living in the great French Pyrenees has been an incredible experience. Quiero mencionar a todos los amigos que he hecho a lo largo de estos años en Saint Girons. Habéis sido mi familia y mi soporte emocional durante estos años. Por todas las rutas de montaña, las acampadas, cenas, viajes y mudanzas internacionales. A todos vosotros, gracias: Sara, Mike, Rebeca, Dani, Alexis, Lida, Romina, Leon, Maleni, Juan, Angel, Rocio y Jose. En especial me gustaría mencionar a Dani y Cari (y Olivia y Maya), por todas las noches de cenas, antes, durante y después del Covid. Habéis sido un pilar súper importante. To all my Friends and colleagues at the Freshwater Biological Association in the UK. You all have been a great inspiration to me. To Roger, Anne, Mel, Gary, Nick, Isabelle and Ross. A mis amigas, que siempre tienen formas de alegrarme los días y sacarme una sonrisa a pesar del estrés y la ansiedad: Raquel, Isabel, Elisa, Irene, Ana, Lucia y Nerea. Me muero de ganas por pasar más tiempo con vosotras. A los profesionales que me habéis acompañado en estos últimos meses, Pep Toni, Azucena y Lucia de Ostraca. Gracias

General introduction

Climate change is a reality. By 2020, the global temperature increased by 1.1°C compared to the historical average in global surface temperature relative to 1850-1900[START_REF] Masson-Delmotte | Climate Change 2021: e Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change[END_REF], and it is expected to increase even more (up to 2-5 degrees depending on the scenario) over the next 100 years (Fig. I.1). Climate change does not only bring increases in mean surface temperature (so-called warming), but also an intensi cation in extreme weather events such as more severe heat waves, as well as new historic droughts and oods [START_REF] Donat | More extreme precipitation in the world's dry and wet regions[END_REF][START_REF] Stott | How climate change a ects extreme weather events[END_REF][START_REF] Stott | Attribution of extreme weather and climate-related events[END_REF][START_REF] Masson-Delmotte | Climate Change 2021: e Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change[END_REF]. Climate change is one of many facets of anthropogenic global change, along with habitat change, pollution, invasive alien species and direct exploitation of natural resources. A recent global meta-analysis [START_REF] Jaureguiberry | e direct drivers of recent global anthropogenic biodiversity loss[END_REF] showed that climate warming only ranks third in importance in terms of direct e ects on population extinctions and biodiversity loss, following habitat change and pollution. However, in terms of the impacts on community composition, global warming is the primary global stressor [START_REF] Jaureguiberry | e direct drivers of recent global anthropogenic biodiversity loss[END_REF]. ese ndings emphasise the need to examine and dissect the e ects of temperature on species and their interactions with other species within the wider ecological network.

Warming has effects across multiple levels of biological organization

Climate change is a ecting di erent levels of biological organisation. Early studies focused on population and species-level e ects, showing species range shi towards higher latitudes and elevations as climate warms [START_REF] Hughes | Biological consequences of global warming: is the signal already apparent?[END_REF][START_REF] Parmesan | A globally coherent ngerprint of climate change[END_REF][START_REF] Lurgi | Climate change impacts on body size and food web structure on mountain ecosystems[END_REF] along with numerous phenological changes [START_REF] Parmesan | A globally coherent ngerprint of climate change[END_REF][START_REF] Root | Fingerprints of global warming on wild animals and plants[END_REF][START_REF] Parmesan | Observed Impacts of global climate change in the U.S. Pew Center on Global Climate Change[END_REF]. Warmer temperatures will thus have a signi cant impact on community composition and the organisation of biodiversity within ecological networks [START_REF] Gitay | Climate change and biodiversity[END_REF][START_REF] Woodward | Climate change and freshwater ecosystems: impacts across multiple levels of organization[END_REF][START_REF] Dawson | Beyond predictions: Biodiversity conservation in a changing climate[END_REF][START_REF] Dossena | Warming alters community size structure and ecosystem functioning[END_REF][START_REF] Jaureguiberry | e direct drivers of recent global anthropogenic biodiversity loss[END_REF].

Species that coexist and interact within a given community can have di erential responses to temperature change [START_REF] Mertens | Escaping herbivory: ocean warming as a refuge for primary producers where consumer metabolism and consumption cannot pursue[END_REF]. Combined with ongoing and predicted changes in climatic regimes (e.g., increasing mean temperatures, earlier onset of growing season, etc.), spatial and temporal mismatches can arise because not all species will respond similarly, and thus species interactions can be lost across space or time, ultimately inducing changes in community structure, species composition and dynamics [START_REF] Montoya | Climate change, biotic interactions and ecosystem services[END_REF]Lurgi et al. 2012a, a;[START_REF] Boukal | Species interactions under climate change: connecting kinetic e ects of temperature on individuals to community dynamics[END_REF]. A typical example concerns the phenology of interacting species, when the owering of plants can precede the emergence of the majority of pollinators, thus impacting the functioning of the community. Such changes will probably alter the distributions, abundancies and extinction probabilities of species [START_REF] Carpenter | Onethird of reef-building corals face elevated extinction risk from climate change and local impacts[END_REF][START_REF] Deutsch | Impacts of climate warming on terrestrial ectotherms across latitude[END_REF]. Given the signi cance of emergent mismatches between species that interact, it is important to have a good understanding of the underlying mechanisms which, rst, cause di erential responses to temperature change and, second, will drive the dynamics of interacting species.

A less explored but pivotal topic is how warming a ects the strength of trophic interactions. In food web ecology, quantifying interaction strength is key to assess the e ects of species interactions on population and community dynamics both empirically and theoretically. e strength of trophic interactions is key for community dynamics because it determines how much energy and materials ow through the food web [START_REF] Mccann | Weak trophic interactions and the balance of nature[END_REF][START_REF] Brose | Allometric scaling enhances stability in complex food webs[END_REF][START_REF] Rooney | Integrating food web diversity, structure and stability[END_REF]. Interaction strength has multiple de nitions, but overall it describes how changes in the biomass of one species a ect the other species' biomass densities [START_REF] Wootton | Measurement of interaction strength in nature[END_REF][START_REF] Berlow | Simple prediction of interaction strengths in complex food webs[END_REF]. In general, warming is likely to change the distribution of interaction strengths. Consumerresource interaction strength has been shown to increase with temperature [START_REF] Sanford | Regulation of keystone predation by small changes in ocean temperature[END_REF][START_REF] O'connor | Warming strengthens an herbivore-plant interaction[END_REF][START_REF] Rall | Universal temperature and body-mass scaling of feeding rates[END_REF][START_REF] Sampaio | Interaction strength between di erent grazers and macroalgae mediated by ocean acidi cation over warming gradients[END_REF][START_REF] Schaum | Temperature-driven selection on metabolic traits increases the strength of an algalgrazer interaction in naturally warmed streams[END_REF]) which has been argued to make biomass distributions more top-heavy, i.e., higher trophic levels of a food web show higher biomass distributions [START_REF] Hoekman | Turning up the heat: Temperature in uences the relative importance of top-down and bottom-up e ects[END_REF][START_REF] Shurin | Warming shi s topdown and bottom-up control of pond food web structure and function[END_REF][START_REF] Velthuis | Warming advances top-down control and reduces producer biomass in a freshwater plankton community[END_REF][START_REF] Barbier | Pyramids and cascades: a synthesis of food chain functioning and stability[END_REF], reducing consumer extinction risk [START_REF] Synodinos | eory of temperaturedependent consumer-resource interactions[END_REF]) and ultimately a ecting community dynamics and functioning [START_REF] Petchey | Environmental warming alters food-web structure and ecosystem function[END_REF][START_REF] Friberg | Relationships between structure and function in streams contrasting in temperature[END_REF][START_REF] Woodward | Climate change and freshwater ecosystems: impacts across multiple levels of organization[END_REF][START_REF] Demars | Temperature and the metabolic balance of streams[END_REF][START_REF] O'gorman | Impacts of Warming on the Structure and Functioning of Aquatic Communities[END_REF][START_REF] Yvon-Durocher | Five Years of Experimental Warming Increases the Biodiversity and Productivity of Phytoplankton[END_REF][START_REF] Zander | E ects of temperature variability on community structure in a natural microbial food web[END_REF][START_REF] Robinson | Temperature e ects on the temporal dynamics of a subarctic invertebrate community[END_REF]. On the other hand, some evidence shows that warming weakens interaction strength [START_REF] Rall | Universal temperature and body-mass scaling of feeding rates[END_REF], which may imply higher stability of populations and more persistent communities by dampening uctuations over time [START_REF] Vasseur | A Mechanistic Approach for Modeling Temperature-Dependent Consumer-Resource Dynamics[END_REF][START_REF] Binzer | e dynamics of food chains under climate change and nutrient enrichment[END_REF][START_REF] Fussmann | Ecological stability in response to warming[END_REF]). Besides interaction strength there exist other interacting factors, such as an increase in nutrient availability, that can jointly a ect food-web stability and structure by modifying the strength of trophic interactions [START_REF] O'connor | Warming and resource availability shi food web structure and metabolism[END_REF][START_REF] Binzer | e dynamics of food chains under climate change and nutrient enrichment[END_REF][START_REF] Binzer | Interactive e ects of warming, eutrophication and size structure: Impacts on biodiversity and food-web structure[END_REF][START_REF] Kratina | Warming modi es trophic cascades and eutrophication in experimental freshwater communities[END_REF][START_REF] Sentis | Towards a mechanistic understanding of temperature and enrichment e ects on species interaction strength, omnivory and foodweb structure[END_REF][START_REF] Sentis | Stoichiometric constraints modulate the e ects of temperature and nutrients on biomass distribution and community stability[END_REF].

Recently, evidence has accumulated on the e ects of climate change on ecosystem functioning [START_REF] Montoya | Climate change, biotic interactions and ecosystem services[END_REF][START_REF] Walther | Community and ecosystem responses to recent climate change[END_REF][START_REF] Woodward | Climate change and freshwater ecosystems: impacts across multiple levels of organization[END_REF]Dossena et al. 2012;[START_REF] Grimm | e impacts of climate change on ecosystem structure and function[END_REF][START_REF] Perkins | Higher biodiversity is required to sustain multiple ecosystem processes across temperature regimes[END_REF]Garcia et al. 2018;[START_REF] Bestion | Phytoplankton biodiversity is more important for ecosystem functioning in highly variable thermal environments[END_REF]. For example, in aquatic systems, warming has been found to have signi cant impacts on the metabolic balance of ecosystems, with ecosystem respiration increasing faster than primary production, converting these systems from sinks to sources of atmospheric CO 2 over certain periods of time [START_REF] Lopez-Urrutia | Scaling the metabolic balance of the oceans[END_REF]Yvon-Durocher et al. 2010b). Warming can also modify the relationship between biodiversity and ecosystem function, where more diversity is required to maintain ecosystem functioning under stressing temperature conditions [START_REF] García | Changes in temperature alter the relationship between biodiversity and ecosystem functioning[END_REF][START_REF] Bestion | Phytoplankton biodiversity is more important for ecosystem functioning in highly variable thermal environments[END_REF]. In cconsequence, under future warmer conditions, the loss of biodiversity is likely to have a stronger negative impact on the functioning of ecosystems.

While we now have an understanding of some of the e ects of warming beyond species (i.e., on species interactions, communities and ecosystems), important gaps in our understanding remain. In particular, limitations in experimental approaches on species and trophic interactions means that we still lack mechanistic understanding about how these are a ected by temperature changes. e research gap in species interactions also extends to our current theoretical understanding of the e ects of warming. Species distribution models are a good example. Models on the e ects of warming on future species distribution have mostly ignored biotic interactions [START_REF] Pearson | Predicting the impacts of climate change on the distribution of species: Are bioclimate envelope models useful?[END_REF][START_REF] Uiller | Predicting global change impacts on plant species' distributions: Future challenges[END_REF][START_REF] Lavergne | Biodiversity and climate change: Integrating evolutionary and ecological responses of species and communities[END_REF][START_REF] Staniczenko | Predicting the e ect of habitat modi cation on networks of interacting species[END_REF], leading to inaccurate predictions. Predictions have generally improved a er species interactions were integrated into the modelling frameworks [START_REF] Heikkinen | Biotic interactions improve prediction of boreal bird distributions at macro-scales[END_REF][START_REF] Kissling | Towards novel approaches to modelling biotic interactions in multispecies assemblages at large spatial extents[END_REF][START_REF] Kissling | Estimating extinction risk under climate change: next-generation models simultaneously incorporate demography, dispersal, and biotic interactions[END_REF][START_REF] Kissling | Multispecies interactions across trophic levels at macroscales: Retrospective and future directions[END_REF]. At smaller spatial scales, though, important theoretical advancements have occurred, incorporating species interactions and traits into such models [START_REF] Vasseur | A Mechanistic Approach for Modeling Temperature-Dependent Consumer-Resource Dynamics[END_REF][START_REF] Gilbert | A bioenergetic framework for the temperature dependence of trophic interactions[END_REF][START_REF] Amarasekare | E ects of temperature on consumer-resource interactions[END_REF][START_REF] Synodinos | eory of temperaturedependent consumer-resource interactions[END_REF]. A deeper empirical understanding of the e ects of temperature on species and biotic interactions, and a better integration into new predictive models, is crucial to develop better understanding, ecological forecasting and conservation planning of future natural ecosystems.

The challenge of warming affecting multiple biological rates simultaneously

When looking at community-and ecosystem-level impacts of climate change, a fundamental challenge arises: ere are multiple biological rates that are temperature dependent, and we must establish how di erent sensitivities a ect the outcome of warming on populations. For instance, in some organisms, metabolic rates has been found to be more sensitive to temperature than ingestion rates (e.g., [START_REF] Rall | Temperature, predator-prey interaction strength and population stability[END_REF][START_REF] Vucic-Pestic | Warming up the system: higher predator feeding rates but lower energetic e ciencies[END_REF]. e thermal mismatches between these two parameters can lead to starvation, and further extinctions can be expected if high temperatures are kept for long periods. However, this knowledge alone is insu cient to understand higher order responses. We must also include species interactions. erefore, to understand the e ects of warming at higher levels of biological complexity, rst it is vital to explore how temperature a ects the individuals through their physiology-thereby in uencing populations and interactions-to be able to link individual responses to higher levels of biological organisation. In this way we may succeed in identifying general patterns that better explain the responses of individuals, populations and species. By considering thermal dependencies of important traits in organisms, we can address whether there are general patterns in the way species respond to climate change within and across ecosystems. is requires to identify characteristics of organisms that determine their sensitivity to climate change, which will allow us to identify possible di erences in thermal sensitivities between interacting species. We can translate from the thermal dependencies of energy gain and loss by calculating the ratio between energy gain and loss across temperatures. is ratio yields the energetic balance that describes the thermal regions where we expect an initial increase with temperature (around the thermal region of temperature i), then a slowdown until it reaches an optimum (Tm). A er the optimum, the organism decreases its energetic balance (temperature ii) where thermal mismatches would materialise for the organism (intra-STM), until it reaches a critical threshold temperature (Tc), where energy gain cannot keep up with the metabolic demands (temperature iii). Above this temperature, further extinctions will be expected if warming persists.

At the population and species levels, the temperature-dependence of physiological parameters related to the acquisition and expenditure of energy are vital to understand the energetic balance for each population. Previous studies have shown that di erences in thermal sensitivities of some biological process such as ingestion and metabolic rates can exist in consumers [START_REF] Rall | Temperature, predator-prey interaction strength and population stability[END_REF][START_REF] Vucic-Pestic | Warming up the system: higher predator feeding rates but lower energetic e ciencies[END_REF][START_REF] Lemoine | Temperature-induced mismatches between consumption and metabolism reduce consumer tness[END_REF][START_REF] Alcaraz | Life in a warming ocean: ermal thresholds and metabolic balance of arctic zooplankton[END_REF][START_REF] Iles | Toward predicting community-level e ects of climate: Relative temperature scaling of metabolic and ingestion rates[END_REF]) leading to mismatches between these parameters for the organism at higher Blue-shaded areas correspond to a positive energetic balance where energy gain increases faster with temperature than energy loss. Orange-shaded areas correspond to a decreasing (intra-TM) but still positive energetic balance with increasing temperatures. Red-shaded areas correspond to a negative energetic balance, i.e., where energy loss exceeds energy gain. At low temperatures (i), for both species, the energetic balance of the organism increases with increasing temperature and gain exceeds loss. At intermediate temperatures (ii), energy gain exceeds loss for both species, but the ratio declines for the consumer, leading to a decline in the energy balance and the emergence of intraspeci c thermal mismatches (Intra-TM). At high temperatures (iii), energy loss for the consumer exceeds energy gain and the ratio falls below one, so the organism cannot ful l its energetic demands. e resource also su ers from energetic de cits, but the G/L ratio still remains over one. ermal mismatches between interacting species (Inter-TM) arise at temperatures at which one of the two interacting species starts to su er from energetic de cits while the other does not. We distinguish two distinct thermal regions within the Inter-TM: (1) where energetic balances di er between interacting species, and (2) where the energetic balances of both species decline with increasing temperature.

temperatures. Based on the change of energy gain and loss with increasing temperatures, an intraspeci c energetic mismatch describes a negative e ect on species energetic balances (i.e., the ratio between energy gain and energy loss) due to warming (Fig. I.2b,.

is mismatch between energy gain (e.g., ingestion, attack rate) and energy loss (e.g., metabolism) entails energetic restrictions, reducing the energetic budget for the organism's maintenance, growth and reproduction by decreasing energetic e ciencies [START_REF] Vucic-Pestic | Warming up the system: higher predator feeding rates but lower energetic e ciencies[END_REF]. erefore, when environmental temperature exceeds a certain temperature (T m ), the organism would rst decrease its energetic balance until it reaches a critical threshold temperature (T c ), where the starvation risk for the organism increases, because energy gain cannot keep up with the metabolic demands. Above this temperature, further extinctions will be expected if warming persists. In other words, energetic constraints happen because of temperature-dependence of energy gain (blue solid line Fig. I.2a) is not as strong as the temperature-dependence of the energy loss, or because thermal optimum of energy gain peaked before that of the energy loss (red solid line Fig. I.2a). In this case, knowing how the energy gain-to-loss ratio (Fig. I.2b) of a population responds to temperature provides information on the energetic availability and survival.

In situations in which two species interact, for instance in consumer-resource interactions, thermal responses of energetic balances of each interacting species can respond in di erent ways. For example, if energy gain exceeds energy loss for a resource species in a given temperature, this can translate into higher resource density available for consumers (see Figs I.2 and I.3 at temperature i). en, if this translates into an increase in consumer ingestion, i.e., higher energy gains for the consumer, then the interaction strength should not change. On the contrary, if temperature translates into higher resource density but the consumer su ers from energetic de cits, because energy gain cannot keep up with the higher metabolic demands (see Figs I.2 at temperature iii,), then this mismatch situation between interacting species (Figs I.3 Inter-TM) will likely lead to changes on the interaction strength. Many scenarios between the two described before are possible and all require further empirical investigation to better understand the mechanisms behind the e ects of temperature on trophic interactions.

General approaches to predict the effects of temperature on multiple biological rates and levels of organization

In this section I present some attempts to mechanistically understand and predict the e ects of temperature on multiple biological rates and across levels of biological organization. Metabolic scaling theories have mainly focused on how species' metabolism responds to changes in temperature, since metabolism dictates the pace of life in all organisms [START_REF] Brown | Toward a metabolic theory of ecology[END_REF]. Metabolism itself, is dictated not only by temperature, but also by both the body size and stoichiometry of organisms. us, temperature, together with organisms' body size are good predictors of biological and physiological rates [START_REF] Peters | Ecological implications of body size[END_REF][START_REF] Gillooly | E ects of Size and Temperature on Metabolic Rate[END_REF][START_REF] Brown | Toward a metabolic theory of ecology[END_REF][START_REF] Clarke | Is there a Universal Temperature Dependence of metabolism?[END_REF]). In addition, the concentration of resources needed to fuel the organism (stoichiometry) is also an important factor in the metabolic equation where metabolic process can be expressed as a function of body mass, temperature and stoichiometry [START_REF] Marquet | Metabolic Ecology: Linking Individuals to Ecosystems[END_REF].

Two main ecological theories have put their e orts in understanding the temperaturedependence of organisms' metabolism, the Metabolic eory of Ecology (MTE) and the hypothesis of 'Oxygen and Capacity-Limited ermal Tolerance' (OCLTT). e MTE states that metabolism dictates the pace of life in every single organism [START_REF] Brown | Toward a metabolic theory of ecology[END_REF]. is biological process is the rate at which organisms transform and allocate energy and materials to survival, growth and reproduction [START_REF] Gillooly | E ects of Size and Temperature on Metabolic Rate[END_REF][START_REF] Savage | E ects of body size and temperature on population growth[END_REF]. According to the MTE, the combined e ect of body mass and temperature on metabolic rate (or any metabolic process, I) can be expressed as:

(1) where i 0 is the normalization constant independent of body size and temperature, M is body mass, Ea is the activation energy, K is Boltzmann's constant and T is absolute temperature in Kelvin [START_REF] Gillooly | E ects of Size and Temperature on Metabolic Rate[END_REF]. Reaction kinetics and any other biochemical reaction, as well as metabolic rates described by MTE, increase exponentially with temperature ( gure I.4) according to the Boltzmann's factor: e -Ea/kT [START_REF] Gillooly | E ects of Size and Temperature on Metabolic Rate[END_REF][START_REF] Brown | Toward a metabolic theory of ecology[END_REF]. In general, temperature-dependence of biological rates, including metabolism, generally assumes an average activation energy value of 0.65 eV. However, this approximate value has been found to vary widely across biological rates, i.e., respiration, velocity, consumption and feeding [START_REF] Clarke | Is there a Universal Temperature Dependence of metabolism?[END_REF][START_REF] White | Allometric exponents do not support a universal metabolic allometry[END_REF][START_REF] Huey | Variation in universal temperature dependence of biological rates[END_REF], between terrestrial and aquatic environments [START_REF] Dell | Systematic variation in the temperature dependence of physiological and ecological traits[END_REF][START_REF] Pad Eld | Rapid evolution of metabolic traits explains thermal adaptation in phytoplankton[END_REF]) and between trophic groups (Lopez-Urrutia 2008; [START_REF] Dell | Systematic variation in the temperature dependence of physiological and ecological traits[END_REF][START_REF] Dell | Temperature dependence of trophic interactions are driven by asymmetry of species responses and foraging strategy[END_REF]considering that their processes are regulated by di erent biological mechanisms: about 0.65 eV for heterotrophs and 0.32 eV for autotrophs. is last disparity arises from the di erences in the biological mechanisms that regulate heterotrophic and autotrophic processes: ATP synthesis and Rubisco carboxylation respectively [START_REF] Allen | e mechanistic basis of the metabolic theory of ecology[END_REF]. erefore, the assumed values of 0.6 -0.7 eV used by theoreticians to parametrise temperature-scaling models [START_REF] Gillooly | E ects of Size and Temperature on Metabolic Rate[END_REF][START_REF] Brown | Toward a metabolic theory of ecology[END_REF] do not always match with empirical data [START_REF] Vasseur | A Mechanistic Approach for Modeling Temperature-Dependent Consumer-Resource Dynamics[END_REF] and requires further analysis and understanding.

On the other hand, the OCLTT relates metabolic performance to temperature and the supply of oxygen to the tissues. is mechanistic hypothesis has been used mainly to predict e ects of warming on ectotherms with cardiovascular and respiratory systems such as sh, reptiles, amphibians, insects and crustaceans [START_REF] Pörtner | Trade-O s in ermal Adaptation: e Need for a Molecular to Ecological Integration[END_REF][START_REF] Verberk | Anaerobic metabolism at thermal extremes: A metabolomic test of the oxygen limitation hypothesis in an aquatic insect[END_REF][START_REF] Verberk | ermal limits in native and alien freshwater peracarid Crustacea: e role of habitat use and oxygen limitation[END_REF][START_REF] Telemeco | Physiology at near-critical temperatures, but not critical limits, varies between two lizard species that partition the thermal environment[END_REF][START_REF] Ganglo | High temperature, oxygen, and performance: Insights from reptiles and amphibians[END_REF]. Although both OCLTT and MTE emphasise metabolism, there is a lively debate in the literature regarding the relevance of the OCLTT in predicting responses of species to warming. What is clear, however, is that whereas the MTE can 'scale-up' predictions for many biological responses to temperature from individuals to populations and communities, the OCLTT hypothesis lacks the connection between responses of populations and species to higher levels of biological organisation.

Thermal performance curves add realism for wider temperature ranges

Empirical evidence has challenged some predictions from MTE. In particular, multiple studies on the thermal biology of di erent taxa show that metabolic rates of organisms systematically show a unimodal trend with temperature [START_REF] Alcaraz | Life in a warming ocean: ermal thresholds and metabolic balance of arctic zooplankton[END_REF][START_REF] Schulte | e e ects of temperature on aerobic metabolism: towards a mechanistic understanding of the responses of ectotherms to a changing environment[END_REF][START_REF] Pad Eld | Rapid evolution of metabolic traits explains thermal adaptation in phytoplankton[END_REF][START_REF] Schaum | Temperature-driven selection on metabolic traits increases the strength of an algalgrazer interaction in naturally warmed streams[END_REF][START_REF] Booth | Diel oxygen uctuation drives the thermal response and metabolic performance of coastal marine ectotherms[END_REF]. us, empirical measurements of di erent rates, including metabolism, are frequently characterised with ermal Performance Curves (TPCs) to assess how biochemical, physiological or behavioral parameters change with temperature [START_REF] Schulte | ermal performance curves, phenotypic plasticity, and the time scales of temperature exposure[END_REF][START_REF] Dowd | ermal variation, thermal extremes and the physiological performance of individuals[END_REF]. TPCs provide a suitable framework to evaluate the thermal tolerance of ectotherms and allow estimations on how fundamental physiological functions are in uenced by environmental temperatures [START_REF] Angilletta | Estimating and comparing thermal performance curves[END_REF]). e modi ed Sharpe-School eld model [START_REF] School Eld | Non-linear regression of biological temperature-dependent rate models based on absolute reaction-rate theory[END_REF]) is used to characterise the shape of this curve (equation 2) and extra parameters of interest can be empirically tested and obtained from it:

(2)

For TPCs, the biological rate of interest (e.g., metabolism) scales exponentially with temperature from the critical minimum (CT min ) (below which the physiological process cannot proceed) to the optimal temperature (T opt in Fig. I.4) where performance is maximized. e slope of this section represents the activation energy (Ea): the minimum quantity of energy the organism must possess in order to undergo a speci c reaction. Past the optimum (T opt ) performance declines sharply down to the critical maximum (above which performance is zero) (CT max in Fig. I.4). Activation energy of TPCs is very similar to the activation energy described by the MTE at temperatures below the T opt (see Fig. I.4). However, a er this temperature, metabolic rates either decelerate until the optimum and follow a rapid decline (as described by thermal biology in TPCs), or continue increasing exponentially following the Boltzmann's factor (acc. to the MTE). e slope of the rate at which metabolic rate declines is de ned as deactivation energy (E h ).

Even though MTE is very e ective to make predictions of warming on di erent biological rates at di erent biological levels, this theory still has some limitations, especially for temperatures close to the thermal optimum and above it [START_REF] Schulte | e e ects of temperature on aerobic metabolism: towards a mechanistic understanding of the responses of ectotherms to a changing environment[END_REF]. Given that climate warming will expose the organisms to higher unprecedented temperatures in the near future [START_REF] Masson-Delmotte | Climate Change 2021: e Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change[END_REF], it is vital to understand how species will respond near their thermal upper limits, and formulate better theoretical predictions for di erent levels of biological organisation at these hotter boundaries. e accuracy of the predictions for how warming will a ect populations, communities and ecosystems are vital for generating more realistic expectations of the e ects of increasing temperatures.

Recently, a new study claims for a new integrative theory in which the metabolic rate is not the central parameter, highlighting the importance of growth and reproduction in understanding the e ects of anthropogenic global change on species [START_REF] White | Metabolic scaling is the product of life-history optimization[END_REF]. is new theory also considers the role of evolution in metabolic, growth and reproduction that is indeed a new way to explore the e ects of temperature across levels of biological organization. is work o ers a [START_REF] Dowd | ermal variation, thermal extremes and the physiological performance of individuals[END_REF][START_REF] Sinclair | Can we predict ectotherm responses to climate change using thermal performance curves and body temperatures?[END_REF])) where CT min is the minimum critical temperature, CT max is maximum critical temperature and T opt is the optimal temperature, Ea is the activation energy and Eh is the deactivation energy. Green dashed line shows the assumed exponential increase of metabolic rates with temperature described by the MTE. mathematically explicit explanation for biological allometries at multiple scales of organization.

ey predict that anthropogenic climate change will cause species to evolve decreased scaling exponents of metabolism, increased growth rates, and reduced lifetime reproductive outputs that will bring further and complex consequences for populations in the future.

Understanding and predicting the effects of temperature on consumer-resource dynamics

Exploring how temperature a ects trophic interactions can provide important insights about the e ects of climate warming on communities and ecosystems.

e theory of trophic interactions has been based on simpli ed consumer-resource models, which rely on population-level ecological processes for parameterization. e latter means that such models have proved useful to investigate the temperature-dependence of trophic interactions [START_REF] Synodinos | eory of temperaturedependent consumer-resource interactions[END_REF]. A representative model -due its common use -is the Rosenzweig-MacArthur model [START_REF] Rosenzweig | Graphical Representation and Stability Conditions of Predator-Prey Interactions[END_REF], which determines the rate of change in consumer (equation 1) and resource (equation 2) densities over time:

[1] [2]
where C and R are the consumer and resource species biomass densities, respectively, at time t; e represents the consumer assimilation e ciency and f represents the functional response between consumption rate and resource densities. e functional response can be linear, as in the classic Lotka-Volterra model; however, an increasing saturating shape has been found to be prevalent in nature. ese saturating responses are known as Holling Type II and Type III; the di erence being that the former increases exponentially prior to saturating, while the latter is sigmoidal (e.g., [START_REF] Sarnelle | Type III Functional Response in Daphnia[END_REF][START_REF] Archer | Consistent temperature dependence of functional response parameters and their use in predicting population abundance[END_REF][START_REF] Daugaard | Warming can destabilize predator-prey interactions by shi ing the functional response from Type III to Type II[END_REF]. When assuming a linear functional response in a Lotka-Volterra model, f can be represented by the interaction strength (i.e., f = a rc ). e parameter m represents the consumer metabolic costs which can be considered as a biomass loss term or individual mortalities, depending on the selected units. r is the intrinsic growth rate of the resource population and K is the resource density at carrying capacity. ough this model accounts for a single trophic interaction, it reveals fundamental aspects of the dynamics as the changes of biomass densities of both trophic levels over time [START_REF] Yodzis | Body size and consumer-resource dynamics[END_REF][START_REF] Vasseur | A Mechanistic Approach for Modeling Temperature-Dependent Consumer-Resource Dynamics[END_REF][START_REF] Synodinos | eory of temperaturedependent consumer-resource interactions[END_REF]. ese insights can then form the foundation for understanding more complex models incorporating multiple species and/or multiple trophic levels, which emulate real food webs more closely [START_REF] Binzer | Interactive e ects of warming, eutrophication and size structure: Impacts on biodiversity and food-web structure[END_REF][START_REF] Barbier | Pyramids and cascades: a synthesis of food chain functioning and stability[END_REF][START_REF] Bideault | ermal mismatches in biological rates determine trophic control and biomass distribution under warming[END_REF].

Temperature dependencies of each particular parameter of consumer-resource models have been derived in some cases from empirical analyses and in others just derived from theory. In general, as described before, metabolic rates have been reported to either increase exponentially, as MTE predicts [START_REF] Goss | Temperature e ects on zooplankton respiration[END_REF][START_REF] Brown | Toward a metabolic theory of ecology[END_REF][START_REF] Rall | Temperature, predator-prey interaction strength and population stability[END_REF][START_REF] Schulte | ermal performance curves, phenotypic plasticity, and the time scales of temperature exposure[END_REF][START_REF] Vucic-Pestic | Warming up the system: higher predator feeding rates but lower energetic e ciencies[END_REF][START_REF] Lemoine | Temperature-induced mismatches between consumption and metabolism reduce consumer tness[END_REF][START_REF] Iles | Toward predicting community-level e ects of climate: Relative temperature scaling of metabolic and ingestion rates[END_REF] or to follow a unimodal response, as most empirical evidence suggests [START_REF] Alcaraz | Life in a warming ocean: ermal thresholds and metabolic balance of arctic zooplankton[END_REF][START_REF] Schulte | e e ects of temperature on aerobic metabolism: towards a mechanistic understanding of the responses of ectotherms to a changing environment[END_REF][START_REF] Pad Eld | Rapid evolution of metabolic traits explains thermal adaptation in phytoplankton[END_REF][START_REF] Schaum | Temperature-driven selection on metabolic traits increases the strength of an algalgrazer interaction in naturally warmed streams[END_REF][START_REF] Booth | Diel oxygen uctuation drives the thermal response and metabolic performance of coastal marine ectotherms[END_REF]. However, most theoretical work focuses on a shortened temperature range, which does not include the peak and subsequent decrease in metabolic rate. Hence, it is generally parameterised as an exponentially increasing function of temperature (e.g., [START_REF] Brown | Toward a metabolic theory of ecology[END_REF][START_REF] Savage | E ects of body size and temperature on population growth[END_REF]. Assimilation e ciency, e, has generally been assumed to be temperature independent [START_REF] Vasseur | A Mechanistic Approach for Modeling Temperature-Dependent Consumer-Resource Dynamics[END_REF][START_REF] Binzer | e dynamics of food chains under climate change and nutrient enrichment[END_REF][START_REF] Binzer | Interactive e ects of warming, eutrophication and size structure: Impacts on biodiversity and food-web structure[END_REF][START_REF] Fussmann | Ecological stability in response to warming[END_REF], but a recent study suggests decreased transfer e ciency in warmed communities [START_REF] Barneche | Warming impairs trophic transfer e ciency in a long-term eld experiment[END_REF]. is is justi able given that empirical studies have found mixed support for temperature e ects on assimilation e ciencies (e.g., [START_REF] Mason | Food , Feeding Rates and Assimilation in Woodland Snails[END_REF][START_REF] Heiman | e In uence of Temperature on the Bioenergetics of the Carnivorous Stone y Nymph, Acroneuria californica Banks (Plecoptera: Perlidae)[END_REF][START_REF] Richardson | Food, feeding rates and assimilation in the land snail Cepaea nemoralis L[END_REF]) which tend to be relatively weak [START_REF] Lang | Temperature and consumer type dependencies of energy ows in natural communities[END_REF]. ough evidence for the thermal dependence of the functional response has been mixed, there is overwhelming support for a unimodal shape [START_REF] Englund | Temperature dependence of the functional response[END_REF][START_REF] Uiterwaal | Arena size modulates functional responses via behavioral mechanisms[END_REF]). e thermal dependence of resource growth rates, r, have been measured in several studies, yielding either an exponentially increasing or a unimodal pattern [START_REF] Savage | E ects of body size and temperature on population growth[END_REF][START_REF] Nejrup | Temperature-and light-dependent growth and metabolism of the invasive red algae Gracilaria vermiculophylla -a comparison with two native macroalgae[END_REF][START_REF] Grimaud | Modeling the temperature e ect on the speci c growth rate of phytoplankton: a review[END_REF][START_REF] Kremer | Temperature-and size-scaling of phytoplankton population growth rates: Reconciling the Eppley curve and the metabolic theory of ecology[END_REF]). However, few empirical studies have reported on the thermal dependence of carrying capacity, K. ese have found a negative trend (exponentially decreasing) with warming [START_REF] Fussmann | Ecological stability in response to warming[END_REF][START_REF] Bernhardt | Metabolic theory and the temperaturesize rule explain the temperature dependence of population carrying capacity[END_REF], which can be interpreted as a consequence of increasing metabolic rate with warming: given a xed amount of nutrients, population density at higher temperatures becomes limited by higher per capita metabolic costs. Meanwhile, theoretical work has proposed all possible thermal dependence shapes for K, each corresponding to a di erent mechanism. For instance, K has been assumed to monotonically decrease, invoking increasing metabolic rates with warming (Rall et al. 2010b;[START_REF] O'connor | eoretical Predictions for How Temperature A ects the Dynamics of Interacting Herbivores and Plants[END_REF][START_REF] Binzer | e dynamics of food chains under climate change and nutrient enrichment[END_REF][START_REF] Dell | Temperature dependence of trophic interactions are driven by asymmetry of species responses and foraging strategy[END_REF][START_REF] Fussmann | Ecological stability in response to warming[END_REF][START_REF] Sentis | Temperature-size responses alter food chain persistence across environmental gradients[END_REF]). e hump-shaped response has been linked to optimal growth conditions with respect to light [START_REF] Uszko | E ects of warming on predatorprey interactions -a resource-based approach and a theoretical synthesis[END_REF], while a U-shaped thermal dependence would re ect the peak in intra-speci c competition around temperatures optimal for growth [START_REF] Amarasekare | E ects of temperature on consumer-resource interactions[END_REF] and references within). Finally, K has sometimes been represented also as temperature invariant (i.e., constant) due to the lack of clarity associated to the thermal dependence of stoichiometry, which should partially determine the carrying capacity [START_REF] Uszko | E ects of warming on predatorprey interactions -a resource-based approach and a theoretical synthesis[END_REF][START_REF] Synodinos | eory of temperaturedependent consumer-resource interactions[END_REF] .

us it becomes clear that there is an urgent need for more empirical evidence on the thermal dependence of certain parameters, since the structure and dynamics of trophic communities strongly depend on them [START_REF] Johnson | A metric for quantifying the oscillatory tendency of consumer-resource interactions[END_REF][START_REF] Synodinos | eory of temperaturedependent consumer-resource interactions[END_REF].

The importance of evolutionary responses of species and interactions to climate warming

Two aspects of climate change are key to understanding how species will respond. First, species will face novel, extremely high temperatures during heat waves (i.e., acute warming events) which are expected to intensify in frequency and severity in coming years [START_REF] Brown | Future changes in heatwave severity, duration and frequency due to climate change for the most populous cities[END_REF][START_REF] Perkins-Kirkpatrick | Increasing trends in regional heatwaves[END_REF]. At the same time, the increase in mean temperature is expected to be a gradual process that will span multiple generations. In some cases, organisms can respond to increasing temperatures through multiple mechanisms (e.g., changes to phenology, behaviour or phenotype) [START_REF] Parmesan | Ecological and Evolutionary Responses to Recent Climate Change[END_REF][START_REF] Angilletta | ermal Adaptation[END_REF][START_REF] Tüzün | Evolution of geographic variation in thermal performance curves in the face of climate change and implications for biotic interactions[END_REF][START_REF] Kontopoulos | Adaptive evolution explains the present-day distribution of the thermal sensitivity of population growth rate Author summary[END_REF][START_REF] Radchuk | Adaptive responses of animals to climate change are most likely insu cient[END_REF]. Evolution is likely to be of vital importance to reduce the risk of extinctions because warming provides opportunities for populations and communities to adapt to the new environmental conditions [START_REF] Bush | Incorporating evolutionary adaptation in species distribution modelling reduces projected vulnerability to climate change[END_REF]. Nevertheless, evolutionary adaptations of populations (e.g., heritable changes in physiology, morphology, behaviour) to warming remain understudied and, therefore, our ability to predict future outcomes limited.

ere remain many unknowns about the role of evolution in populations, communities, and ecosystems. Previous studies have shown that thermal sensitivities of species can evolve in an adaptive, and sometimes rapid, manner [START_REF] Mclean | If you can't stand the heat, stay out of the city: ermal reaction norms of chitinolytic fungi in an urban heat island[END_REF][START_REF] Knies | Hotter is better and broader: ermal sensitivity of tness in a population of bacteriophages[END_REF]omas et al. 2012;[START_REF] Schaum | Adaptation of phytoplankton to a decade of experimental warming linked to increased photosynthesis[END_REF][START_REF] Kontopoulos | Adaptive evolution shapes the present-day distribution of the thermal sensitivity of population growth rate[END_REF]. erefore, responses to warming may depend not only on ecological responses of individuals or even the responses associated with species interactions, but also on their ability to adapt and evolve to new conditions [START_REF] Shurin | Warming shi s topdown and bottom-up control of pond food web structure and function[END_REF][START_REF] Velthuis | Warming advances top-down control and reduces producer biomass in a freshwater plankton community[END_REF].

Empirical evidence for thermal evolution in both resources and consumers has been mounting over the past decade across taxa (e.g., [START_REF] Campillo | Selection on life-history traits and genetic population divergence in rotifers[END_REF][START_REF] Campillo | Local adaptation in rotifer populations[END_REF][START_REF] Sentis | ermal acclimation modulates the impacts of temperature and enrichment on trophic interaction strengths and population dynamics[END_REF][START_REF] Schaum | Temperature-driven selection on metabolic traits increases the strength of an algalgrazer interaction in naturally warmed streams[END_REF][START_REF] Tseng | Species interactions mediate thermal evolution[END_REF]. For instance, thermal evolution in Chlamydomonas reinhardtii has been linked to an increase of photosynthesis, having a direct impact on ecosystem functioning [START_REF] Schaum | Adaptation of phytoplankton to a decade of experimental warming linked to increased photosynthesis[END_REF]. Here, isolates of this algal species that were exposed to long-term experimental warming for several years increased their tness with respect to non-evolved isolates. Background thermal histories of the same species were shown to be important for growth to uctuating temperatures [START_REF] Kremer | Gradual plasticity alters population dynamics in variable environments: thermal acclimation in the green alga Chlamydomonas reinhartdii[END_REF]. In general, in autotrophs, thermal evolution confers higher maximum growth and thermal optima for the warm-adapted populations conditions [START_REF] Schlüter | Adaptation of a globally important coccolithophore to ocean warming and acidi cation[END_REF][START_REF] Listmann | Swi thermal reaction norm evolution in a key marine phytoplankton species[END_REF][START_REF] Liang | Molecular mechanisms of temperature acclimation and adaptation in marine diatoms[END_REF]. ese improvements, however, brought associated impacts (trade-o s) on traits related to ecosystem functioning such as photosynthetic e ciency, growth rates and irradiance stress [START_REF] Jin | Fast adaptation of tropical diatoms to increased warming with tradeo s[END_REF]. Nonetheless, thermal evolution can also potentially modify ecosystem functioning. For example, populations of Chlorella vulgaris evolved to temperatures that initially limited its growth by rapid evolution of increased carbon-use e ciency, suggesting that warm adapted algae could evolve increased carbon xation [START_REF] Pad Eld | Rapid evolution of metabolic traits explains thermal adaptation in phytoplankton[END_REF]. Evolutionary responses to Chapter 1 explores the thermal dependency of interaction strength, f, based on energetic imbalances of interacting species. Chapter 2 focuses on the evolutionary responses to temperature of interaction strength based on individual species traits related to energy gain and loss. Chapter 3 examines the temperature dependencies and evolutionary responses of resource population traits, such as growth rate, r, and carrying capacity, K. And nally, Chapter 4 focuses on consumer's traits, investigating mortality/survival (i.e., parameter m) to temperature across two temporal scales, as well as other important demographic traits using two thermal contrasting populations of consumers.

warming has also been observed in the water ea Daphnia. Researchers compared populations from recent times, which have experienced increased heatwaves in recent decades, with a 'naïve' historic population from the 1960s grown from dormant eggs bank at the same location [START_REF] Geerts | Rapid evolution of thermal tolerance in the water ea Daphnia[END_REF]. Here, the critical thermal maximum, which speci cally measures tolerance to extreme temperatures and are hence related to heatwaves, was signi cantly higher in recent clones than those from the 1960's.

ermal evolution has also the potential to strongly modify and even reverse the outcome of the interactions between consumers and resources under warming [START_REF] Tseng | Species interactions mediate thermal evolution[END_REF]. From the few examples available, thermal evolution of consumers has been reported to strengthen the consumer-resource interaction [START_REF] Schaum | Temperature-driven selection on metabolic traits increases the strength of an algalgrazer interaction in naturally warmed streams[END_REF][START_REF] Wang | ermal evolution ameliorates the longterm plastic e ects of warming, temperature uctuations and heat waves on predator-prey interaction strength[END_REF]) compared to unevolved populations. However, to date, few studies have looked simultaneously at patterns of thermal evolution of both consumers and resources in shaping their interactions [START_REF] Barton | Local adaptation to temperature conserves top-down control in a grassland food web[END_REF][START_REF] De Block | Local genetic adaptation generates latitude-speci c e ects of warming on predator-prey interactions[END_REF][START_REF] Tseng | Species interactions mediate thermal evolution[END_REF][START_REF] Wang | ermal plasticity and evolution shape predator-prey interactions di erently in clear and turbid water bodies[END_REF]. erefore, there is an urgent need to explore thermal evolutionary responses of interacting species to generate better predictions of climate warming on interspeci c interactions, and in consequence, on communities and ecosystems.

Even though evolution has implications at the ecosystem level, laboratory experiments should be treated with caution because the rates of thermal adaptation may signi cantly di er in complex natural communities where species interact with many others. erefore, in order to translate the e ects of temperature on populations and species interactions -together with their evolutionary responses -to a wider context it will be necessary to apply an appropriate scaling process across levels of biological organisation, from individual and pair-wise responses to whole ecosystems [START_REF] Woodward | Climate change and freshwater ecosystems: impacts across multiple levels of organization[END_REF][START_REF] Ghedini | Metabolic scaling across succession: Do individual rates predict community-level energy use?[END_REF][START_REF] Bozinovic | ermal e ects vary predictably across levels of organization: empirical results and theoretical basis[END_REF].

Summary of the chapters

e general objective of this PhD thesis is to understand the ecological and evolutionary e ects of temperature on both resource and consumer species and their interactions. is will allow for improved prediction of temperature changes to community dynamics to help us to better forecast the consequences of di erent climatic warming scenarios. To do so, this thesis is organised in 4 chapters, each addressing thermal dependencies, and evolutionary responses, of di erent constituent parameters of consumer-resource models (Fig. I.5). In chapter 1, I explore the thermal dependencies of the parameter `f` referred to as the e ect of the consumer on the resource by measuring the e ect of temperature on the interaction strength and the balance between energy gain and loss of two consumer-resource pairs. In chapter 2, I aim to understand evolutionary responses of `f`, measured again as interaction strength, in conjunction with the energetic balances for populations of consumers and resources that have experienced long-term (i.e., 13 years) exposure to experimental warming. In chapter 3, I examine ecological and evolutionary responses of resource growth rate, r, nutrient acquisition, and its carrying capacity, K, across a temperature gradient using contrasting populations of two resource species that di er in their thermal background history. In chapter 4, I investigate thermal dependencies of mortality in consumers, measured as survival rates across two temporal scales, in acute and life-long exposures to temperature. In addition, in this chapter I evaluate whether changes in demographic traits (e.g., fecundity) exhibited a compensatory relationship that explained di erences observed in survival between unevolved and evolved populations of the consumer across temperatures. Chapter 1 and 2 focused on resources, consumers, and their interaction, and Chapter 3 and 4 on resources and consumers respectively. While the rst chapter only considers ecological responses to warming, the remaining chapters consider both ecological and evolutionary responses to changing temperatures. Here, I use an empirical approach employing di erent populations of species collected and isolated from two semi-natural freshwater communities that di ered in their long-term thermal histories. Following, I brie y summarize each chapter describing their motivation, objective and questions posed and the main ndings and conclusions. A better mechanistic understanding of temperature-dependencies and evolutionary responses of constituent parameters of consumer-resource models will help us to improve predictions of global warming for trophic interactions and natural communities.

Chapter 1: ermal mismatches explain consumer-resource dynamics in response to environmental warming

• Motivation: Changing temperatures will impact food webs in ways we are yet to fully understand. Such understanding is hindered by the complexity of the problem, as di erent physiological and ecological processes show di erent sensitivities to changing temperatures. One path to improving our understanding and generating good predictions is to acquire a mechanistic understanding of the e ects of temperature change on consumer-resource dynamics. Such e ects can be assessed by the impacts of consumers on resources, measured as interaction strength, relying on how resources and consumers acquire and lose energy.

• Objectives and questions: e rst chapter of the thesis aims to analyse whether thermal responses of energetic balances (i.e., the ratio between energy gain and loss) of both consumer and resource species help to predict the outcome of their interaction in the context of climatic warming. Speci cally, I use a more integrative approach by simultaneously considering the fundamental energetic balances of both interacting species to investigate (1) whether warming cause mismatches between the thermal response of energy gains and losses for consumer and resource species individually;

(2) whether warming induces mismatched responses between interacting species;

(3) whether the mismatched response between interacting species can provide a mechanistic understanding of the thermal dependence of interaction strength.

• Main results and conclusions: I found that increases of temperature initially increased the energetic balance for both resource species, while for the consumer energy availability declined with warming, due to the stronger thermal sensitivity of respiration compared to ingestion. en at the interaction level, interaction strength decreased with temperature when the resources' energetic balance increased while that of the consumer declined (i.e., mismatch at the interaction). However, when the energetic balances of both interacting species declined with temperature, interaction strength increased. is study provides a new mechanistic approach integrating both resource and consumer performance independently to understand and predict the e ects of temperature on consumer-resource interactions. is, combined with the focus on energetic balances, provides additional depth to the interpretation of how consumerresource interactions depend on temperature.

Chapter 2: Evolutionary responses of species traits to temperature determine consumerresource dynamics under warming

• Motivation: there is a gap in knowledge in predicting the e ects of climatic warming, because much of the current empirical and theoretical research does not account for evolutionary thermal adaptation of species. Yet, multiple studies have reported cases where populations of either one or both interacting species showed signs of evolutionary changes to temperature. Moreover, species interactions have documented dependency on temperature, which implies a complex situation for predicting the e ects of environmental warming on species populations' dynamics and thus, on communities and ecosystems.

• Objectives and questions: the second chapter of this thesis is devoted to understanding ecological and evolutionary responses of consumer-resource interactions to temperature change. e overall aim of this chapter is to understand how thermal evolution of individual energetic traits in consumer and resource populations can help to better predict the e ects of temperature on species interactions in the long-term. Speci cally, I use two contrasting thermal populations of resource and consumer species to investigate (1) whether the physiological traits and energetic balances, investigated in Chapter 1, of resources and consumers, evolved under a long-term exposure to warming;

(2) whether the evolutionary thermal responses of each individual species can be used to better predict the impact of temperature on the interaction when species populations are allowed to evolve to temperature.

• Main results and conclusions: I nd that energetic traits of one resource species and the consumer showed signs of thermal evolutionary adaptation. ermal evolution of both interacting species maintained the thermal response of interaction strength, which represents a cryptic response where evolution preserves the outcome of the ecological response, making it appear that no evolution has occurred. On the other hand, when only one of the interacting species evolved, the temperature-dependency of interaction strength changed dramatically. Here, thermal evolution of the consumer enhanced the e ect of the consumer on the resource across temperatures. A closer examination of the warming-induced evolutionary responses to underlying physiological traits in both interacting species provides additional information yielding insight to better predict the impacts of climatic warming on consumer-resource interactions. e novelty of this chapter is the simultaneous exploration of evolutionary responses in two trophic levels, and also on their interactions.

Chapter 3: Ecological and evolutionary responses of primary producers to increasing temperatures

• Motivation: very little is known about how temperature a ects two key resource parameters (i.e., growth rate, r, and carrying capacity, K). ese two parameters are important in determining a population's own temporal dynamics, as well as in uencing trophic interactions. Exploring the trends, and possible evolutionary responses, of key resource traits with temperature can help to extend the knowledge we have on the e ects of climatic warming on resource dynamics and species interactions.

• Objectives and questions: in this chapter I investigate empirically (1) the thermal dependency of resource growth rates (r) and carrying capacity (K), and (2) I explore evolutionary responses of these two traits to long-term exposure to experimental warming. In addition, I examine the thermal dependency, and evolutionary responses of nutrient acquisition of the same resource species as a way to extend the mechanistic understanding of carbon and nutrient transformation into biomass under warming.

• Main results and conclusions: I found general patterns for both species and thermal populations in growth rates (unimodal), carrying capacity (linear decline) and nitrate acquisition (either unimodal or saturating increasing) with increasing temperatures. Moreover, resource parameters also showed thermal evolution a er long-term exposure to warming, resulting in larger growth rates and maximum densities at carrying capacity, as well as higher rates of nitrate acquisition. ese results help to extend the empirical knowledge we have on the e ects of temperature on consumer-resource interactions, and better predict the impact of warming on populations' dynamics.

Chapter 4: e impact of acute and life-long exposures to temperature on survival and other demographic traits of consumers

• Motivation: Demographic traits such as survival and fecundity govern the tness of all individuals, and thus ultimately control population traits. Di erences in the thermal dependencies of demographic traits that underlie population dynamics-as well as their evolution-can strongly modify the responses of consumer and resource dynamics under warming. When populations are able to evolve to new thermal conditions, di erent traits can trade o with each other, or even compensate others, to determine tness. Additionally, trade-o s can also emerge across time scales, when considering how populations respond to acute and life-time exposure to temperature.

• Objectives and questions: in this chapter I investigate empirically (1) the e ects of temperature on di erent demographic traits for two populations of a consumer species that di er in their multi-generational thermal histories, and ( 2) the e ects of temperature on consumers' survival rates at two contrasting temporal scales (i.e., acute or life-long exposures to temperature) for these same two populations.

• Main results and conclusions: e results on survival rates of both thermal-origin populations of D. pulex suggested that thermal evolution of increased survival rates in acute thermal conditions traded-o with survival under life-long exposure to temperature. Although I found general thermal dependencies for demographic traits, such as intrinsic growth rate (exponential increase), net reproductive rates (unimodal) and generation times (linear decline), these did not di er between thermal populations. In consequence, I found no evidence of compensatory e ects by increased fecundity in the warm-evolved population that could o set the observed di erences in survival rates over acute and chronic exposure to temperature between populations.

Study system

roughout my PhD, I used microcosms experiments with freshwater consumer and resource species. Laboratory manipulations in microcosms simulate and predict the behaviour of natural systems under controlled conditions, and can provide advantages over macrocosms and eld observation studies for some questions in ecology and evolution [START_REF] Drake | Microcosms as Models for Generating and Testing Community eory[END_REF][START_REF] Fussmann | Ecological and Evolutionary Dynamics of Experimental Plankton Communities[END_REF][START_REF] Altermatt | Big answers from small worlds: A user's guide for protist microcosms as a model system in ecology and evolution[END_REF]. For instance, the simpli cation of environmental stressors with a number of individual or interacting species makes them ideal systems to disentangle ecological and evolutionary mechanisms that would otherwise be very complicated to observe in natural systems. In my laboratory experiments I used two freshwater algae species, Chlamydomonas reinhardtii and Desmodesmus sp. (Figures I.6 e unicellular green alga C. reinhardtii is a classical reference and model organism for studying a myriad of questions such as genetics, physiology and even behavior. It is an excellent laboratory species because it is easy to culture and grows easily in di erent media. is species has also been reported to be an important source of food for multiple herbivore planktonic species. Desmodesmus sp. is also a green alga, which has been frequently reported for a high phenotypic plasticity, showing variability in cells forming cell-groups from either single cells up to 4 or 8 cells [START_REF] Lürling | Phenotypic plasticity in the green algae Desmodesmus and Scenedesmus with special reference to the induction of defensive morphology[END_REF]. is species is also an important food source for herbivorous zooplankters. Finally, D. Pulex is an important component of the planktonic fraction in freshwater food webs. It interacts with lower levels by grazing, is a strong competitor to other cladocerans, rotifers and protists, and constitutes an important prey species for other invertebrate (e.g. dragon ies, phantom midge) and vertebrate (e.g. sh) species. In consequence, daphnids are pivotal to energy transfer through aquatic food webs, so if temperature compromises its survival, this will amplify up and down the food web, causing disruptions across multiple trophic levels. Additionally, daphnids [START_REF] Lampert | Daphnia: Development of a Model Organism in Ecology and Evolution[END_REF][START_REF] Geerts | Rapid evolution of thermal tolerance in the water ea Daphnia[END_REF][START_REF] Yousey | Resurrected 'ancient' Daphnia genotypes show reduced thermal stress tolerance compared to modern descendants[END_REF], as well as the two resource species selected [START_REF] Schaum | Adaptation of phytoplankton to a decade of experimental warming linked to increased photosynthesis[END_REF][START_REF] Tseng | Species interactions mediate thermal evolution[END_REF] have previously shown adaptive responses to environmental changes. In consequence, this makes the study of evolutionary responses to changing temperatures possible.

For all three experimental species, I isolated in 2019 two contrasting thermal populations from a long-term mesocosm platform at the Freshwater Biological Association River Laboratory, Dorset, UK. Mesocosms consisted of plastic tanks of approximately 1m 3 volume and 50 cm depth that mimicked small shallow freshwater systems [START_REF] Yvon-Durocher | Warming alters the size spectrum and shi s the distribution of biomass in freshwater ecosystems[END_REF]. ere, since 2005, half of the tanks-initially 10 but in 2019 only 8-are kept at a temperature 4 °C above the other half, 8 tanks, that naturally uctuate with ambient temperatures. is set-up allows for variation at diurnal and seasonal scales for both thermal treatments with only the experimentally imposed di erence of 4 °C between treatments. is system of predator and prey species allowed me to evaluate both ecological and evolutionary responses to warming.

Abstract

A mechanistic understanding of the e ects of temperature on species and their interactions will improve predictions of the consequences of warming on ecosystems. Predictions are complex, as di erent ecological processes show di erent sensitivities to changing temperatures. Here we provide a new mechanistic approach centred on the temperature dependency of the balance of energy gain to energy loss for consumer and resource species simultaneously. We found that increases of temperature provided more energy available for the resource species. In consumers, temperature dependency of respiration was stronger than ingestion resulting in general declines in energy availability with warming. We then used consumer-resource energetic balances to predict interaction strengths. We found that interaction strength decreased with temperature when the resource's energetic balance increased while that of the consumer declined with warming. However, it increased when energetic balances of both interacting species declined with temperature while the consumer's ingestion remained una ected.

Introduction

Climate change is expected to increase mean surface temperatures between 1.5 and 5°C relative to 1850-1900 mean temperature over the next 80 years (IPCC 2021). is presents an important challenge across levels of biological organisation as temperature regulates important ecological processes. Temperature a ects growth, reproduction, development and survival rates at the population level [START_REF] Dell | Systematic variation in the temperature dependence of physiological and ecological traits[END_REF][START_REF] Frances | E ects of environmental warming during early life history on libellulid odonates[END_REF][START_REF] Adamczuk | Population dynamics and life history traits of Daphnia magna across thermal regimes of environments[END_REF], alters community size structure by bene ting smaller taxa [START_REF] Daufresne | Global warming bene ts the small in aquatic ecosystems[END_REF][START_REF] Yvon-Durocher | Warming alters the size spectrum and shi s the distribution of biomass in freshwater ecosystems[END_REF] and impacts several functions such as decomposition, productivity and respiration at the ecosystem level (Yvon-Durocher et al. 2010a). Yet, we are far from being able to generate precise predictions on the e ects of environmental warming on species and communities [START_REF] Synodinos | eory of temperaturedependent consumer-resource interactions[END_REF].

How organisms respond to environmental warming represents a complex question, because temperature a ects multiple biological rates simultaneously. Moreover, these rates can respond di erently to temperature. To aggregate this information, one can measure how temperature alters an organism's energy gain and loss. In general, energy loss (e.g., respiration rate, metabolism, exudation, excretion) increases with temperature following either an exponential [START_REF] Goss | Temperature e ects on zooplankton respiration[END_REF][START_REF] Brown | Toward a metabolic theory of ecology[END_REF][START_REF] Rall | Temperature, predator-prey interaction strength and population stability[END_REF][START_REF] Schulte | ermal performance curves, phenotypic plasticity, and the time scales of temperature exposure[END_REF][START_REF] Vucic-Pestic | Warming up the system: higher predator feeding rates but lower energetic e ciencies[END_REF][START_REF] Lemoine | Temperature-induced mismatches between consumption and metabolism reduce consumer tness[END_REF][START_REF] Iles | Toward predicting community-level e ects of climate: Relative temperature scaling of metabolic and ingestion rates[END_REF] or unimodal trend [START_REF] Alcaraz | Life in a warming ocean: ermal thresholds and metabolic balance of arctic zooplankton[END_REF][START_REF] Schulte | e e ects of temperature on aerobic metabolism: towards a mechanistic understanding of the responses of ectotherms to a changing environment[END_REF][START_REF] Pad Eld | Rapid evolution of metabolic traits explains thermal adaptation in phytoplankton[END_REF][START_REF] Schaum | Temperature-driven selection on metabolic traits increases the strength of an algalgrazer interaction in naturally warmed streams[END_REF][START_REF] Booth | Diel oxygen uctuation drives the thermal response and metabolic performance of coastal marine ectotherms[END_REF]. Energy gain (e.g., nutrient acquisition, ingestion rate, attack rate) can similarly increase exponentially [START_REF] Rall | Temperature, predator-prey interaction strength and population stability[END_REF][START_REF] Vucic-Pestic | Warming up the system: higher predator feeding rates but lower energetic e ciencies[END_REF][START_REF] Fussmann | Ecological stability in response to warming[END_REF][START_REF] Binzer | Interactive e ects of warming, eutrophication and size structure: Impacts on biodiversity and food-web structure[END_REF][START_REF] Archer | Consistent temperature dependence of functional response parameters and their use in predicting population abundance[END_REF] or follow a unimodal trend [START_REF] Englund | Temperature dependence of the functional response[END_REF][START_REF] Lemoine | Temperature-induced mismatches between consumption and metabolism reduce consumer tness[END_REF][START_REF] Sentis | Using functional response modeling to investigate the e ect of temperature on predator feeding rate and energetic e ciency[END_REF][START_REF] Alcaraz | Life in a warming ocean: ermal thresholds and metabolic balance of arctic zooplankton[END_REF] (L, in red) parameters. e slope of the rate is the activation energy (E a ), the temperature at which the rate peaks is the optimum temperature (T opt ), the slope of the rate a er the peak is the deactivation energy (E h ), the maximal value of rate performance occurs at MRP, and the temperature of energy gain rate in ection (T m i , of consumer, c, or resource, r) is the maximum value of the gain-to-loss ratio. b) and d) represent the G/L ratio calculated from thermal dependencies of energy gain and loss depicted in a) and c). Blue-shaded areas correspond to a positive energetic balance where energy gain increases faster with temperature than energy loss. Orange-shaded areas correspond to a decreasing but still positive energetic balance with increasing temperatures. Red-shaded areas correspond to a negative energetic balance, i.e., where energy loss exceeds energy gain. Vertical dashed lines depict the temperature at which the G/L ratio is maximized (T m ) and the crossover temperature (T c ) where energy gain equals energy loss (ratio = 1). At low temperatures (i), for both species, the energetic balance of the organism increases with increasing temperature and gain exceeds loss. At intermediate temperatures (ii), energy gain exceeds loss for both species, but the ratio declines for the consumer, leading to a decline in the energy balance and the emergence of intraspeci c thermal mismatches (Intra-TM). At high temperatures (iii), energy loss for the consumer exceeds energy gain and the ratio falls below one, so the organism cannot ful l its energetic demands. e resource also su ers from energetic de cits, but the G/L ratio still remains over one. Interspeci c thermal mismatches (Inter-TM) arise at temperatures at which one of the two interacting species starts to su er from energetic de cits while the other does not. We distinguish two distinct thermal regions within the Inter-TM: (1) where energetic balances di er between interacting species, and (2) where the energetic balances of both species decline with increasing temperature. et al. 2014;[START_REF] West | Impacts of warming revealed by linking resource growth rates with consumer functional responses[END_REF][START_REF] Uszko | E ects of warming on predatorprey interactions -a resource-based approach and a theoretical synthesis[END_REF][START_REF] Betini | Temperature triggers a non-linear response in resource-consumer interaction strength[END_REF], however, energy gain can also be invariant across temperature [START_REF] Vucic-Pestic | Warming up the system: higher predator feeding rates but lower energetic e ciencies[END_REF][START_REF] Rall | Universal temperature and body-mass scaling of feeding rates[END_REF][START_REF] Iles | Toward predicting community-level e ects of climate: Relative temperature scaling of metabolic and ingestion rates[END_REF]). e ratio between energy gain and loss (i.e., G/L ratio in Figs. 1.1b and 1.1d) potentially explains how species' energetic balance changes across temperatures, which ultimately a ects individual tness and population dynamics [START_REF] Rall | Temperature, predator-prey interaction strength and population stability[END_REF][START_REF] Vucic-Pestic | Warming up the system: higher predator feeding rates but lower energetic e ciencies[END_REF][START_REF] Gilbert | A bioenergetic framework for the temperature dependence of trophic interactions[END_REF].

Based on the change of energy gain and loss with increasing temperature we de ne intraspeci c thermal mismatches to describe a negative e ect on species energetic balances due to warming (i.e., intra-TMs in Fig. 1.1). A rst possibility occurs when the G/L ratio decreases, implying a reduction in the energetic budget. e second possibility describes a case where energy losses exceed gains, i.e., when the G/L ratio is less than one. us, intraspeci c thermal mismatches trigger energetic restrictions, which can impair the organism's maintenance, growth, and reproduction at higher temperatures. e characterization of intraspeci c thermal mismatches can be the rst step towards predicting responses to warming of interacting species.

While intraspeci c thermal mismatches are well-characterized for consumers [START_REF] Rall | Temperature, predator-prey interaction strength and population stability[END_REF][START_REF] Vucic-Pestic | Warming up the system: higher predator feeding rates but lower energetic e ciencies[END_REF][START_REF] Lemoine | Temperature-induced mismatches between consumption and metabolism reduce consumer tness[END_REF][START_REF] Alcaraz | Life in a warming ocean: ermal thresholds and metabolic balance of arctic zooplankton[END_REF][START_REF] Iles | Toward predicting community-level e ects of climate: Relative temperature scaling of metabolic and ingestion rates[END_REF], they remain relatively understudied for resource species [START_REF] Pad Eld | Rapid evolution of metabolic traits explains thermal adaptation in phytoplankton[END_REF][START_REF] Barton | Evolutionary temperature compensation of carbon xation in marine phytoplankton[END_REF]. Moreover, research on energetic balances of consumer-resource pairs remains scarce [START_REF] Mertens | Escaping herbivory: ocean warming as a refuge for primary producers where consumer metabolism and consumption cannot pursue[END_REF]. erefore, it is unclear whether intraspeci c thermal mismatches of interacting species show similar trends with warming. If consumers and resources produced similar intraspeci c patterns independently, then one could infer that the energetic balance within their interaction remains unchanged with increasing temperatures. If, however, the energetic balances -and intraspeci c thermal mismatches -of interacting consumer and resource species di er as temperature increases, interspeci c thermal mismatches materialise (Inter-TMs in Fig. 1.1). us, the characterisation of the thermal dependencies of interacting species' energetic balances can reveal potential interspeci c thermal mismatches. ese will provide information on how temperature change impacts the structure (e.g., biomass distribution) and dynamics of food webs through changes in energetic uxes and interaction strength [START_REF] Rip | Cross-ecosystem di erences in stability and the principle of energy ux[END_REF][START_REF] Gilbert | A bioenergetic framework for the temperature dependence of trophic interactions[END_REF] Interaction strength is an important metric describing consumer-resource dynamics, and ultimately the stability of the system, as it quanti es the impact of the consumer on the resource's density [START_REF] Wootton | Measurement of interaction strength in nature[END_REF][START_REF] Berlow | Simple prediction of interaction strengths in complex food webs[END_REF]. When interaction strength increases with temperature [START_REF] O'connor | Warming strengthens an herbivore-plant interaction[END_REF][START_REF] Rall | Universal temperature and body-mass scaling of feeding rates[END_REF][START_REF] Sampaio | Interaction strength between di erent grazers and macroalgae mediated by ocean acidi cation over warming gradients[END_REF][START_REF] Schaum | Temperature-driven selection on metabolic traits increases the strength of an algalgrazer interaction in naturally warmed streams[END_REF][START_REF] Bideault | Temperature Modi es Consumer-Resource Interaction Strength rough Its E ects on Biological Rates and Body Mass[END_REF] species abundances and community dynamics can be modi ed [START_REF] Hoekman | Turning up the heat: Temperature in uences the relative importance of top-down and bottom-up e ects[END_REF][START_REF] Shurin | Warming shi s topdown and bottom-up control of pond food web structure and function[END_REF][START_REF] Velthuis | Warming advances top-down control and reduces producer biomass in a freshwater plankton community[END_REF], potentially destabilising the system and leading to extinctions at higher temperatures [START_REF] Yvon-Durocher | Five Years of Experimental Warming Increases the Biodiversity and Productivity of Phytoplankton[END_REF]. Warming has also been found to reduce interaction strength, thus, increasing stability of populations [START_REF] Vasseur | A Mechanistic Approach for Modeling Temperature-Dependent Consumer-Resource Dynamics[END_REF][START_REF] Binzer | e dynamics of food chains under climate change and nutrient enrichment[END_REF][START_REF] Rall | Universal temperature and body-mass scaling of feeding rates[END_REF].

Previous studies have primarily focused on the consumer perspective, determining how interaction strength changes with temperature through alterations in functional response parameters rather than examining fundamental energetic balances and their mismatches across the consumer-resource pair [START_REF] Sentis | Using functional response modeling to investigate the e ect of temperature on predator feeding rate and energetic e ciency[END_REF][START_REF] Sentis | ermal acclimation modulates the impacts of temperature and enrichment on trophic interaction strengths and population dynamics[END_REF][START_REF] Uszko | When is a type III functional response stabilizing? eory and practice of predicting plankton dynamics under enrichment[END_REF][START_REF] Uszko | E ects of warming on predatorprey interactions -a resource-based approach and a theoretical synthesis[END_REF].Taken altogether, however, interspeci c thermal mismatches may provide a previously underutilized means through which to predict the behaviour of interaction strength with changing temperature. Here, we aim to answer three questions. First, does environmental warming cause intraspeci c thermal mismatches in consumers and resources as a result of di erences in thermal dependencies of energy gain and loss? Second, in consumer-resource interactions does environmental warming induce interspeci c thermal mismatches? And third, can interspeci c thermal mismatches provide a mechanistic understanding of the thermal dependence of interaction strength?

Materials and methods

Study system and experimental design

We focused on one consumer, Daphnia pulex, and two algal resource species, Chlamydomonas reinhardtii and Desmodesmus sp., isolated from shallow freshwater open-air experimental ponds in Dorset, UK, between January and October 2019. ese taxa are cosmopolitan and keystone freshwater species. A er isolation we maintained the organisms in semi-continuous batch cultures in freshwater medium in incubators until experiments (see Suppl. Methods S1.1).

We measured thermal dependencies of physiological rates related to energy gain (i.e., ingestion, net photosynthesis) and loss (i.e., respiration) for the algae species and for Daphnia feeding on each resource separately in basal conditions at eight temperatures. For the algae, temperatures were 14, 18, 22, 26, 30, 34, 38, 42 C, while temperatures were 14, 18, 22, 26, 30, 32, 34, 36 C for Daphnia. Disparity in tested temperatures was linked to di erences in thermal traits of the species found in previous pilot experiments (i.e., consumers exposed to 38 and 42 C died during acclimation, thus we added 32 and 36 C, the maximal temperature at which individuals could survive the acclimation process). Prior starvation yielded basal conditions of the organisms at culturing conditions (see Suppl. Methods S1.2). For all experiments, a temporally blocked design (n = 3 in each block, n = 6 across two blocks) ensured that replicates were tested at each temperature in two separate incubators to prevent pseudoreplication at the level of the incubator. For respiration and net photosynthesis, controls contained 0.2 µm ltered medium. For ingestion, controls instead contained each algal species without consumers. To avoid thermal shock, each replicate (including controls) was given one hour of ramp-up acclimation in water baths following starvation to the assay temperature prior to experiments. Oxygen depletion for 30 minutes in dark conditions measured respiration. Oxygen production for 30 minutes in constant light conditions (PAR intensity of 67 -70 µmol m -2 s -1 ) measured net photosynthesis immediately following measurement of respiration in algal tests. For respiration and net photosynthesis, replicates were 5 ml samples with no air bubbles in glass vials (SensorVial SV-PSt5-4mL, PreSens®) mounted on a Sensor Dish reader (PreSens®). Before tracking oxygen measurements (in mg O 2 L -1 ), we gave the samples 1 hour at assay temperatures in the incubators for stabilisation of the oxygen device. For respiration and photosynthesis, consumer replicates contained ve starved adult daphnids in ltered media, and algal replicates consisted of 5 ml starved algal cultures adjusted to set densities (see Suppl. Methods S1.2 and Fig. S1.2) using a modi ed nutrient-free medium for dilution. Consumer and resource respiration rates were measured separately. For ingestion, we placed ve starved adult daphnids in 5 ml of highly dense algal suspension from our clonal batch cultures (either C. reinhardtii or Desmodesmus sp. taken at the exponential phase). Consumer ingestion was then measured as algal density removed from the media over 150 minutes in dark conditions to prevent any phototactic reaction of the daphnids, which could impact the consistency of ingestion measurements [START_REF] Serra | Optimal light conditions for Daphnia ltration[END_REF] as well as respiration rates. Initial algal densities did not statistically di er between control and consumer treatments within temporal blocks (all Post-Hoc pairwise tests, p > 0.05, Suppl. Methods S1.4). We used ow cytometry (BD FACSCanto II high throughput sampler) to measure nal algal densities of preserved algal samples from the algae respiration and net photosynthesis experiments, as well as at the beginning and at the end of Daphnia ingestion experiments (see Suppl. Methods S1.3).

For physiological rates exhibiting unimodal responses to temperature (i.e., respiration and net photosynthesis), we tted the data to a Sharpe-School eld model [START_REF] School Eld | Non-linear regression of biological temperature-dependent rate models based on absolute reaction-rate theory[END_REF] described in Equation 1 which characterises the shape of a ermal Performance Curve (TPC), computing predictions to 0.001 C precision in the R 4.0.3 statistical environment (see Suppl. Methods S1.4): [1] where rate(T) is the rate at a temperature T ( C), k is the Boltzmann constant with a value of 8.62e-05, E a is the activation energy (in electron volts, eV), i.e., the slope below the optimum, E h is the de-activation energy (eV) at high temperature, i.e. the slope beyond the optimum, t h is the temperature at which enzymes are half suppressed due to high temperatures, r tref is the rate at a standardised temperature, and T ref is a standardisation temperature ( C) [START_REF] Barneche | Warming impairs trophic transfer e ciency in a long-term eld experiment[END_REF]. ese parameters are obtained from the non-linear model (with a signi cance level of 0.05). TPCs also provide other complementary thermal performance parameters (i.e., the optimum temperature, T opt , and maximal rate at optimum temperature, MTP, Fig. 1.1). We evaluated the t of unimodal rates for the 25 curves described by Pad eld et al. ( 2021).

e selected model-the Sharpe-School eld model (Eq. 1)-best t the majority of the rates and it o ered the additional advantage of providing estimates of previously described TPC parameters. Bootstrapping using the case resampling method yielded con dence intervals for the TPC parameters (see Suppl. Methods S1.4). Linear responses of ingestion rates with temperature were assessed with general linear models (GLM) a er verifying that both data and model residuals complied with parametric assumptions. For ingestion rates, we independently tted the data to linear regression models for each resource species, and computed predicted ingestion to 0.001 C precision. Ingestion rates of D. pulex feeding on Desmodesmus sp. showed no signi cant temperature dependence, hence to calculate predicted values of ingestion we tted ingestion data to a linear regression with the slope constrained to a value of zero. Subsequently, we calculated species energetic balances as net photosynthesis-to-respiration ratio for resources, or as ingestion-to-respiration ratio () for consumers, using predicted values of each per capita rate from either the TPC or GLM models. From individual energetic balances we identi ed the intraspeci c thermal mismatches (intra-TM) for each species starting at those temperatures at which the balance declined with increasing temperature. We inferred interspeci c thermal mismatches (inter-TM) by comparing individual energetic balances for both consumer-resource pairs, and identi ed the thermal mismatch regions (Fig. 1.1), where: 1) trends of energetic balances contrast between the interacting species; and 2) both species reduce their energetic balance with increasing temperature. en, based on interspeci c thermal mismatches (i.e., di erences between respiration and ingestion/photosynthesis for both interaction species) we elaborated expected outcomes of thermal dependencies of interaction strength. Finally, we experimentally measured thermal dependencies of interaction strength for each consumer-resource pair and veri ed if our predictions using the thermal mismatches matched the trends of interaction strengths calculated across temperatures.

Computing energy loss and gain in resources

Algal per capita respiration rates (R r , mg O 2 l -1 min -1 cell -1 ) were calculated using Equation 2:

[2]
where for each replicate, m t is the slope of the linear regression between oxygen saturation and time, m c is the mean slope of the controls from the same temporal block, and d is algae density. We multiplied the oxygen di erence between algae and control replicates by -1 so that R r describes the algal per capita oxygen consumption. Although algal batch cultures were non-axenic, bacteria densities were negligible and therefore bacterial respiration was not taken into account in our resource respiration rate measurements. Per capita rates of net photosynthesis (P, mg O 2 l -1 min -1 cell -1 ) were calculated using Equation 2, but without multiplying the oxygen di erence between algae and control replicates by -1.

Computing energy loss and gain in the consumer

Per capita rate of consumer respiration (R c , mg O 2 l -1 min -1 Daphnia -1 ) was calculated using Equation 2 but using m t as the slope of oxygen depletion for replicates containing daphnids, and d as the number of daphnids alive at the beginning of the experiment in Daphnia replicates instead. e value of d was generally 5, but in exceptional cases individuals died during the acclimation process. We converted consumer per capita respiration rates (R c , mg O 2 l -1 min -1 Daphnia -1 ) into energetic equivalents of metabolism (R C E , Joules l -1 h -1 Daphnia -1 ) by assuming that 1mg O 2 equals 14.06 J [START_REF] Peters | Ecological implications of body size[END_REF]) (see Suppl. Methods S1.5). Per capita rates of raw ingestion (rI, cells ml -1 h -1 Daphnia -1 ) were calculated using Equation 3:

[3]
where D T0 and D T150 are resource densities in Daphnia treatment replicates at the beginning and the end of the experiment, C 0 and C 150 are the mean value of resource densities at the beginning and the end of the experiment across control replicates (without consumers) from each temporal block (n=3 x 2 temporal blocks), y is the number of consumers in the Daphnia treatment replicates alive at the beginning of the experiment, and t is the length of the experiment (150 minutes). Resource densities were at high concentrations (~ 4.5 x 10 5 cells ml -1 for C. reinhardtii and ~ 1.3 x 10 6 cells ml -1 Desmodesmus sp. based on pilot experiments) to achieve saturating values of the functional response. Similar to consumer respiration rates, per capita raw ingestion rates (rI, cells ml -1 h -1 Daphnia -1 ) were transformed into energy equivalents (rI E , Joules l -1 h -1 Daphnia -1 ) to make them quantitatively comparable (see Suppl. methods S1.5). To account for imperfect assimilation, we then calculated nal per capita ingestion rates, I E Joules l -1 h -1 Daphnia -1 , by multiplying per capita raw ingestion rates in energy units, rI E , by a unitless assimilation e ciency for each algal species. Assimilation e ciencies were assumed to be constant across temperatures set at 14% when D. pulex fed on C. reinhardtii and 10% when it instead fed on Desmodesmus sp. (see Suppl. Methods S1.5). Adult experimental daphnids averaged 2.08 ± 0.1 mm in length (mean ± SD).

Consumer-resource Interaction Strength

From the ingestion experiments, using algal densities at the end of the tests (i.e., T 150 ), we next estimated per capita interaction strength (IS) for each consumer-resource pair as the log-response ratio, also called the Dynamic Index [START_REF] Berlow | Quantifying variation in the strengths of species interactions[END_REF], but using the more intuitive inverse form [as in [START_REF] Schaum | Temperature-driven selection on metabolic traits increases the strength of an algalgrazer interaction in naturally warmed streams[END_REF]]: [4] where N is the algal densities without consumers present (mean value of three control replicates per temporal block), D is the algal densities with consumers present (Daphnia treatment replicates), y is the number of consumers in each Daphnia treatment replicate and t is the experiment length. e Dynamic Index does not depend on equilibrium conditions, and therefore works well for short-term experiments [START_REF] Laska | eoretical concepts and empirical approaches to measuring interaction strength[END_REF][START_REF] Berlow | Interaction strength in food webs : issues and opportunities[END_REF]). Here the index measures the absolute value of per capita interaction strength by time, accounting for algal growth with and without consumers (O'Connor 2009). A large value of IS indicates a strong per capita impact of the consumer on the resource density. Conversely, low values of IS indicate a weak impact of one consumer on resource densities. We tted values of interaction strength to general linear models (GLM) by conducting a full linear regression including the interaction between temperature and algal species and performed a two-way analysis of variance (ANOVA) to get slopes and summary statistics (see Suppl. Methods S1.4).

Results

Intraspecific thermal mismatches in resources

ermal performance of energy gain (i.e., photosynthesis) and loss (i.e., respiration) di ered within and across resources (Tables 1.1,S1 .1,S1.2,Figs. 1.2,1.3). Photosynthesis was more sensitive to temperature increase than respiration for both resource species, with almost a 4-fold increase for C. reinhardtii for temperatures below the optimum of the G/L ratio (T m ). For both resources, optimum temperatures were higher for respiration than for net photosynthesis (T opt R > T opt P , see Table 1.1). Although respiration temperature optima were very similar between algae species, optimum of net photosynthesis was about 4 degrees higher for C. reinhardtii. ese di erential temperature sensitivities and optima for energy gain and loss led to important intraspeci c thermal mismatches, with marked di erences between species (Figs. 1.2b,1.3b).

us, although both resources exhibited unimodal trends of energetic balances, intraspeci c thermal mismatches were more pronounced for Desmodesmus sp. than for C. reinhardtii as they arose at lower temperatures. While the crossover temperature, T c (i.e., G/L ratio = 1) was not identi ed for Desmodesmus sp. within the temperature range tested here, this value occurred at relatively high temperature for C. reinhardtii, near the optimum of respiration.

Intraspecific thermal mismatches in the consumer

e consumer showed marked di erences between thermal sensitivities of energy gain (i.e., ingestion) and loss (i.e., respiration) (Tables 1.1,S1 .1,S1.3,Fig. 1.4). Consumer respiration was unimodal with temperature. However, thermal dependencies of ingestion showed linear and contrasting responses depending on what algal species served as a food source. While ingestion declined slowly with temperature when consumers fed on C. reinhardtii (β = -0.075, R 2 = 0.15, F 1, 44 = 7.573, p = 0.009), ingestion was temperature-independent when consumers fed on Desmodesmus sp. (β = 0.05, R 2 = 0.05, F 1, 45 = 2.655, p = 0.11). Consumer respiration (R c ) was more sensitive to increases of temperature than Daphnia ingestion (I) feeding on either resource species. ese thermal di erences led to declines in the energetic balances for the consumer, and yielded intraspeci c thermal mismatches, for the whole temperature range tested (Figs. 1.4b,1.4d). e consumer's crossover temperatures (Tc) di ered slightly between resource species, with a higher value when it fed on Desmodesmus sp.

Interspecific thermal mismatches

Based on the observed intraspeci c thermal mismatches at the individual level (Figs. 1.2, 1.4, S1.2), we expected interspeci c thermal mismatches for both consumer-resource pairs to emerge at low temperatures, 14 C. However, di erences in thermal regions '1' and '2' of the interspeci c thermal mismatch (Fig. 1.1) between both interacting pairs points to a di erence in the nature of the thermal mismatch and the implications for the interaction. For the Daphnia -C. reinhardtii pair, interspeci c thermal mismatches arose at 14 C, Table 1.1. Estimated parameters of thermal performance curves of resources and consumer per capita rates that followed unimodal responses with temperature. Sharpe-School eld model parameters show mean estimated values of activation energy (E a ), deactivation energy (E h ), optimum temperature (T opt ), and maximum rate of performance (MRP) for resources' net photosynthesis (P) and respiration (R r ) rates, and consumer respiration (R c ) rates.

Species Rates E a (eV) T opt ( C) MRP ng O 2 l -1 min -1 cell -1 MRP pg O 2 min -1 cell -1 E h (eV) C. reinhardtii
-1 L -1 h -1 ** D. pulex respiration units' volume corrected are Joules Daphnia -1 h -1
as increases of temperature reduced the energy balance of the consumer (Fig. 1.4b) but increased that of the resource (Fig. 1.2a). us, the thermal region '1' is de ned between 14 and 30.7 C. Temperatures beyond this thermal region (>30.7 C) caused declines in energetic balances for both interacting species (i.e., thermal region '2' of inter-TM).

Alternatively, for the Daphnia -Desmodesmus sp. pair, interspeci c thermal mismatches also arose at 14 C. However, for this pair thermal region '1' of the inter-TM occurred between 14 -19 C, and therefore we observed that further increases of temperature generally decreased the energetic balance for both interacting species (>19 C, thermal region '2').

Thermal dependencies of interaction strengths

e e ect of temperature on interaction strength showed opposite trends for the two consumer-resource interactions (ANOVA test: F 1, 90 = 20.24, p <0.001) (Tables S1.4,S1 .5,Fig. 1.5). Temperature increased interaction strength when consumers fed on Desmodesmus sp. (β = 0.0004, p = 0.02), while interaction strength decreased with temperature when the consumer fed on C. reinhardtii (β = -0.0007, p <0.001). e di erences in thermal regions of interspeci c thermal mismatches between species pairs could explain the di erences in thermal dependencies of interaction strength. Consumers feeding on C. reinhardtii su ered from energetic de cits with increasing temperatures while the resource's energy balance increased for the majority of the thermal gradient (<30.7 C, thermal region '1').

is could reduce the intensity of the per capita e ect of the consumer on C. reinhardtii with rising temperatures (Tables S1.4,S1 .5,Fig. 1.4a). On the contrary, consumers feeding on Desmodesmus sp., su ered from energetic de cits but the thermal region '1' of the mismatch for this pair comprised a narrow thermal region (14 -19 C). For the majority of the thermal range (> 19 C), increases of temperature generally reduced energetic balances for both species. Nevertheless, the consumer maintained constant ingestion rates (Fig. 1.4c) which could translate into either a constant or enhanced intensity of the per capita e ect of the consumer on Desmodesmus sp. with rising temperatures. In addition, we observed that the consumer intraspeci c thermal mismatch was not as strong when feeding on Desmodesmus sp. (i.e., crossover temperature, Tc, was slightly larger for Desmodesmus sp.) than when it fed on C. reinhardtii instead (Figs. 1.4b,1.4d). us, we consider that the net e ect of the consumer on the resource increased with temperature which is re ected in the thermal dependence of interaction strength (Fig. 1.5).

Discussion

Trophic interactions, which can be strongly responsive to temperature change, constitute the building blocks of ecological communities. erefore, understanding how temperature a ects consumers, resources, and their interactions is necessary for predicting the impacts of climate change on ecosystems. We performed experiments to determine the thermal dependencies of energy gain and loss of two consumer-resource pairs. is allowed us to examine intra-and inter-speci c thermal mismatches -i.e., the negative e ects of warming on species energetic balances (Fig. 1.1) -which can compromise species' performance and survival. Finally, we used interspeci c thermal mismatches to predict how interaction strength will change with increasing temperatures. Our approach deviates from past attempts in considering interaction strength from both the resource and consumer perspectives, rather than o ering a consumer-centric interpretation. is, combined with the focus on energetic balances, o ers a new mechanistic understanding of the impacts of climatic warming on trophic interactions.

Intraspeci c thermal mismatches depend on two main factors that determine how the balance of energy gain and loss changes as temperature increases: the relative sensitivities to temperature increase (i.e., slopes) and the optimal temperatures. Compared to previously reported values, our estimated slopes for the resource species (i.e., activation energies Ea, Tables 1.1, S1.1-2) were higher for photosynthesis [START_REF] Lopez-Urrutia | Scaling the metabolic balance of the oceans[END_REF][START_REF] Pad Eld | Rapid evolution of metabolic traits explains thermal adaptation in phytoplankton[END_REF][START_REF] Barton | Evolutionary temperature compensation of carbon xation in marine phytoplankton[END_REF]) and lower for respiration [START_REF] Barton | Evolutionary temperature compensation of carbon xation in marine phytoplankton[END_REF]. Hence, we observed that energy gain (i.e., net photosynthesis) increased faster than energy loss (i.e., respiration) with warming. is contradicts the well-supported result that respiration has a greater thermal sensitivity than photosynthesis in autotrophs (Allen et al. 2005;[START_REF] Lopez-Urrutia | Scaling the metabolic balance of the oceans[END_REF][START_REF] Anderson-Teixeira | Di erential responses of production and respiration to temperature and moisture drive the carbon balance across a climatic gradient in New Mexico[END_REF][START_REF] Pad Eld | Rapid evolution of metabolic traits explains thermal adaptation in phytoplankton[END_REF]. ese contrasting outcomes can be explained by di erences in the metabolic state of the resource ( omas et al. 2017;[START_REF] Marañón | Nutrient limitation suppresses the temperature dependence of phytoplankton metabolic rates[END_REF]. While in our case resources were maintained in basal metabolic conditions following prolonged starvation, other studies used non-starved cells [START_REF] Pad Eld | Rapid evolution of metabolic traits explains thermal adaptation in phytoplankton[END_REF][START_REF] Barton | Evolutionary temperature compensation of carbon xation in marine phytoplankton[END_REF]. It is hard to conclude which approach -starvation or not-best ts to natural conditions, given the multitude of potential circumstances. Our experiment best mimics the e ects of temperature on autotrophs in cases where nutrients are consistently low (e.g., oligotrophy) or maintained at low levels for a certain period (e.g., autumn-winter). Although some respiration rates for Desmodesmus sp. showed negative values, we believe that they were likely caused by the small signal of this algal species compared to C. reinhardtii (relative to the instrument sensitivity) and the correction by control replicates.

For the consumer, our results of thermal sensitivities (Tables 1.1, S1.1-2) agree with previous observations: respiration was more sensitive to temperature than ingestion [START_REF] Rall | Temperature, predator-prey interaction strength and population stability[END_REF][START_REF] Vucic-Pestic | Warming up the system: higher predator feeding rates but lower energetic e ciencies[END_REF][START_REF] Archer | Consistent temperature dependence of functional response parameters and their use in predicting population abundance[END_REF], resulting in intraspeci c thermal mismatches. Although ingestion rates generally increase with temperature, we found no signi cant thermal dependence when Daphnia fed on Desmodesmus sp. (similar to [START_REF] Rall | Temperature, predator-prey interaction strength and population stability[END_REF][START_REF] Iles | Toward predicting community-level e ects of climate: Relative temperature scaling of metabolic and ingestion rates[END_REF][START_REF] Archer | Consistent temperature dependence of functional response parameters and their use in predicting population abundance[END_REF]) and a negative trend when it fed on C. reinhardtii. As energy acquisition for the consumer had a weak relationship with temperature, this translated into lower values of crossover temperatures (Tc; 20.7 C for C. reinhardtii, 22.5 C for Desmodesmus sp.) than expected for D. pulex [START_REF] Goss | Daphnia development and reproduction: responses to temperature[END_REF]. One explanation for the low Tc could be the di erence in the metabolic state of the consumers [START_REF] Brown | Toward a metabolic theory of ecology[END_REF]Clarke & Fraser 2004) and the length of the exposure to temperature. Exceeding these crossover temperatures under short-term exposures causes energy de cits and stress for the consumers, though this does not necessarily translate into mortality. Ways to bu er against this stress in the longer term could include a reduction in body size to lower metabolic demands [START_REF] Khan | E ect of temperature on water ea Daphnia magna (Crustacea:Cladocera)[END_REF][START_REF] Van Doorslaer | Experimental thermal microevolution in community-embedded Daphnia populations[END_REF]. However, if the organism cannot respond, extinctions would be expected. By conducting the D. pulex ingestion experiments in darkness, we were able to best mimic natural conditions. Daphnids generally react to predators with diel vertical migration. During the day they remain at lower depths, minimising predation. ey migrate up to the surface at night, exhibiting greater feeding activity under the cover of darkness [START_REF] Serra | Optimal light conditions for Daphnia ltration[END_REF]. Similar to the negative values seen in some cases for Daphnia respiration, we believe that negative values of ingestion were mostly likely linked to methodological causes (i.e., related to equipment sensitivity) (although trends were consistent across temperatures). For interaction strength, some negative values, such as we observed here, are not completely anomalous as they have also been reported previously in the literature [START_REF] O'connor | Warming strengthens an herbivore-plant interaction[END_REF][START_REF] Sampaio | Interaction strength between di erent grazers and macroalgae mediated by ocean acidi cation over warming gradients[END_REF][START_REF] Schaum | Temperature-driven selection on metabolic traits increases the strength of an algalgrazer interaction in naturally warmed streams[END_REF].

We argued that the comparison of intraspeci c thermal mismatches of resources and consumers determines consumer-resource interspeci c thermal mismatches, which in turn help to predict how interaction strength changes with temperature. Although interspeci c thermal mismatches for both consumer-resource pairs emerged at low temperatures, the nature and implications of the mismatch di ered. We de ned two regions within the interspeci c thermal mismatch with increasing temperature (Fig. 1.1); one where the consumer energetic balance decreases while the resource's does not (region 1), and a second when both consumer and resource su er a reduction in energetic balance (region 2). us, the large thermal range of region 1 of the interspeci c thermal mismatch between Daphnia and C. reinhardtii would indicate a decreasing interaction strength (Table S1 .4,Fig. 1.4a). In contrast, the second pair (Daphnia-Desmodesmus sp.) had a wide thermal region 2 of the mismatch (Fig. 1.4b). However, the consumer ingestion rate remained constant, while the resource energetic balance declined.

is could imply that the pressure (i.e., interaction strength) exerted upon the resource should increase with warming. e contrasting results for interaction strength between the two resource species suggest a strong context-dependency of the e ects of consumers on resource population densities across temperature gradients. Such context-dependency is not surprising [START_REF] Betini | Temperature triggers a non-linear response in resource-consumer interaction strength[END_REF][START_REF] Uiterwaal | Functional responses are maximized at intermediate temperatures[END_REF]. As has been argued, the di erence in thermal optima observed in the two resource species' energetic balances could explain this divergence between experiments [START_REF] Betini | Temperature triggers a non-linear response in resource-consumer interaction strength[END_REF]. Alternatively, di erences in traits of the algae, such as motility, could explain the di erence in our results. Recent studies have shown that the swimming speed of C. reinhardtii increases signi cantly with temperature [START_REF] Sekiguchi | ermotaxis in Chlamydomonas is brought about by membrane excitation and controlled by redox conditions[END_REF]. If increased swimming speed helps the alga to avoid consumption by the consumer, this could weaken the interaction strength with warming, a possibility with implications at the community level [START_REF] Svensson | Diatom cell size, Coloniality and motility: Trade-O s between temperature, Salinity and nutrient supply with climate change[END_REF]. On the other hand, our results for the Daphnia-Desmodesmus sp. pair interaction strength are in line with the expectations that temperature enhances top-down control as a result of increasing ingestion rates [START_REF] Hoekman | Turning up the heat: Temperature in uences the relative importance of top-down and bottom-up e ects[END_REF][START_REF] Shurin | Warming shi s topdown and bottom-up control of pond food web structure and function[END_REF][START_REF] Velthuis | Warming advances top-down control and reduces producer biomass in a freshwater plankton community[END_REF][START_REF] Kazanjian | Impacts of warming on top-down and bottom-up controls of periphyton production[END_REF].

Even though the interaction strength results may be context-dependent, our mechanistic interpretation based on energetic mismatches is not. Inter-speci c thermal mismatches consider both resource and consumer performance independently to predict the e ects of warming on the interaction of the two species. Typically, interaction strength quanti es the impact of the consumer on the resource, providing a consumer-centric perspective. Shortterm interaction strength has been determined by the ingestion rate alone [START_REF] Rall | Temperature, predator-prey interaction strength and population stability[END_REF], the functional response [START_REF] Cuthbert | e Functional Response Ratio (FRR): advancing comparative metrics for predicting the ecological impacts of invasive alien species[END_REF], or the relative change in resource abundance caused by the consumer [START_REF] Berlow | Interaction strength in food webs : issues and opportunities[END_REF][START_REF] Schaum | Temperature-driven selection on metabolic traits increases the strength of an algalgrazer interaction in naturally warmed streams[END_REF]. us, the role of the resources in determining interaction strength has been largely understudied.

Measuring the energetic balance of each species highlights the temperatures for which intraspeci c, and consequently interspeci c, thermal mismatches arise. e consumer energetic balance, as measured here, represents the consumer population growth given no resource limitation [START_REF] Yodzis | Body size and consumer-resource dynamics[END_REF][START_REF] Synodinos | eory of temperaturedependent consumer-resource interactions[END_REF]. Similarly, resource energetic balance can correlate to resource growth rate [START_REF] Barton | Evolutionary temperature compensation of carbon xation in marine phytoplankton[END_REF]. It has been argued that the di erence between resource growth rate and consumption rate can be a good indicator of interaction strength, particularly for short-term dynamics [START_REF] West | Impacts of warming revealed by linking resource growth rates with consumer functional responses[END_REF]. Our focus on energy balances rather than population growth provides additional depth to the interpretation of how the interaction depends on temperature.

ere are di erent ways interspeci c thermal mismatches can manifest, corresponding to di erent impacts for the interaction. When only consumers su er from an intraspeci c mismatch (i.e., region 1 of the mismatch), we observe an increase in consumer energetic demands relative to energy gains, which suggest a weakening impact on the resource. At the same time, increasing resource energetic reserves provide the means to mitigate any adverse e ects from predation. Hence, it is reasonable to deduce that interaction strength should decrease, as our results showed (C. reinhardtii result). In fact, a strong correlation between decreasing consumer energetic balance and interaction strength has appeared in previous experiments (see [START_REF] Synodinos | eory of temperaturedependent consumer-resource interactions[END_REF].

If both species su er from intraspeci c mismatches (i.e., interspeci c mismatch region 2), the interaction could be detrimental to the resource. To better understand this, it is important to consider what drives the consumer intraspeci c mismatch. Increasing or constant consumer ingestion rate while the resource energetic surplus decreases with warming should translate into increased interaction strength. On the other hand, decreased ingestion rates will necessitate that consumer metabolic demands be met through other means, such as reduced energy expenditure or decreased body size [START_REF] Khan | E ect of temperature on water ea Daphnia magna (Crustacea:Cladocera)[END_REF][START_REF] Van Doorslaer | Experimental thermal microevolution in community-embedded Daphnia populations[END_REF]. Despite a decrease in resource energy reserves, this should weaken the interaction strength.

Focusing solely on how consumer performance depends on temperature misses one half of the interacting pair. e notion of thermal mismatches, as presented here, includes the resource performance in the quanti cation of consumer-resource interactions. is additional layer of mechanistic interpretation can improve our understanding of how the interaction between consumers and resources can change with temperature. e approach presented here is conceptual, supported by an experiment of two interacting pairs. To make this approach widely applicable, a next step would quantify more precisely how thermal mismatches relate to interaction strength. We expect this will yield a strong mechanistic framework for understanding how energy uxes impact the dynamics of food webs under climate change.

Conclusions

e response of trophic interactions to increasing temperatures will be important in determining the dynamics and functioning of communities and ecosystems under climate change. We presented an approach to quantify the impact of warming on consumer-resource interactions, which is based on two pillars. On the one hand, we used energetic balances as an indicator of how species respond to increasing temperatures, de ning intraspeci c thermal mismatches when the energetic balance decreases. On the other hand, we considered both the resource and consumer energetic balances to determine the interaction, contrary to most approaches which are consumer-centric. By comparing the two species' (intraspeci c) thermal mismatches we deduced temperature regions of interspeci c thermal mismatches, where one or both species su er from decreasing energy reserves. We argue that interspeci c energy mismatches can provide a powerful mechanistic tool to understand and predict the impacts of warming on trophic interactions.

Chapter 2

Evolutionary responses of species traits to temperature determine consumer-resource dynamics under warming Keywords: climate warming, consumer-resource interactions, thermal evolution, interaction strength, thermal performance curves, algae, zooplankton

Manuscript in prep.

Álvarez-Codesal, S., Faillace, C. A., Garreau, A., Bestion, E., Synodinos, A.D., & Montoya, J.M.

Abstract

To more accurately predict the impacts of global warming on ecosystems it is vital to understand how evolutionary responses to increasing temperatures a ect interspeci c interactions. Predictions are di cult, because each interacting species can have di erent evolutionary trajectories in response to changing temperatures. We compared the evolutionary responses for populations of consumers and resources that have experienced long-term (i.e., 13 years) exposure to experimental warming. Here we provide a new mechanistic approach based on the temperature dependency of the balance of energy gain to energy loss for consumer and resource species simultaneously and then relate the paired balance of the interacting species to e ects to the outcomes of the interaction, as assessed by interaction strength. ermal evolution increased the energy gain-to-loss ratio (i.e., energetic balance) in one of the resource species across temperatures by decreasing the associated metabolic costs. e outcomes of thermal evolution in consumers, however, di ered depending on the food source. When consumers fed on one resource species, thermal evolution increased its energetic balance at middle and high temperatures, but not in cold conditions, where unevolved consumers instead exhibited larger energetic balances. For the second resource, thermal evolution diminished the energetic balance, but evolved consumers feeding on this species exhibited overall larger energetic stasis across temperatures. When examining e ects on interaction strength, we found that the temperaturedependence of interaction strength remained unchanged when both interacting species evolved in terms of energetic balance. However, these trends changed markedly (i.e., interaction strength increased in magnitude following thermal evolution) when thermal evolution of energetic balances of the two interacting species was uneven. Despite the apparent context-dependency in the outcomes of species interactions following thermal evolution, we suggest that closer examination of individual evolutionary responses in the interacting species can provide insight to better predict the impacts of climatic warming on consumer-resource interactions.

Introduction

Climatic warming represents a major challenge for organisms as it will expose them to novel temperature conditions. e thermal sensitivity of ectotherms, in particular, will partially determine how warming will impact them. For instance, species with narrow thermal tolerances that live close to their optimal temperatures (i.e., specialists) will likely be more a ected by warming than those that have broader thermal niches (i.e., generalists) [START_REF] Deutsch | Impacts of climate warming on terrestrial ectotherms across latitude[END_REF]Lurgi et al. 2012a). Two aspects of climatic warming are key to understanding how species will respond. First, exposure to extremely high temperatures during heat waves (i.e., acute warming events) are expected to intensify in frequency and severity in coming years (Brown 2020; Perkins-Kirkpatrick & Lewis 2020). Second, exposure to higher mean temperatures is expected to be a gradual process that will span multiple generations. is will provide opportunities for populations and communities to adapt to the new environmental conditions, which is likely to reduce the risk of extinctions [START_REF] Bush | Incorporating evolutionary adaptation in species distribution modelling reduces projected vulnerability to climate change[END_REF]. In some cases, organisms can respond to increasing temperatures through multiple mechanisms (e.g., plastic or evolutionary changes to phenology, behaviour or phenotype) [START_REF] Parmesan | Ecological and Evolutionary Responses to Recent Climate Change[END_REF][START_REF] Angilletta | ermal Adaptation[END_REF][START_REF] Tüzün | Evolution of geographic variation in thermal performance curves in the face of climate change and implications for biotic interactions[END_REF][START_REF] Kontopoulos | Adaptive evolution explains the present-day distribution of the thermal sensitivity of population growth rate Author summary[END_REF][START_REF] Radchuk | Adaptive responses of animals to climate change are most likely insu cient[END_REF]. Nevertheless, evolutionary adaptations of populations (e.g., heritable changes in physiology, morphology, behaviour) to warming remain understudied and, therefore, our ability to predict future outcomes limited.

As seen in Chapter 1, temperature impacts energy balances within and between organisms as a result of mismatches in thermal sensitivities of energy gain and loss [START_REF] Rall | Temperature, predator-prey interaction strength and population stability[END_REF][START_REF] Vucic-Pestic | Warming up the system: higher predator feeding rates but lower energetic e ciencies[END_REF][START_REF] Lemoine | Temperature-induced mismatches between consumption and metabolism reduce consumer tness[END_REF][START_REF] Iles | Toward predicting community-level e ects of climate: Relative temperature scaling of metabolic and ingestion rates[END_REF]. is can cause energetic restrictions for the organisms, particularly at high temperatures, where metabolic demands (i.e., energy loss) tend to increase with warming. When such energetic imbalances are maintained over long periods and the organisms cannot respond through thermal regulation or adaptation in physiological traits [START_REF] Mcgaughran | Evolutionary Responses to Warming[END_REF], extinctions are to be expected. us, understanding how temperature a ects the balance between an organism's energy gain and loss is key to understanding species performance and survival under warming.

Most theory and models that focus on species interactions under climatic warming, such as consumer-resource theory, do not account for evolutionary thermal adaptation of species [START_REF] Bideault | Temperature Modi es Consumer-Resource Interaction Strength rough Its E ects on Biological Rates and Body Mass[END_REF][START_REF] Faillace | Eco-evolutionary consequences of habitat warming and fragmentation in communities[END_REF]. ermal evolution, however, has the potential to strongly modify and even reverse the outcome of the interactions between consumers and resources under future warming [START_REF] Tseng | Species interactions mediate thermal evolution[END_REF]. Empirical evidence for thermal evolution in both resources and consumers independently has been mounting over the past decade across taxa [START_REF] Campillo | Selection on life-history traits and genetic population divergence in rotifers[END_REF][START_REF] Campillo | Local adaptation in rotifer populations[END_REF][START_REF] Sentis | ermal acclimation modulates the impacts of temperature and enrichment on trophic interaction strengths and population dynamics[END_REF][START_REF] Schaum | Temperature-driven selection on metabolic traits increases the strength of an algalgrazer interaction in naturally warmed streams[END_REF][START_REF] Tseng | Species interactions mediate thermal evolution[END_REF]. For instance, warm-adapted algae populations showed rapid evolution in multiple traits, exhibiting for example higher tness across temperatures, higher thermal optima of photosynthesis and growth rates, or smaller sizes compared to those from ambient origins (Schlüter et [START_REF] Cavalheri | Rapid evolution of thermal plasticity in mountain lake Daphnia populations[END_REF]. For instance, contemporary Daphnia populations, which have experienced heatwaves during recent decades, have signi cantly higher maximal thermal tolerance compared to a 'naïve' historic population from the 1960s [START_REF] Geerts | Rapid evolution of thermal tolerance in the water ea Daphnia[END_REF].

Evolutionary adaptations of consumers and/or resources to new thermal conditions can impact their interaction dynamics [START_REF] Angilletta | ermal Adaptation[END_REF][START_REF] Schaum | Temperature-driven selection on metabolic traits increases the strength of an algalgrazer interaction in naturally warmed streams[END_REF][START_REF] Tseng | Species interactions mediate thermal evolution[END_REF]. One of the most common approaches to consumer-resource interactions is the use of interaction strengths. Consumer-resource interaction strength quanti es the impact of the consumer on the resource and is a key determinant of the structure and dynamics of food webs [START_REF] Wootton | Measurement of interaction strength in nature[END_REF][START_REF] Berlow | Simple prediction of interaction strengths in complex food webs[END_REF]). e use of interaction strengths links empirical estimations with theoretical models of consumer-resource dynamics [START_REF] Berlow | Interaction strength in food webs : issues and opportunities[END_REF]). In the literature, interaction strength has been reported to both increase [START_REF] O'connor | Warming strengthens an herbivore-plant interaction[END_REF][START_REF] Rall | Universal temperature and body-mass scaling of feeding rates[END_REF][START_REF] Sampaio | Interaction strength between di erent grazers and macroalgae mediated by ocean acidi cation over warming gradients[END_REF][START_REF] Schaum | Temperature-driven selection on metabolic traits increases the strength of an algalgrazer interaction in naturally warmed streams[END_REF][START_REF] Bideault | Temperature Modi es Consumer-Resource Interaction Strength rough Its E ects on Biological Rates and Body Mass[END_REF]) and decrease [START_REF] Vasseur | A Mechanistic Approach for Modeling Temperature-Dependent Consumer-Resource Dynamics[END_REF][START_REF] Binzer | e dynamics of food chains under climate change and nutrient enrichment[END_REF][START_REF] Rall | Universal temperature and body-mass scaling of feeding rates[END_REF] with warming. However, how the strength of consumer-resource interactions changes with thermal evolution of either one or both of the interacting species remains largely unknown. From the few examples available, thermal evolution of only consumers has been reported to strengthen the consumer-resource interaction [START_REF] Schaum | Temperature-driven selection on metabolic traits increases the strength of an algalgrazer interaction in naturally warmed streams[END_REF][START_REF] Wang | ermal evolution ameliorates the longterm plastic e ects of warming, temperature uctuations and heat waves on predator-prey interaction strength[END_REF]) compared to those with no evolution. To date, few studies have looked simultaneously at patterns of thermal evolution of both consumers and resources in shaping their interactions [START_REF] Barton | Local adaptation to temperature conserves top-down control in a grassland food web[END_REF][START_REF] De Block | Local genetic adaptation generates latitude-speci c e ects of warming on predator-prey interactions[END_REF][START_REF] Tseng | Species interactions mediate thermal evolution[END_REF][START_REF] Wang | ermal plasticity and evolution shape predator-prey interactions di erently in clear and turbid water bodies[END_REF]. For example, in a tri-trophic food web, thermal adaptation of predators guaranteed the regulation of resource populations down in the food web [START_REF] Barton | Local adaptation to temperature conserves top-down control in a grassland food web[END_REF]. In this respect, when two species interact, we expect very di erent dynamics if thermal adaptation is observed in one or both interacting partners [START_REF] Faillace | Eco-evolutionary consequences of habitat warming and fragmentation in communities[END_REF]. To illustrate, if warm-adapted resource populations evolved higher thermal tolerance than ambientadapted populations, yielding higher densities at higher temperatures, this can weaken the interaction between the consumer and the resource, unless the consumer improves its thermal tolerance to persist with the resource densities at higher temperatures. We can envision that this could occur with species that di er in their capacities for evolutionary response. On the contrary, the adaptation of both species may instead drive cryptic dynamics where evolutionary processes yield patterns similar to expectations from solely ecological processes. For instance, using the former example (e.g., resource evolved higher thermal tolerance and higher densities at higher temperatures) if warm-adapted consumer populations evolve also higher thermal tolerances, at similar pace than the resource species, yielding also higher densities at higher temperatures, the consumer would be able to keep a similar e ect on resource biomass densities, yielding a similar outcome of the interaction to previous conditions with no evolution. erefore, in a species interaction framework, evaluating how thermal evolution a ects individual traits of the interacting species will provide vital information to improve predictions of the impacts of climate warming on consumer-resource dynamics To better understand how potential evolutionary adaptation to temperature of individual energetic traits in populations a ects species interactions, we conducted experiments with two algae species as resources and a grazer as the consumer from two communities with a history of long-term exposure to di erent temperature conditions. We aimed to answer three questions. First, do physiological traits related to energy gain and loss in populations of resources and consumers with contrasting thermal background histories evolve to temperature? Second, is there any adaptation in their energetic balances, i.e., the ratio between energy gain and loss?

ird, what e ect does such evolution have on interaction strength when comparing species pairs with di erent thermal background histories? For instance, if both interacting species have adapted similarly to warming, does it yield cryptic responses in species interactions.

Materials and methods

Study system

We focused on species with fast generation times and asexual reproduction under laboratory conditions so that evolutionary responses to background thermal histories could be evaluated. We collected organisms, two resource species, Chlamydomonas reinhardtii, Desmodesmus sp., and one consumer, Daphnia pulex, from two contrasting thermal populations from a longrunning eld mesocosm experiment in Dorset, UK, in 2019-as in Chapter 1 (see methods in Chapter 1, section 1.3 and Suppl. Methods S1.1 in Appx. A). ere, since 2005, half of the tanks-initially 10 but in 2019 only 8-are kept at a temperature 4°C above the other half, 8 tanks, that naturally uctuate with ambient temperatures [START_REF] Yvon-Durocher | Warming alters the size spectrum and shi s the distribution of biomass in freshwater ecosystems[END_REF]. is set-up allows for variation at diurnal and seasonal scales for both thermal treatments with only the experimentally imposed di erence of 4 C between treatments. Populations isolated from heated tanks are herea er de ned as 'warm' and those from unheated tanks are herea er de ned as 'ambient' . For the resources, one unique genotype was employed for each thermal population of each species, while for consumers, isolation of ve parthenogenetic females of D. pulex from each thermal treatment yielded 10 clonal lineages in total, i.e., 5 from ambient and 5 from warm conditions. A er isolation we maintained the clonal isolates individually in semi-continuous batch cultures in freshwater medium in incubators. Isolation, culturing conditions and experimental set-up followed the same protocols described in chapter 1 (section 1.3 and Appx. A. S1.1-3). However, initially during the process of full isolation and genetic analyses ambient and warm populations were maintained at di ering culturing conditions in two incubators, keeping the original 4 degrees' di erence (ambient at 18 and warm at 22°C) but the same 12:12 dark:light photoperiod regime and light intensity. en, since March 2020 all clonal batch cultures were transferred into a single incubator in common garden conditions at 20°C keeping the light regime and intensity unchanged until further experiments. Daphnia populations grew on a mixture of algae species, Chlamydomonas reinhardtii, Desmodesmus sp. and Tetradesmus obliquus, originally isolated from the same ponds as the Daphnia populations, i.e., ambient-origin Daphnia fed upon algae isolated from ambient mesocosms and vice versa.

In this study, we rst measured evolutionary responses to temperature of physiological and energetic responses in interacting consumer-resource pairs. ese measurements provided information on species' performance and survival. en we determined if thermal evolution of energetic traits of the interacting species provided insight into how thermal evolution changes the interaction strength with temperature. us, we evaluated whether evolution in the physiological traits of consumers and resources were likely to transform into altered consumerresource interactions across temperatures or cryptic e ects in which underlying evolution in the interacting populations instead maintained the (overall behaviour of the) interaction.

Effects on individual traits

We measured thermal dependencies of physiological rates related to energy gain (i.e., ingestion, net photosynthesis) and loss (i.e., respiration) for both thermal populations of the resources and the consumer feeding on each resource species always from the same thermal treatment in basal conditions at eight temperatures separately (see section 1.3 and Suppl. Methods S1.2 -3 in Appx. A). is experimental set-up, only pairs consumers with resources from the same thermal origin. Short-term oxygen depletion in dark conditions, and oxygen production in light conditions, of starved algal cells at eight temperatures (14, 18, 22, 26, 30, 34, 38, 42°C) measured per capita respiration and net photosynthesis rates of algae species. Short-term oxygen consumption in dark conditions by ve starved adults of Daphnia on each replicate at eight temperatures (14, 18, 22, 26, 30, 32, 34, 36°C) measured per capita respiration rates of D. pulex. Finally, per capita ingestion rates were measured as the di erence between initial and nal algal densities of either resource species in presence or absence of ve starved consumers per replicate at the same eight temperatures. While for respiration tests (and algal net photosynthesis) replicates were exposed over 1.5 hours to each test temperature, the time of exposure was 2.5 hours for ingestion experiments. Because the body mass of daphnids and biovolume of algae genotypes di ered signi cantly between thermal origins (Fig. S2.1), we did a mass and biovolume correction respectively to all individual per capita rates of energetic traits, i.e., respiration, net photosynthesis and ingestion (see Appx. B Supp. Methods S2.1). Finally, per capita rates, either mass or biovolume corrected, for consumers or resources were transformed into energy equivalents to make quantitatively comparable units of energy gain and loss (Appx. A. S1.5). In addition, for the ingestion rates of Daphnia, we applied assimilation e ciencies speci c to each of the resource species upon which the Daphnia fed.

As in the previous chapter, for energetic traits exhibiting unimodal responses to temperature (i.e., respiration and net photosynthesis), we tted the data to a Sharpe-School eld model [START_REF] School Eld | Non-linear regression of biological temperature-dependent rate models based on absolute reaction-rate theory[END_REF], characterising ermal Performance Curves (TPC) for each trait parameter in R statistical so ware (4.0.3) (Pad eld et al. 2021; R Core Team 2021). From this model, we obtained TPC parameters including thermal sensitivity of the rate or the slope before the optimum E a , the temperature of the optimum T opt , the maximal rate or magnitude MRP, and the negative slope beyond the optimum E h (see methods in Chapter 1, section 1.3 and Suppl. Methods S1.4 in Appx. A). For linear responses to temperature, such as in ingestion rates, we tted the data to General Linear Models (GLMs), a er examination of possible data outliers (following methods described in Appx. A Supp. Methods S1.4), and used two-way analysis of variance (ANOVA) to evaluate the e ects of temperature and thermal origin and their interaction on ingestion. To get values of ingestion slopes (i.e., estimates, standard deviation and t-value) for each algal species we used the `emtrends` function and for the intercepts the `emmeans` function setting temperature to a value of zero. Both functions employed belong to the emmeans R-package [START_REF] Lenth | emmeans: Estimated Marginal Means, aka Least-Squares Means[END_REF]. en, to get the ingestion predictions that were used for calculating the energetic balance, when ingestion rates showed no signi cant temperature dependence (p-value of the slope > 0.05) we calculated predicted values by tting the ingestion data to a linear regression with the slope constrained to a value of zero.

Effects on energetic balances and adaptations on species traits

We computed energetic balances using predicted values of each trait in energy units from either the TPC or GLM models in the form of net photosynthesis-to-respiration ratio (P/ R r ) for resources, and ingestion-to-respiration ratio (I/R c ) for consumers. In cases where the trends of ingestion rates were insensitive to temperature (slope p > 0.05) we assumed constant ingestions rates across temperatures for the predictions with intercepts constrained to the mean value and the slope to zero. Optimum values of energetic balances, i.e., energy gain-to-loss ratios, were de ned as maximum temperature (T m ), and the crossover temperature (Tc) was the temperature at which energy gain equals loss (i.e., when gain-toloss ratio equals unity).

We considered that a warm-origin population of a focal species exhibited thermal adaptation when the energetic balance was greater than in those from ambient origin.

Effects on species interaction

We measured interaction strength, with consumers only exposed to resources from the same thermal origin. Per capita interaction strength between consumers and resources was measured as the log response ratio calculated as in [START_REF] Schaum | Temperature-driven selection on metabolic traits increases the strength of an algalgrazer interaction in naturally warmed streams[END_REF] (see methods in section 1.3.4 of chapter 1). is ratio measures the absolute value of per capita interaction strength by time, accounting for algal growth with and without consumers (O'Connor 2009). It works well for short-term experiments because it does not depend on equilibrium conditions [START_REF] Laska | eoretical concepts and empirical approaches to measuring interaction strength[END_REF][START_REF] Berlow | Interaction strength in food webs : issues and opportunities[END_REF]). Large values of interaction strength indicate a strong per capita impact of the consumer on the resource density. Conversely, low values of interaction strength indicate a weak impact of one consumer on resource densities. We tted values of interaction strength to general linear models (GLM) by conducting a full linear regression including the interaction between temperature and thermal origin for each algal species and performed a two-way ANOVA to assess di erences in slope and intercepts.

Results

Effects on individual traits

ermal reaction norms of energy gain and loss di ered in general between populations with di erent thermal origin for both resources and consumers (Figs 2.1 -4, S2.1, tables 2.1 -4). e warm-origin genotype of C. reinhardtii show less dramatic and more homeostatic responses than their ambient counterparts. In particular, the thermal responses of both respiration and net photosynthesis in the warm-origin genotype of C. reinhardtii showed weaker thermal sensitivity, i.e., shallower activation energies, and were of smaller magnitude than in those of the ambient-origin genotype. However, for this algae species, optimum temperatures of energy gain and loss were very similar between the genotypes from both Table 2.1. Estimated parameters of thermal performance curves and con dence intervals of resources (biovolume-corrected) and consumer (mass-corrected) rates that followed unimodal responses with temperature for ambient (A) and warm (W) thermal origin populations. Sharpe-School eld model parameters show mean estimated values of activation energy (E a ), deactivation energy (E h ), optimum temperature (T opt ), and maximum rate of performance (MRP) for resources' net photosynthesis (P) and respiration (R r ) rates, and consumer respiration (R c ) rates. * D. pulex per capita respiration units are Joules L -1 h -1 individual -1 ** D. pulex per capita respiration units' volume-corrected are Joules h -1 individual -1 † D. pulex mass-corrected respiration units are Joules L -1 h -1 µg -1 ‡ D. pulexx mass-corrected respiration units' volume-corrected are Joules h -1 µg -1 (c-d). Ambient-to-warm (A/W) ratios are calculated using the predicted values of Sharpe-School eld models for each parameter. Units of both parameters are mg O2 L -1 min -1 µm -3 . Values of A/W ratios below unity correspond to thermal areas where warm-origin genotypes respire or photosynthesised more than ambient ones. Conversely, for values larger than one, ambient-origin genotypes outscore those of warm origin. -1 h -1 µg -1 ). Linear model outputs for the results testing the e ect of temperature on ingestion rates for D. pulex feeding on each algal species in the form of lm(ingestion ~ Temperature * ermal origin) for each algae species. Daphnia populations were only paired with same thermal origin resources, i.e., ambientorigin consumers with ambient-origin resources and vice versa. Contrast analysis for slopes of ambient and warm isolates of C. reinhardtii are as follows: estimate = -0.000515 ± 0.000992, t-ratio = -0.519, p-value = 0.6049; and for Desmodesmus sp.: 0.0014 ± 0.000707, t-ratio = 1.977, p-value= 0.05. Highlighted estimates of p-values represent signi cance levels lower than 0.05. thermal origins. On the contrary, the genotype of Desmodesmus sp. isolated from the warm treatment exhibited higher respiration rates and lower net photosynthesis than the ambient genotype across temperatures. For this species, the optimum temperature of respiration remained very similar across thermal origin, but that of net photosynthesis di ered slightly with the warm-origin genotype exhibiting a higher thermal optimum.

Species

Table 2.2. Summary table of thermal sensitivities of D. pulex mass-corrected ingestion rates (JL

Per capita consumer respiration had a unimodal trend with temperature for both populations regardless of thermal origin, with some marked di erences. Warm-origin daphnids had reduced thermal sensitivity of respiration by nearly half compared to ambientorigin individuals and had a slightly increased optimum (Fig. 2.3a, Table 2.1). At intermediate temperatures (20 -28 °C) the magnitude of the respiration rate also decreased signi cantly. While per capita rates of D. pulex respiration di ered between populations from the two thermal origins, this di erence disappeared when correcting by biomass (Fig. 2.3b, Table 2.1). Nonetheless, overall consumer respiration was more sensitive to temperature than ingestion feeding on either resource species (Figs 2.3, 2.4, tables 2.1 -3). Ingestion rates of D. pulex feeding on C. reinhardtii showed negative trends with temperature (ambient: β = -0.0015, R2 = 0.15, p = 0.03; warm: β = -0.0010, R2 = 0.03, p = 0.13) with no di erence in slopes (contrast analysis: p = 0.60) or intercepts (contrast analysis: p = 0.8) between thermal origin consumer-resource pairs. On the other hand, the ingestion rate of D. pulex on Desmodesmus sp. showed contrasting responses with increasing temperatures for the two populations (ambient: β = 0.00067, R2 = 0.03, p = 0.18; warm: β = -0.0007, R2 = 0.06, p = 0.14), di ering in both slope (contrast analysis: p = 0.05) and in intercept (contrast analysis: p = 0.03) between them. Although ingestion by the ambient Daphnia on Desmodesmus sp. increased with temperature, ingestion was insensitive to temperature for the warm pair.

Effects on energetic balances

Because thermal performance of energy gain and loss di ered within and across thermal genotypes of resources (Figs 2.5, 2.6, 2.7), this translated into di erences in energetic balances. Although thermal optima (T m ) of energetic balances were very similar within a resource species, thermal responses of warm-origin genotypes were broader than those of ambient-origin resources. e potential energy acquired, i.e., energy balance, by warm-origin C. reinhardtii was higher than that of the ambient-origin population across temperatures, with the exception of intermediate temperatures around the optimum (Fig. 2.7a). Conversely, for Desmodesmus sp., the ambient genotype was always energetically more e cient than the warm genotype across the whole temperature range when accounting for biovolume and cell di erences (Fig. 2.7b).

Because only ambient-origin Daphnia feeding on ambient-origin C. reinhardtii had temperature-dependent ingestion, we used constant ingestions rates across temperatures for the remaining pairs with intercepts constrained to the mean value and the slope to zero (Figs 2.8, 2.9). us, the di erences in ingestion rate values between ambient and warmadapted populations translated into a stronger decline of energetic balances with increasing temperature for ambient-origin Daphnia and about a 4°C higher crossover temperature (i.e., Tc) for the warm-origin population. Discrepancies in energetic balances between ambient and warm Daphnia populations evidenced marked di erences depending upon food source and temperature (Fig. 2.10). For instance, at low temperatures when Daphnia fed on C. reinhardtii, ambient-origin daphnids showed higher energetic availability than those from the warm treatment. However, at temperatures above 18°C the advantage in energy availability reversed. For the Daphnia-Desmodesmus sp. pair though, warm-origin daphnids showed a larger energetic balance for most of the temperatures tested.

Effects on interaction strength

e e ect of temperature on interaction strength depended upon the thermal origin and identity of the resource (Fig. 2.11, Table 2.4). When comparing among the trends observed for interaction strength for ambient-origin and warm-origin pairs, we observed that for the pair where both the consumer and resource evolved in energetic traits in tandem-D. pulex and C. reinhardtii-the strength of the consumer-resource interaction was maintained across thermal origin pairs. Speci cally, while temperature decreased the values of interaction strength (ambient pair: β = -0.00073, p < 0.01, warm pair: β = -0.00053, p < 0.01), its e ects did not depend upon the interaction of thermal origin with temperature (ANOVA test: F 1,88 = 0.479, p = 0.49). However, for the second pair-D. pulex and Desmodesmus sp.-where evolution occurred solely in the traits of the consumer, we observed a di erent pattern. Here, the strength of the per capita consumer-resource interaction for the warmorigin pair increased in magnitude relative to that of the ambient-origin pair (ANOVA test: F 1, 89 = 3.66, p = 0.05). For this pair, even though interaction strength di ered marginally (ANOVA test: F1, 89 = 2.869, p = 0.09) between thermal origins across temperatures (interaction in the ambient pair increased: β = 0.00040, p = 0.04, and in the warm pair was temperature independent: β = -0.000065, p < 0.74), this di erence was particularly larger at low temperatures, with contrasting intercept values (contrast analysis: p = 0.03).

Table 2.4 Statistical results of two-way ANOVA

for the e ects of temperature and populations' thermal origin on per capita interaction strength in a short-term experiment with Daphnia pulex feeding either on C. reinhardtii or Desmodesmus sp. Daphnia populations were only paired with resources from the same thermal origin, i.e., ambient-origin consumers with ambient-origin resources and vice versa. e full model tests the e ect of temperature on interaction strength values with interaction of thermal origin in the form of lm(interaction strength ~ Temperature * thermal origin), for C. reinhardtii: F 3,88 = 8.542, p < 0.001, and R2 = 0.22; and for Desmodesmus sp.: F 3,89 = 2.675, p = 0.05, and R2 = 0.082. Highlighted estimates of p-values represent signi cance levels lower than 0.05.

Response

Discussion

To more accurately predict the impacts of global warming on ecosystems it is vital to understand how adaptations of di erent species to increasing temperatures a ect their biotic interactions. In particular, evolution can alter consumer-resource interactions in a variety of ways. For instance, evolution in anti-herbivore defences in resource species has been shown to impact consumer-resource interactions by increasing densities of herbivoreresistant genotypes, leading to either declines [START_REF] Meyer | Prey evolution on the time scale of predator-prey dynamics revealed by allele-speci c quantitative PCR[END_REF] or increases [START_REF] Cairns | Evolution in interacting species alters predator life-history traits, behaviour and morphology in experimental microbial communities[END_REF] in consumer densities in the long-term. More speci cally, thermal evolution in predator attack rates resulted in higher mortality rates for prey populations from contrasting latitudinal origins to that of the predator [START_REF] De Block | Local genetic adaptation generates latitude-speci c e ects of warming on predator-prey interactions[END_REF]. Also, thermal evolution in herbivore metabolism and consumption was reported to strengthen long-and short-term consumer-resource interactions [START_REF] Schaum | Temperature-driven selection on metabolic traits increases the strength of an algalgrazer interaction in naturally warmed streams[END_REF]). In the context of climate warming, this is likely to be especially important. Organisms respond to temperature through a number of physiological responses with a combination of unimodal (e.g., metabolism, respiration, handling time, intrinsic growth) and linear (e.g., ingestion, interaction strength) trends.

Mismatches in the thermal dependencies of these physiological and other tness traits (i.e., imbalanced thermal response between the di erent traits) makes di cult to predict the e ects of climate change on species interactions, as seen in chapter 1. Even more challenging, consumers and resources respond simultaneously to temperature in a way that the net e ect of evolution can increase or decrease the outcome of their interaction. For instance, thermal evolution of a resource species was reported to facilitate the thermal evolution of growth rates for the consumer, resulting in larger consumer population size [START_REF] Tseng | Species interactions mediate thermal evolution[END_REF]).

e understanding of how evolutionary responses of each interacting species combine to drive outcomes of the interaction under climatic warming remains a major challenge. We argue that closer examination of the warming-induced evolutionary responses to underlying physiological and energetic traits in both interacting species will provide the information that we need to predict the direction of evolutionary changes of species interactions. In our study, we found two very distinctive outcomes for short-term interaction strengths between consumer-resource pairs with di ering thermal histories. In one case, when D. pulex fed on C. reinhardtii, we found that interaction strength did not change between pairs that di ered in their long-term histories of thermal exposure. However, in the second case, when D. pulex fed on Desmodesmus sp., interaction strength changed signi cantly following thermal evolution.

e contrasting results for interaction strength suggest a strong context-dependency of the e ects of consumers on resource population densities across temperature gradients when thermal evolution takes place.

In our rst consumer-resource pair, D. pulex and C. reinhardtii, interaction strength did not change as a result of thermal evolution, suggesting that consumer-resource dynamics would remain unaltered under warming. Two possibilities exist to explain this result: (i) no thermal evolution occurred in either species or (ii) thermal evolution occurred, but maintained the outcome of the interaction, leading to so-called cryptic responses. In our system, the exploration of individual physiological and energetic traits revealed thermal evolution in both interacting species, yielding a cryptic e ect on the interaction, where the outcome remains unchanged regardless the evolutionary context [similar to [START_REF] Brans | Cryptic eco-evolutionary feedback in the city: Urban evolution of prey dampens the e ect of urban evolution of the predator[END_REF]]. Respiration rates of warm-origin C. reinhardtii (Fig. 2.1a), had lower thermal dependency compared to that of the ambient-origin genotype, which in general translated into a more homeostatic response to temperature [similar to [START_REF] Tian | ermal adaptation occurs in the respiration and growth of widely distributed bacteria[END_REF]]. us, thermal evolution in respiration rates of this species led to compensatory metabolic responses to warming (Pad eld et al. 2017). Our results for net photosynthesis (Fig. 2.1b) t the expectations for a specialist-generalist shi [START_REF] Jin | Fast adaptation of tropical diatoms to increased warming with tradeo s[END_REF]). e thermal niche width in the warmadapted genotype was wider than that of the ambient-adapted genotype, but at the expense of decreased maximum rates of net photosynthesis. ese combined evolutionary responses led to a wider thermal niche for the energetic balance of the warm-adapted genotype, although around the optimum both genotypes performed similarly. ese results agree with those reported in other systems. [START_REF] Cullum | Evolutionary Adaptation to Temperature . IX . Preadaptation to Novel Stressful Environments of Escherichia coli Adapted to High Temperature Author ( s )[END_REF] showed that selection for improved tness at moderate temperatures reduced growth at temperature extremes for Escherichia coli. In copepods, evolution of thermal breadth expansion comes at the expense of reductions of the maximal thermal performance at intermediate temperatures [START_REF] Willett | Potential tness trade-o s for thermal tolerance in the intertidal copepod Tigriopus californicus[END_REF]. On the other hand, thermal responses of the mass-corrected ingestion for D. pulex feeding on C. reinhardtii seems to be consistent across thermal origins. For both thermal origin pairs, ingestion did not di er, decreasing with increasing temperature [also observed by [START_REF] Kooijman | Population Consequences of a Physiological Model for Individuals[END_REF]]. However, as the magnitude of ingestion rates and respiration between thermal origin slightly di ered, this translated into larger energetic balances for ambient-origin D. pulex at low temperatures (i.e., < 18°C) and a reverse pattern for temperatures above 18°C. Similarly, a study with damsel ies and Daphnia showed that local thermal adaptation (i.e., same latitudinal origins) of both species did not change the e ect of the predator on prey survival when Daphnia was grown at two di erent temperatures [START_REF] De Block | Local genetic adaptation generates latitude-speci c e ects of warming on predator-prey interactions[END_REF].

For the second consumer-resource interaction, D. pulex feeding on Desmodesmus sp., interaction strength di ered between thermal origin pairs. Here, interaction strength was temperature-independent for the warm-origin pair, however the overall impact of the consumer on the resource, particularly at low and intermediate temperatures, was stronger compared to the ambient-origin pair. In this case, the consumer had an increased energetic balance for the warm-origin population. On the contrary, the warm-origin genotype of Desmodesmus sp. exhibited both higher respiration and lower net photosynthesis rates across temperatures than the ambient-origin genotype. Here, for the warm-origin genotype, although the energy gain-to-loss ratio was wider across temperatures than for the ambientorigin genotype (similar to the observed pattern in C. reinhardtii) the magnitude of the energetic balance was almost half of that of the ambient-origin genotype. One possible explanation for this result is that either the warm-origin genotype showed a maladaptation to warming, or it adapted to something else at the community level, which was not captured in our experiments. For the consumer, when correcting by mass, respiration rates changed very little with temperature between thermal origins, however, the response of Daphnia ingestion on Desmodesmus sp. di ered between thermal origins. Ingestion was higher for the warm-origin population, but it is important to mention that the warm-origin genotype of Desmodesmus sp. showed signi cant variability in the frequency of cell aggregates, as well as in the mean cell biovolume, that could a ect aspects of ingestion, such as handling time.

us, while ingestion by warm-origin daphnids was higher at low temperatures, the warmorigin genotype of Desmodesmus sp. exhibited a lower energetic balance compared to the ambient-origin genotype. is translated into a mismatch in thermal adaptation of energetic balance between the consumer and resource species. As the consumer increased its energetic balance, the resource fared worse, and as a consequence, the consumer exerted a stronger e ect on the resource density in the warm-origin pair. We suggest that this situation-where thermal adaptation occurs in just one of the interacting species (i.e., the consumer increased the gain-to-loss ratio a er thermal evolution)-may prove to be an important driver of altered interspeci c interactions or community dynamics in warmed communities, resulting in dramatic changes to eco-evolutionary dynamics, which is analogous to the mismatch between habitat niche and the evolution of interacting species to habitat conditions for instance in a consumer-resource interaction as proposed in [START_REF] Faillace | Eco-evolutionary consequences of habitat warming and fragmentation in communities[END_REF]].

Our results demonstrate how exploring individual energetic balances of interacting species, and their possible thermal adaptations, increases the mechanistic understanding and predicting power on how species interactions and community dynamics will respond to climate change. e exploration of thermal evolution of physiological and energetic traits provides clues about why we observed di erent outcomes in interspeci c interactions for di erent species pairs. In natural systems there are cases where the speed of thermal evolution can be altered by life-history constraints for each species. For instance, interactions between consumers with long generation times with resources with very fast generation times (e.g., shzooplankton interactions) are likely to produce mismatches in terms of thermal adaptations. In these conditions, even if both consumers and resources adapt to temperature increases, the speed of selection can be slower for consumers, and then we would expect important changes in the interaction, as seen for D. pulex and Desmodesmus sp. in our study. On the other hand, in interacting pairs with either similar selection speeds or rapid generation times, where both species can evolve similarly, the chances for cryptic changes in the interspeci c interactions, and in their dynamics, are more likely. In the case of consumers feeding on multiple resources simultaneously, our results suggest that caution should be exercised when scaling-up to community-level responses, as di erent consumer-resource pairs can have very di erent evolutionary responses to long-term exposure to environmental changes.

Chapter 3 Ecological and evolutionary responses of primary producers to increasing temperatures

Keywords: temperature-dependence, carrying capacity, growth rates, nutrient acquisition, thermal evolution, reaction norms, algae, community dynamics, consumer-resource interactions

Manuscript in prep.

Álvarez-Codesal, S., Faillace, C. A., Garreau, A., Bestion, E., Synodinos, A.D., & Montoya, J.M.

Abstract

Mean temperatures are rising globally, a ecting multiple biological rates governing the physiology and productivity of species. is will have far-reaching consequences through species interactions ultimately altering food webs and ecosystems. erefore, it will be key to understand the thermal dependence of species traits in food webs, as well as how these dependencies evolve in response to prolonged warming. In any food web resource species, such as primary producers, constitute the basis of the chain. Here we investigated the growth rate and carrying capacity, for ambient-origin and warm-origin (ambient+4 °C) genotypes of two algal species, C. reinhardtii and Desmodesmus sp., across a temperature gradient from 14 -38 °C. We found that resource growth had a unimodal thermal dependence, while carrying capacity declined linearly across species and genotypes. ermal evolution of C. reinhardtii increased its population growth rate and carrying capacity. For Desmodesmus sp., population growth rate was also higher in the warm-origin genotype, however, carrying capacity was lower. In addition, we found that the thermal dependence of nutrient acquisition followed a unimodal trend for C. reinhardtii, or increasing saturating for Desmodesmus sp., which, in combination with the declining carrying capacity with warming, suggests a low e ciency in biomass conversion of primary producers at higher temperatures. ese results provide clues on how evolutionary history can alter the response of resource species to warming. It will be fundamental to expand this line of research to include consumer species in order to, ultimately, project the e ects of warming via eco-evolutionary pathways on the trophic interactions.

Introduction

Global warming is expected to increase mean global surface temperature by 2-5 degrees by 2100 (IPCC, 2021), presenting an important risk for the survival of individual organisms and, as a consequence, for biodiversity across the globe [START_REF] Green | Extinction risk from climate change[END_REF][START_REF] Pimm | Climate Disruption and Biodiversity[END_REF][START_REF] Pecl | Biodiversity redistribution under climate change: Impacts on ecosystems and human wellbeing[END_REF]. Environmental temperature is fundamental in determining species physiology (e.g., metabolism), specially for ectotherms (as seen in Chapter 1) [START_REF] Yodzis | Energy Flow and the Vertical Structure of Real Ecosystems[END_REF]. e e ects of this temperature change at the species level will propagate to species interactions (as seen in Chapter 1 and 2), ultimately a ecting food web dynamics and ecosystem functioning (Yvon-Durocher et al., 2010b;[START_REF] Kosten | Warmer climates boost cyanobacterial dominance in shallow lakes[END_REF][START_REF] Meerho | Environmental Warming in Shallow Lakes. A Review of Potential Changes in Community Structure as Evidenced from Space-for-Time Substitution Approaches[END_REF][START_REF] Yvon-Durocher | Five Years of Experimental Warming Increases the Biodiversity and Productivity of Phytoplankton[END_REF][START_REF] Velthuis | Warming advances top-down control and reduces producer biomass in a freshwater plankton community[END_REF].

Intrinsic growth rate and carrying capacity are two fundamental properties of populations that underlie both population and community dynamics, as demonstrated theoretical and empirically [START_REF] Savage | E ects of body size and temperature on population growth[END_REF][START_REF] Gilbert | A bioenergetic framework for the temperature dependence of trophic interactions[END_REF][START_REF] Uszko | E ects of warming on predatorprey interactions -a resource-based approach and a theoretical synthesis[END_REF][START_REF] Bernhardt | Metabolic theory and the temperaturesize rule explain the temperature dependence of population carrying capacity[END_REF][START_REF] Synodinos | eory of temperaturedependent consumer-resource interactions[END_REF]) . e intrinsic growth rate of a population, r, corresponds to the maximal exponential growth rate of a population in the absence of nutrient limitation [START_REF] Savage | E ects of body size and temperature on population growth[END_REF]). As such, the intrinsic growth rate re ects the di erence in per-capita birth and death rates of a population. On the other hand, carrying capacity quanti es the maximum densities of the resource populations once growth has saturated, i.e., when r=0 and population densities remain constant over time [START_REF] Savage | E ects of body size and temperature on population growth[END_REF]). Understanding how these population properties change with increasing temperatures will be of great importance for determining and predicting the e ects of climate warming on species interactions and community dynamics. ermal dependencies of resources' growth rates have been assessed in several studies, yielding either an exponentially increasing or a unimodal response to temperature [START_REF] Savage | E ects of body size and temperature on population growth[END_REF][START_REF] Nejrup | Temperature-and light-dependent growth and metabolism of the invasive red algae Gracilaria vermiculophylla -a comparison with two native macroalgae[END_REF][START_REF] Grimaud | Modeling the temperature e ect on the speci c growth rate of phytoplankton: a review[END_REF][START_REF] Kremer | Temperature-and size-scaling of phytoplankton population growth rates: Reconciling the Eppley curve and the metabolic theory of ecology[END_REF]). However, few measurements of the thermal dependence of carrying capacity exist and these have shown a negative trend (exponentially decreasing) with warming [START_REF] Fussmann | Ecological stability in response to warming[END_REF][START_REF] Bernhardt | Metabolic theory and the temperaturesize rule explain the temperature dependence of population carrying capacity[END_REF]. is can be interpreted as a consequence of increasing metabolic rate with warming: given a xed amount of nutrients, population density at higher temperatures becomes limited by higher metabolic costs. Additionally, accounting for decreased body size with warming weakened the negative trend of the carrying capacity's thermal dependence, i.e., per capita metabolic demands became smaller, allowing for the same amount of nutrients to sustain more individuals [START_REF] Bernhardt | Metabolic theory and the temperaturesize rule explain the temperature dependence of population carrying capacity[END_REF]. eoretical work has proposed all possible shapes of thermal-dependence for K, each corresponding to a di erent mechanism. For instance, K has been assumed to monotonically decrease derived from increasing metabolic rates with warming [START_REF] Rall | Temperature, predator-prey interaction strength and population stability[END_REF][START_REF] O'connor | eoretical Predictions for How Temperature A ects the Dynamics of Interacting Herbivores and Plants[END_REF][START_REF] Binzer | e dynamics of food chains under climate change and nutrient enrichment[END_REF][START_REF] Dell | Temperature dependence of trophic interactions are driven by asymmetry of species responses and foraging strategy[END_REF][START_REF] Fussmann | Ecological stability in response to warming[END_REF][START_REF] Sentis | Temperature-size responses alter food chain persistence across environmental gradients[END_REF]). e hump-shaped response has been linked to optimal growth conditions with respect to light [START_REF] Uszko | E ects of warming on predatorprey interactions -a resource-based approach and a theoretical synthesis[END_REF], while a U-shaped thermal dependence would re ect the peak in intraspeci c competition for temperatures optimal for growth (Amarasekare 2015 and references within). Finally, K has been represented as temperature-invariant (i.e., constant) due to the lack of clarity associated to the thermal dependence of stoichiometry which should partially determine the carrying capacity [START_REF] Uszko | E ects of warming on predatorprey interactions -a resource-based approach and a theoretical synthesis[END_REF][START_REF] Synodinos | eory of temperaturedependent consumer-resource interactions[END_REF] . us it becomes clear that there is an urgent need for more empirical evidence on the thermal dependence of the carrying capacity, since the structure and dynamics of trophic communities strongly depend on this [START_REF] Johnson | A metric for quantifying the oscillatory tendency of consumer-resource interactions[END_REF][START_REF] Synodinos | eory of temperaturedependent consumer-resource interactions[END_REF].

Adding a further layer of complexity, the thermal dependence of these traits can evolve over time. Evolutionary adaptation of intrinsic growth rate has been reported for di erent algae species across ecosystems ( omas et al. 2012;[START_REF] Schlüter | Adaptation of a globally important coccolithophore to ocean warming and acidi cation[END_REF][START_REF] Schaum | Adaptation of phytoplankton to a decade of experimental warming linked to increased photosynthesis[END_REF]Schaum et al. , 2018a;;[START_REF] Aranguren-Gassis | Nitrogen limitation inhibits marine diatom adaptation to high temperatures[END_REF][START_REF] Kottuparambil | Adaptation of Red Sea Phytoplankton to Experimental Warming Increases eir Tolerance to Toxic Metal Exposure[END_REF][START_REF] Liang | Molecular mechanisms of temperature acclimation and adaptation in marine diatoms[END_REF]. ermal evolution generally increased both the thermal optimum (i.e., temperature at which growth achieves the maximum value) and the maximum growth rate of populations that evolved at higher temperatures (i.e., warm-adapted populations). It remains unclear the extent to which carrying capacity can evolve in response to temperature. Given the importance of these parameters, in order to determine the e ects of climate warming on consumer-resource dynamics, we must understand how intrinsic growth rate and carrying capacity evolve in response to habitat warming.

Both population growth rate and carrying capacity depend on nutrient uptake by autotrophs, nitrogen in particular. Nitrogen is one of the most abundant chemical elements in living matter and is present in important biomolecules such as amino and nucleic acids (DNA/RNA), chlorophyll and amino sugars [START_REF] Stankiewicz | Nitrogen and N-Containing Macromolecules in the Bio-And Geosphere: An Introduction[END_REF]. Hence, to get a more comprehensive understanding of the ecological and evolutionary responses to temperature of r and K, we measured adittionally the temperature dependency and evolutionary adaptation of nitrogen uptake by algae. Understanding how resources acquire nitrogen from the environment as temperature increases can help us to better understand how fast nutrients are processed and biomass is accumulated, and ultimately the e ects on consumer-resource dynamics [START_REF] Uszko | E ects of warming on predatorprey interactions -a resource-based approach and a theoretical synthesis[END_REF].

In this chapter, we aim to answer two questions. First, are there consistent patterns across resource species in the thermal dependencies of intrinsic growth rates, carrying capacity and nutrient acquisition? Second, is there evidence of evolutionary adaptation in these resource traits between populations with di erent thermal histories? Finally, we consider the implications of the thermal dependencies and evolutionary changes of resource traits on consumer-resource dynamics. For doing so, we measured population growth rates, carrying capacity and nutrient acquisition across a gradient of temperatures (14-38 °C) for two algal species whose populations originated from two di erent temperature regimes ('ambient' and 'warm'). is determined whether the thermal dependence of growth rates and carrying capacity di ered between warm and ambient populations within species and, hence, whether the traits evolved.

Materials and methods

We collected two algae species, Chlamydomonas reinhardtii and Desmodesmus sp., from two contrasting thermal populations from a long-running eld mesocosm experiment in Dorset, UK, in January 2019 (see Suppl. methods in Appx. A S1.1). ere, since 2005, half of the tanksinitially 10 but in 2019 only 8-are kept at a temperature 4°C above the other half, 8 tanks, that naturally uctuate with ambient temperatures [START_REF] Yvon-Durocher | Warming alters the size spectrum and shi s the distribution of biomass in freshwater ecosystems[END_REF]. Populations isolated from heated tanks are herea er de ned as 'warm' and those from unheated tanks are herea er de ned as 'ambient' . A er isolation we maintained the clonal isolates individually in semi-continuous batch cultures in freshwater COMBO media [START_REF] Kilham | COMBO: A de ned freshwater culture medium for algae and zooplankton[END_REF] in two incubators keeping the original 4 degrees' di erence (ambient at 18 and warm at 22 °C) but with identical photoperiod and light intensity. Since March 2020 all clonal batch cultures were transferred into a single incubator in common garden conditions at 20°C keeping the light regime and intensity unchanged until further experiments.

We measured growth rates, r, and densities at carrying capacity, K, by means of growth curve experiments, as well as nitrate acquisition, for the two di erent thermal genotypes of the two algal species under a 12:12 light: dark photoperiod regime and a PAR intensity of 67 -70 µmol m -2 s -1 . Growth curves and nutrient acquisition experiments were conducted independently in separate experimental set-ups. For both experiments, we tested the e ects of eight essay temperatures (14, 17, 20, 23, 26, 29, 32 and 35 °C). We used a maximum of 35°C based on previous studies on Critical thermal maxima (i.e., CT max : the upper critical temperature in respect to growth) for these two algal species [START_REF] Nalley | Temperature e ects on growth rates and fatty acid content in freshwater algae and cyanobacteria[END_REF]. However, because algal growth was still noti ed for some genotypes at 35°C, we decided to include an extra temperature (38 °C) for growth curve analyses.

Growth curves to estimate growth rates and carrying capacities

Growth was assessed as algal density change over time (days), measured for a period of 21 days. At the beginning of the experiment we used algae from the clonal batch cultures growing in exponential phase in common garden conditions. First, we checked algal densities using ow cytometry and then adjusted the initial densities to c. 100 -200 cell/ml by dilution with COMBO media and distributed into the replicates. We used one clonal isolate for C. reinhardtii ambient (i.e., n = 6 per tested temperature) but we used 3 isolates from a single genotype of the warm instead (i.e., n = 18 per temperature). For Desmodesmus sp. we used 4 isolates of a single genotype for ambient and 4 isolates of a single and di erent genotype from warm (i.e., n = 24 at each temperature). e reason for keeping di erent isolates within genotypes was because we observed some marked di erences in morphology across the isolates from the same putative genotype (see sequencing methods in Appx. A S1.1).

For each thermal isolate, we set up a 6-well plate, constituting 6 replicates, where in each well-replicate we distributed a total volume of 10 ml of starting algal densities. Following this, we randomly placed the plates inside Panasonic incubators at experimental temperatures. Every day, over 21 days, we routinely sampled at same times 150 µl of well homogenised sample from each replicate into 96-well plates, added 15 µl of 10% sorbitol solution and stored at -80°C for subsequent batch process using ow cytometer (see further methods on ow cytometry extraction in Appx. A S1.3). Following the daily sampling, we assigned a di erent random location to each plate inside the incubators. Because of the large size of experimental replicates by populations and temperatures, we divided the temperatures in three di erent temporal blocks. First, in October 2020 we undertook growth experiments at 14, 20, 26 and 32 °C, in March 2021 at 17, 23, 29 and 35 °C, and in July 2021 at 38 °C. Finally, to evaluate whether biovolume changed across growing temperatures between thermal origins we calculated the mean biovolume at the stationary phase for all species populations. For this, we used the ow cytometry FSC laser data (i.e. because it was found to be a proxy for mean cell length as explained in Appx. B Supp. Methods S2.1) when populations achieved the stationary phase.

We obtained intrinsic growth rates, r, and densities at carrying capacity, K, by tting data of cell densities over time to a logistic growth curve (equation 1) using the GrowthCurver R package (Sprou ske & Wagner 2016) using R-statistical so ware (R Core Team 2021):

[1] is function gives the number of cells ml -1 (N) at time t, in days, with the parameters of the logistic equation K, N 0 , and r. K is the carrying capacity, maximum value of cells densities at the stationary phase; N 0 is the initial cell densities of the curve and r is the growth rate, i.e., the slope of the exponential phase of the function. Upon nding no di erences in growth among the warm isolates of C. reinhardtii we decided to randomly sampled two replicates from each of the three isolates to yield n=6 for the warm genotype at each temperature. For C. reinhardtii, we tted data from each replicate sample to the logistic growth curve, to get r and K, so n = 6 at each temperature for each thermal genotype. In contrast, for Desmodesmus sp. we used all the 6 data replicates from each isolate to generate a single growth curve. erefore, the number of replicates for r and K was n = 4 for Desmodesmus sp. instead. where rate(T) is the rate at a temperature T (°C), k is the Boltzmann constant with a value of 8.62e-05, E a is the activation energy (in electron volts, eV), i.e., the slope below the optimum, E h is the deactivation energy (eV) at high temperature, i.e. the slope beyond the optimum, t h is the temperature at which enzymes are half suppressed due to high temperatures, r terf is the rate at a standardised temperature, and T ref is a standardisation temperature (°C). In addition, other TPC parameters were obtained from the model, the maximum rate of performance (MRP) and the optimum temperature (Topt). TPCs were t using 'rTPC' , 'nls.multstart' (Pad eld et al. 2021). Bootstrapping using the case resampling method employing 'rTPC' , 'nls.multstart' and 'car' [START_REF] Fox | An R Companion to Applied Regression[END_REF]) packages yielded con dence intervals of TPC parameters.

To test the e ects of temperature on carrying capacity, K, for both algal species we rst corrected carrying capacity values (units: cells/ml) by mean biovolume di erences obtained from manual measurements as explained in chapter 2 (Suppl. Methods Appx. B S2.1). en, to test the e ects of temperature and populations' thermal origin on carrying capacity (biovolume corrected, units: µm 3 /ml), we employed two di erent statistical tests based on parametric assumptions. Because K data of C. reinhardtii comply with parametric assumptions, we run a two-way analysis of variance (ANOVA) test. On the contrary, because K data of Desmodesmus sp. did not conform with parametric assumptions, we run instead a non-parametric permutational ANOVA test, using the aovp function from the 'lmPerm' R-package.

Finally, we evaluated if growing temperature and populations' thermal origin had an e ect on mean biovolume of algal cells at the stationary phase. First, a Mann-Whitney test (i.e., data did not comply with parametric assumptions) con rmed that thermal-origin populations di ered statistically in median biovolume in both algal species (Fig. S3.3) as observed for algal cells analysed in chapter 2 (Appx. B Fig. S2.1). en, to evaluate the e ect of growing temperature and populations' thermal origin on mean biovolume of cells at the stationary phase I run a non-parametric permutational ANOVA test, using the aovp function from the 'lmPerm' R-package (see Appx. B. Fig. S3.2 and table S3.1).

Nutrient uptake

Nitrate removal rates were measured as nitrate concentration removed (mg NO 3 -l -1 h -1 ) from the media by algal cells, following a prolonged starvation of 48 hours and 1 hour of ramp-up acclimation to the testing temperature, at eight temperatures, 14, 17, 20, 23, 26, 29, 32 and 35 °C over the course of 48 hours. Starvation of algae cultures aimed at depleting nitrogen and phosphorus pools within the cell [START_REF] Shirwastav | Adaptability of growth and nutrient uptake potential of Chlorella sorokiniana with variable nutrient loading[END_REF][START_REF] Boonchai | E ect of nutrient starvation on nutrient uptake and extracellular polymeric substance for microalgae cultivation and separation[END_REF] to prevent any possible cellular nutrient storage e ect on nutrient uptake that could mask the responses of the di erent thermal populations. Cells starvation allowed us to evaluate nutrient acquisition closer to basal metabolic conditions, which can remove any initial di erence related to their metabolic state.

We started nitrate experiments with algae coming from the clonal batch cultures in exponential conditions that were subsequently starved over a period of 48 hours prior to the experiments (see Supp. methods in Appx. A. S1.2). Following algal starvation, we prepared the experimental replicates (n = 6 at each temperature for each thermal origin) in 50 ml Erlenmeyer's ask, consisting of 20 ml sample where a small aliquot of starved algae was diluted into COMBO media to get initial set-up densities. For C. reinhardtii samples initial densities were set up to 100,000 cells/ml, and for Desmodesmus sp. 500,000 cells/ml. ese initial densities were based on carrying capacity di erences between species observed during algae maintenance. Control replicates, also 6 per tested temperature, contained just 20 ml of COMBO media. A er setting up the replicates with appropriate densities we sampled 4 ml of well homogenized sample from each replicate, ltered through 0.2 µm lters and stored in a freezer at -20 °C until further chemical analyses. In addition, we collected 150 µl samples from each algal replicate to determine precisely cell densities in each replicate by ow cytometry analyses (as described in Appx. A. S1.3). Initial algal densities were used to obtain per capita rates of nitrate removal. A er 48 hours of exposure to the tested temperatures in full nutrient conditions, we repeated the sampling of 4 ml sample, ltration and storage at -20 °C for each replicate. Nitrate concentrations in initial and nal experiment's samples were analysed using High Performance Ion Chromatography [NF EN ISO 10304-1 (July 1995)] by the Laboratoire Ecologie Fonctionnelle et Environnement at Toulouse University. We divided replicates of each thermal population in two temporal blocks, to remove pseudoreplication at the level of the incubator, and randomized the temperatures across the four experimental weeks, using four incubators at a time.

Nitrate removal rates were measured as the di erence between nitrate concentration at the beginning of the experiment (t 0 ) and a er 48 hours (t 48 ) for each replicate with algae at the tested temperature, and corrected by mean changes in nitrate levels in control replicates of the same temporal block (equation 3):

[3]
where, for each replicate, N t0 was the nitrate concentration at the beginning of the experiment, N t48 the nitrate concentration at the end of the experiment, C t0 -C 48 was the mean nitrate di erence at the beginning and the end of the experiment in the three control replicates from the same temporal block, d was algae density at the beginning of the experiment, and 48 the number of hours the experiment lasted. Because mean cell biovolume of algae populations di ered signi cantly between thermal origins (see Appx. B, Fig. S2.1 and Supp. Methods S2.1), we did a biovolume and cell aggregate correction to each replicate of the nitrate acquisition experiment. We applied this correction dividing the per capita rates of nitrate acquisition by mean cell biovolume in each replicate (calculated from each replicate cytometry FSC-laser data) and multiplying by the mean number of cell aggregates per each recorded event by the cytometer (i.e., 1 for both thermal-origin populations of C. reinhardtii and a 2.8 factor for ambient and 1.47 for warm isolates of Desmodesmus sp., see further explanation in Appx. B Supp. Methods S2.1).

To test the e ects of both temperature and populations' thermal origin on nitrate acquisition, we tted the data of both species to di erent models. First, because C. reinhardtii data followed a unimodal thermal response, we tted the data to a Sharpe-School eld model (equation 2) following the same statistical methods as for growth rates. In contrast, because Desmodesmus sp. data did not conform to a unimodal response (Sharpe-School eld parameters show poor tting, p>0.05), we tted the data to a logarithmic model. For this species, we analysed the e ect of temperature and thermal origin on nutrient acquisition running a logarithmic model in the form of: lm(nitrate acquisistion ~ log(temp) * ermal_origin, data). Finally, I run permutational ANOVA tests for Desmodesmus sp. using the adonis function from the 'vegan' package in R using log(temperature) and thermal origin as main e ects and nitrate acquisition as a response term with 999 permutations. e distance metric used (i.e. weighted Unifrac or Bray-Curtis dissimilarity) did not alter the results so only the results of the Unifrac distance are presented.

Results

Growth rates

ermal performance curves of intrinsic growth rates, r, di ered markedly between ambient-and warm-origin populations for both resource species, showing consistent unimodal trends (See Fig. 3.1, tables 3.1a and 3.3a). Growth rates for the warm genotype of C. reinhardtii were up to 1.5 times larger than those of the ambient origin across temperatures. However, for Desmodesmus sp., even though the warm genotype exhibited larger growth rates than the ambient genotypes, particularly at intermediate temperatures, this di erence was not as large as in C. reinhardtii. For both species, predicted values of activation energy, Ea, were larger for warm isolates. is implies that warm genotypes increased their growth faster than those from ambient origin when temperature increased. In the case of C. reinhardtii, both the thermal optimum and the maximal rate were signi cantly larger (no overlap between con dence intervals) than in the ambient-origin genotype, indicating a full evolutionary adaptation for the warm genotype. On the contrary, the temperature and magnitude of the thermal optimum did not di er across genotypes of Desmodesmus sp. (i.e., overlap in con dence intervals).

Carrying capacity

Carrying capacity declined linearly with increasing temperatures across species regardless of thermal origin a er correcting for biovolume and cell aggregate di erences (Fig. 3.2, table 3.2). e slope of the decline depended upon thermal origin, with opposite patterns between both species. While carrying capacity of the ambient genotype of C. reinhardtii declined faster compared to the warm genotype, for Desmodesmus sp. the decline was instead slightly steeper for the warm-origin genotype, but not signi cantly di erent between genotypes. Moreover, carrying capacity of the warm-origin genotype of C. reinhardtii was generally larger across temperatures, with the exception at low temperatures, i.e., 14 and 17 °C. In contrast, for Desmodesmus sp. carrying capacity was consistently larger for the Table 3.1. Estimated parameters of thermal performance curves and con dence intervals of intrinsic growth rates (a) and nitrate removal rates (b) for ambient (A) and warm (W) origin populations of algae species. Sharpe-School eld model parameters show mean estimated values of activation energy (E a ), deactivation energy (E h ), optimum temperature (T opt ), and maximum rate of performance (MRP) for resources' intrinsic growth rates and nitrate removal rates only for C. reinhardtii. Rates of nitrate acquisition by Desmodesmus sp. are not included here because they did not t a unimodal trend with temperature (see methods in section 3.3). * Units of MRP for growth rates are day -1 and for nitrate removal rates in mg NO 3 -L -1 cell -1 h -1 . ). e solid lines and shaded regions represent the predictions and 95% con dence intervals of the linear models for each genotype. Equations above represent linear models with tting (R 2 ) by thermal origin (see Table 3.2 for statistical details). ambient-origin genotype. ese results reversed when we did not account for biovolume and cell aggregate di erences (see Fig. S3.1 in Appx. C).

Nutrient acquisition

Nitrate removal rate with increasing temperatures had a unimodal trend for C. reinhardtii and a logarithmic pattern (i.e., it better t a logarithmic function) for Desmodesmus sp. regardless of thermal origin (Fig. 3.3, tables 3.1b and 3.3b-d). For C. reinhardtii the nitrate removal response of the warm genotype was consistently larger than in ambient population, with almost a 2-fold increase in maximal rates and a signi cant shi in thermal optimum to warmer temperatures. For Desmodesmus sp., the warm-origin genotype exhibited larger rates of nutrient removal across temperatures by unit of cell volume and aggregate. Here, both the slope and the intercept of nitrate acquisition trends di ered statistically between Desmodesmus sp. thermal genotypes.

Discussion

eory point to the importance of resource growth rate and carrying capacity in determining the changes in consumer and resource densities over time [START_REF] Amarasekare | E ects of temperature on consumer-resource interactions[END_REF][START_REF] Uszko | E ects of warming on predatorprey interactions -a resource-based approach and a theoretical synthesis[END_REF]. erefore, studying the thermal dependencies of these resource traits will be key to improving predictions of consumer-resource dynamics with warming [START_REF] Synodinos | eory of temperaturedependent consumer-resource interactions[END_REF]. What is more, species' responses to changing temperatures can evolve to improve their survival and growth at higher temperatures. Evidence showing the thermal evolution of resource growth rates has been mounting, however responses in carrying capacity remain understudied. Our experiments add to the existing empirical evidence for the unimodal thermal dependence of resource growth rates ( omas et al. 2012;[START_REF] Schlüter | Adaptation of a globally important coccolithophore to ocean warming and acidi cation[END_REF][START_REF] Schaum | Adaptation of phytoplankton to a decade of experimental warming linked to increased photosynthesis[END_REF][START_REF] Schaum | Temperature-driven selection on metabolic traits increases the strength of an algalgrazer interaction in naturally warmed streams[END_REF][START_REF] Aranguren-Gassis | Nitrogen limitation inhibits marine diatom adaptation to high temperatures[END_REF][START_REF] Kottuparambil | Adaptation of Red Sea Phytoplankton to Experimental Warming Increases eir Tolerance to Toxic Metal Exposure[END_REF][START_REF] Liang | Molecular mechanisms of temperature acclimation and adaptation in marine diatoms[END_REF]. Additionally, we observed a linear decrease in carrying capacity with increasing temperature, similar to previous experimental results [START_REF] Bernhardt | Metabolic theory and the temperaturesize rule explain the temperature dependence of population carrying capacity[END_REF].

It has been argued that the thermal dependence of population growth rate is a direct consequence of the thermal dependence of metabolic rates [START_REF] Savage | E ects of body size and temperature on population growth[END_REF]). e metabolic rates in our experiments (reported in chapter 2) were in some way related, but the two physiological parameters di ered somewhat. For C. reinhardtii, growth rates were overall larger across temperatures for the warm-origin genotype. is could result from lower metabolic costs of the warm-origin genotype across temperatures (see chapter 2, Fig. 2.1). On the other hand, growth rates of the warm-origin genotype of Desmodesmus sp. exhibited a vertical shi (thermal optimum remained unchanged), increasing the overall growth compared to the ambient-origin genotype, particularly at intermediate temperatures.

e dependence of nutrient acquisition on changing temperature yielded di erent patterns between the two algae species. e reason for this could lie in the temperatures tested. While for C. reinhardtii the thermal gradient (14 -35 °C) covered the full thermal response for nutrient removal, for Desmodesmus sp., the thermal range was not su cient to characterise the decrease in the response at the higher end. Previous studies on algae species have reported consistent unimodal trends for nitrate acquisition with temperature (Priscu et al. 1989;Reay et al. 1999). Overall, nutrient acquisition increased across temperatures for warm-origin populations across species. e general increase of nutrient acquisition with warming contrasts with the thermal dependence of carrying capacity. In our experiments, the negative relationship between nutrient acquisition and carrying capacity suggests a decrease on e ciency in biomass conversion with warming. Carrying capacity decreased while nutrient acquisition increased with warming across species and populations. For a constant e ciency in biomass conversion across temperatures, the more nutrients are processed, the larger the population numbers should be (K). However, we observed the opposite: more nutrients were required with warming, but population size decreased. erefore, our results indicate that all species became less e cient in converting nutrients into population biomass with increasing temperature (similar to [START_REF] Marañón | Unimodal size scaling of phytoplankton growth and the size dependence of nutrient uptake and use[END_REF][START_REF] Marañón | Nutrient limitation suppresses the temperature dependence of phytoplankton metabolic rates[END_REF][START_REF] Bernhardt | Metabolic theory and the temperaturesize rule explain the temperature dependence of population carrying capacity[END_REF]. For C. reinhardtii nutrient acquisition increased across temperatures for the warm-origin genotype, and carrying capacity decreased but with higher values for the warm-origin population. e higher carrying capacity combined with the larger amounts of nitrates removed from the media suggests that the warm-origin population had higher resource demands by unit of cell volume, or at least that they were more e cient in transforming the nutrients and carbon into biomass. On the other hand, results for growth rates in association with nitrate removal rates, and carrying capacity, for Desmodesmus sp. tell a very di erent story. For this species, nitrate acquisition was faster for the warm-origin genotype, even a er correcting for di erences in biovolume and cell aggregates. However, the e ciency in transforming nitrate appeared to be poor when compared with the ambient genotype, as carrying capacity remained larger for the ambient genotype. In particular, even when growth rates and nitrate acquisition were greater for the warm population of Desmodesmus sp., values of cell volume at carrying capacity were consistently lower. ese results point towards either a maladaptation of this population to warming, or an adaptation at the community level on the warm mesocosms in Dorset that we cannot explain within the scope of our experimental design and analysis (as suggested also in Chapter 2). We acknowledge that the thermal evolutionary responses presented here could be altered if nitrogen was limited (Aranguren-Gassis et al. 2019) such as in oligotrophic conditions or right at the peak of the growing season where nitrogen is actively used. We therefore indicate that thermal responses in resource traits here presented show their optimal potential for thermal adaptations for both investigated species.

Our results have clear implications for trophic structure and dynamics. Warming could arguably lead to hump-shaped consumer-to-resource biomass ratios driven by the humpshaped thermal dependence of resource growth [START_REF] Synodinos | eory of temperaturedependent consumer-resource interactions[END_REF]. erefore, biomass ratios could attain a maximum around the optimal temperature for growth. In terms of the dynamics induced by warming, the implications of our empirical results are more complex. On the one hand, resource growth rate increases the speed of the dynamics [START_REF] Rip | Cross-ecosystem di erences in stability and the principle of energy ux[END_REF] and may even increase the amplitude of oscillations of populations abundances through time (DeLong & Lyon 2020). On the other hand, decreasing carrying capacity should weaken the tendency for oscillations (Rosenzweig 1971;[START_REF] Johnson | A metric for quantifying the oscillatory tendency of consumer-resource interactions[END_REF], thus producing more stable coexistence. e di ering thermal evolution between the two algal species could point to di erent outcomes in their interaction with a consumer. For C. reinhardtii, adaptation led to higher population growth and carrying capacity. is simultaneous increase in both traits could cause oscillations of populations abundances through time with potential negative implications for the survival of both interacting species. On the other hand, the thermal responses of the warm-origin genotype of Desmodesmus sp. reduced the carrying capacity across temperatures. Combined with a higher resource growth rate, this implies that the stability and persistence of interacting consumer-resource pairs could increase with higher growth leading to faster convergence of the dynamics and lower carrying capacity reducing the tendency for oscillations.

Knowledge of how temperature in uences important resource traits is crucial to better understand and predict the e ects of global change on species interactions and community dynamics. Here our results indicate that, although the thermal dependencies of growth, carrying capacity and nutrient acquisition with changing temperatures were (somewhat) consistent across species, thermal evolution altered outcomes for both species. ermal evolution in C. reinhardtii yielded higher growth rates and carrying capacity (as well as nitrate acquisition) across temperatures, which we hypothesised it can lead to destabilising oscillations when interacting with a consumer, compromising their survival. On the contrary, thermal evolution in Desmodesmus sp. resulted in higher growth rates but lower carrying capacity, which we hypothesise that can result in higher stability of the system with fewer oscillations. Although we found evidence for evolutionary adaptation in traits of warm-origin populations of both species (i.e., full evolutionary adaptation for C. reinhardtii, and only in some traits for Desmodesmus sp.), our study would suggest that warming could either increase or reduce the stability (in terms of potential oscillations of populations abundances through time and species persistence) of trophic communities depending on how e ciently nutrient acquisition is transferred into biomass and the thermal evolution trajectory for carrying capacity.

Abstract

Evolution can mediate the responses of species and populations to climate change. Species tness, and thus survival, will largely depend on how species' traits evolve in response to changes in the environment, such as temperature. Evolutionary responses, however, may be constrained by trade-o s determined by interacting selective pressures among traits or potentially across temporal scales because the demands of acute and chronic temperature stress can di er. Ultimately, individual tness is the composite of multiple traits with potential trade-o s and/ or compensatory dynamics occurring across aspects of the life history, making the study of multiple life history components an essential piece to improve understanding about evolutionary responses to climate change. We observed a signi cant increase in acute-i.e., immediate, shortterm-thermal tolerances in response to a c. fourteen-year ambient +4 °C selection treatment. However, long-term exposure to warming reduced life-long survival rates, suggesting a trade-o between acute and chronic heat tolerance. Growth rates, fecundity and generation times did not vary between thermal populations. We found no evidence of increased fecundity that could o set the observed di erences in survival rates over acute and chronic exposure to temperature between populations. Our results suggest that the selection for higher thermal tolerance in acuteextreme whether events, such as heat-waves, come with a long-lasting decrease in survival at extreme low and high temperatures. erefore, these results provide clues on how evolutionary history can alter the response of consumer species to warming at di erent temporal scales.

Introduction

Demographic traits underlie population responses to external factors such as temperature change. For example, survival and fecundity are key determinants of individual tness, and are also important drivers of population traits such as intrinsic growth rate. ese demographic and population traits are thermally dependent. e thermal dependencies of fecundity and survival generally follow unimodal trends across a wide range of temperatures, increasing towards an optimum temperature and decreasing a er that optimum (e.g., [START_REF] Goss | Daphnia development and reproduction: responses to temperature[END_REF][START_REF] Grewal | ermal adaptation of entomopathogenic nematodes: Niche breadth for infection, establishment, and reproduction[END_REF][START_REF] Kingsolver | ermal sensitivity of growth and feeding in Manduca sexta caterpillars[END_REF][START_REF] Angilletta | ermal Adaptation[END_REF][START_REF] Kim | Temperature-dependent fecundity of overwintered Unaspis yanonensis (Hemiptera: Diaspididae) and use of degree-days for the prediction of rst crawler[END_REF][START_REF] Stazione | ermal-speci c patterns of longevity and fecundity in a set of heat-sensitive and heat-resistant genotypes of Drosophila melanogaster[END_REF]. Di erences in the thermal dependencies of such parameters that underlie population dynamics can strongly modify the responses of consumer-resource dynamics under warming. Because species interactions are key for the ow of energy and materials in food webs, the study of thermal dependencies of species interactions is vital to better predict the e ects of climate warming for communities and ecosystems. Additionally, these same demographic traits are potentially under directional selection in response to warming, such that the temperature dependency of the traits can evolve in response to warming. Exposure to extremes and high temperatures can impose selection pressure on organisms and drive the evolution of physiological capacities [START_REF] Logan | Natural selection on thermal performance in a novel thermal environment[END_REF][START_REF] Buckley | How extreme temperatures impact organisms and the evolution of their thermal tolerance[END_REF][START_REF] Diamond | Evolution of thermal tolerance and its tness consequences: parallel and non-parallel responses to urban heat islands across three cities[END_REF]. erefore, the exploration of thermal tolerances of survival and fecundity of consumer populations -and their evolution-is essential to improve predictions of species interactions under warming.

While extreme weather events such as heat waves increase tolerance to high temperatures [START_REF] Bozinovic | e mean and variance of environmental temperature interact to determine physiological tolerance and tness[END_REF][START_REF] Estay | Beyond average: An experimental test of temperature variability on the population dynamics of Tribolium confusum[END_REF][START_REF] Geerts | Rapid evolution of thermal tolerance in the water ea Daphnia[END_REF], they may result in reduced energy allocation to other functions such as reproduction [START_REF] Ragland | Evolution of thermotolerance in seasonal environments: e e ects of annual temperature variation and life-history timing in Wyeomyia smithii[END_REF][START_REF] Roitberg | Cold snaps, heatwaves, and arthropod growth[END_REF][START_REF] Koussoroplis | Understanding and predicting physiological performance of organisms in uctuating and multifactorial environments[END_REF]. Indeed, previous research has reported that prolonged exposure to extreme temperatures can decrease survival, fertility, and growth rates [START_REF] Folguera | An experimental test of the role of environmental temperature variability on ectotherm molecular, physiological and life-history traits: Implications for global warming[END_REF][START_REF] Sikkink | Rapid evolution of Phenotypic plasticity and shi ing thresholds of genetic assimilation in the nematode Caenorhabditis remanei[END_REF][START_REF] Sales | Experimental heatwaves compromise sperm function and cause transgenerational damage in a model insect[END_REF][START_REF] Cavieres | Transgenerational and within-generation plasticity shape thermal performance curves[END_REF]. In many cases, improvement in one trait can be realized at the expense of reduced performance in a second trait, yielding a trade-o . Some of the most recognisable include those where evolved antipredator defences that allow higher survival of these individuals cause demographic costs in population growth rates [START_REF] Riessen | Demographic Costs of Antipredator Defenses in Daphnia[END_REF][START_REF] Kasada | Form of an evolutionary tradeo a ects ecoevolutionary dynamics in a predator-prey system[END_REF][START_REF] Ehrlich | e shape of a defense-growth trade-o governs seasonal trait dynamics in natural phytoplankton[END_REF]. Another example is the well-known competition-colonization/dispersal trade-o where species or genotypes that have particularly good competition abilities generally show low dispersal or colonization capacities [START_REF] Hanski | Coexistence in a Patchy Environment: ree Species of Daphnia in Rock Pools[END_REF][START_REF] Amarasekare | Competitive coexistence in spatially structured environments: A synthesis[END_REF][START_REF] Cadotte | On testing the competition-colonization trade-o in a multispecies assemblage[END_REF][START_REF] Liang | Molecular mechanisms of temperature acclimation and adaptation in marine diatoms[END_REF]. Trait trade-o s have also been reported when thermal evolution occurs. For example, evolution in response to thermal selection on growth rates resulted in lowered survival rates in species of sh or lizards [START_REF] Present | Physiological Basis of Latitudinal Growth Di erences in Menidia menidia: Variation in Consumption or E ciency?[END_REF][START_REF] Billerbeck | Adaptive variation in energy acquisition and allocation among latitudinal populations of the Atlantic silverside[END_REF][START_REF] Lankford | Evolution of intrinsic growth and energy acquisition rates. II. Trade-o s with vulnerability to predation in Menidia menidia[END_REF][START_REF] Bestion | Live Fast, Die Young: Experimental Evidence of Population Extinction Risk due to Climate Change[END_REF], while thermal selection for larger adult sizes in Drosophila traded o with reduced survival in larval stages [START_REF] Bochdanovits | Experimental evolution in Drosophila melanogaster: Interaction of temperature and food quality selection regimes[END_REF].

Trait trade-o s are not the only kind of trade-o s that can occur, however, especially when we consider environmental change-such as habitat warming-not previously experienced by species. In particular, a single trait can show a trade-o across time-scales. While these temporal trade-o s are less studied than trait trade-o s, they may nonetheless be particularly relevant for populations that are evolving in response to habitat warming. Habitat warming actually encapsulates multiple related selection pressures. In particular, organisms can evolve in response to chronic habitat warming (i.e., sustained increased mean temperature), but habitat warming also involves exposure to extreme weather events, where temperatures may rise even higher over short time scales (i.e., acute exposure), increasing the variability in temperatures experienced by organisms. us, the trade-o between acute and chronic heat tolerance can occur when acute and chronic exposure may require a di erent suites of traits [START_REF] Rezende | Tolerance landscapes in thermal ecology[END_REF]. For instance, evolution to increase performance near the thermal optimum may occur in response to the anticipated moderate increases to chronic temperature, but this can come at the expense of tolerance of extreme weather events (e.g., heat waves), where organisms experience, and must survive, highly stressful conditions, but only for short periods of exposure. is tradeo can emerge as a result of genetic di erences of heat-shock proteins that emerge as a result of chronic and acute exposure to temperature [START_REF] Yousey | Resurrected 'ancient' Daphnia genotypes show reduced thermal stress tolerance compared to modern descendants[END_REF]. For instance, laboratory work with Drosophila melanogaster reported that populations that evolved at the highest temperature better survived heat shock events at the expense of the acclimation response and had signi cant divergence at three chromosomes compared to populations evolved at more moderate temperatures [START_REF] Cavicchi | Chromosomal Analysis of Heat-Shock Tolerance in Drosophila melanogaster Evolving at Di erent Temperatures in the[END_REF]. Trade-o s are not only reported in laboratory selection experiments. For example, pond snails from a warm geothermal spring exhibited tolerance to higher chronic temperature at the expense of lower acute thermal tolerance compared to coldorigin populations [START_REF] Johansson | Maximum thermal tolerance trades o with chronic tolerance of high temperature in contrasting thermal populations of Radix balthica[END_REF]. Also, species of porcelain crabs that evolved the greatest tolerance to high temperatures in nature did so at the expense of acclimation capacity at the upper thermal limit [START_REF] Stillman | Acclimation capacity underlies susceptibility to climate change[END_REF]. Additional empirical work has demonstrated that genotypes that have evolved higher thermal tolerance to either acute or chronic temperature exposure exhibited worse survival at the opposing temporal scale compared to unevolved genotypes [START_REF] Sgrò | A comprehensive assessment of geographic variation in heat tolerance and hardening capacity in populations of Drosophila melanogaster from Eastern Australia[END_REF][START_REF] Castañeda | Heat tolerance in Drosophila subobscura along a latitudinal gradient: Contrasting patterns between plastic and genetic responses[END_REF]. us, temporal trade-o s may be important for a variety of organisms responding to climate warming.

Ultimately, it is the combination, or balance, of traits in a given environment that determines individual tness. us, we can consider compensatory interactions among traits as the ip side to trade-o s. As an example of this phenomenon, life history strategies are frequently governed by relatively high survival and low fecundity on the one hand, or low initial survival, but high adult fecundity on the other. In the context of evolutionary responses, we might therefore expect that a signi cant loss of performance in one trait, such as survival, must be o set by a compensatory gain in another trait, such as fecundity, to maintain tness and prevent extinctions in the face of environmental change.

In light of ongoing climate warming, it is therefore of vital importance to increase our mechanistic understanding of temperature e ects on consumer demographic parameters, as well as on the evolutionary response changes to these parameters. An in-depth study of consumer demographic traits can help to unravel the e ects of warming on trade-o s in demographic parameters and identify if there are compensatory responses that can account for such trade-o s. In this study we had three aims. First, we investigated the e ects of temperature on di erent demographic traits for two populations of a consumer species, Daphnia pulex, that di er in their multi-generational thermal histories. Next, we examined the e ects of temperature on consumers' survival rates at two contrasting temporal scales (i.e., acute versus life-long exposures to temperature) for these same two populations. Finally, we evaluated whether changes observed in demographic traits (survival and fecundity) exhibited a compensatory relationship in the unevolved and evolved populations of the consumer across temperatures. To do so, we measured survival rates of two contrasting thermal populations of the consumer D. pulex under acute (i.e., c. 1.5 -2.5 hours) and life-time exposures (i.e., up to 100 days) to temperature. To evaluate possible compensatory dynamics and increase our understanding of responses in survival rates to temperature across temporal scales, we measured di erent demographic traits such as intrinsic growth rate, net reproductive rate (i.e., accumulated fecundity), body size, survival, and generation time for each thermal population. We focused on these traits because they have been reported to be a ected by temperature in zooplankton species [START_REF] Mclaren | E ects of Temperature on Growth of Zooplankton, and the Adaptive Value of Vertical Migration[END_REF][START_REF] Goss | Daphnia development and reproduction: responses to temperature[END_REF][START_REF] Ranta | Growth, size and shape of Daphnia longispina, D. magna and D. Pulex[END_REF][START_REF] Yampolsky | Adaptive phenotypic plasticity and local adaptation for temperature tolerance in freshwater zooplankton[END_REF][START_REF] Bom M | Warming alters the metabolic rates and life-history parameters of Ceriodaphnia silvestrii (Cladocera)[END_REF].

Materials and methods

We isolated two contrasting thermal populations of the water ea, Daphnia pulex, from the long-term mesocosms facility at the FBA River Laboratory, Dorset (as explained in the methods of chapter 2, section 2.3). From each thermal population, we isolated 5 individual parthenogenetic females which yielded 10 clonal lineages in total. All 10 clonal lineages were maintained individually in batch cultures in laboratory incubators since isolation in November 2019 in a modi ed nutrient-free version of COMBO freshwater medium [START_REF] Kilham | COMBO: A de ned freshwater culture medium for algae and zooplankton[END_REF] to avoid bacterial overgrowth. We initially maintained the 4°C di erence between ambient (at 18°C) and warm (at 22°C) populations. Since March 2020, cultures have grown in common garden conditions at 20°C, and 12:12 dark:light photoperiod regime for successive experiments. Daphnia populations initially consumed a mixture of algae species, Chlamydomonas reinhardtii, Desmodesmus sp., and Tetradesmus obliquus, also originally isolated from the same ponds as the Daphnia (i.e. ambient Daphnia were fed with algae isolated from ambient ponds and vice We isolated two contrasting thermal populations of Daphnia pulex from a long-running study of experimental warming in arti cial ponds in Dorset, UK, that experienced up to 14 years of either ambient or ambient +4 °C conditions. We cultured them in common garden conditions in incubators for more than 15 generations and then exposed them to either acute (i.e., short-term, c. 1.5-2.5 h) or lifetime (i.e., long-term, up to 100 days) exposure to temperature and measured survival rates. In addition, we also measured additional demographic traits such as intrinsic growth rates, net reproductive rates and generation times for both thermal populations. versa). However, since January 2021, all Daphnia have been fed a common algae food source, Ankistrodesmus sp., to remove any possible e ect from food quality [START_REF] Kilham | E ects of algal food quality on fecundity and population growth rates of Daphnia[END_REF]). e population of Ankistrodesmus sp. algae originated from Sciento UK supply company and grew in aerated COMBO media in identical common garden conditions.

We used life table experiments to determine the long-term e ects of four growing temperatures, 14, 18, 20, 22 C, on survivorship and other demographic traits (i.e., individual growth rates, net reproductive rate, generation times and maximum size at maturity) of both thermal contrasting populations of D. pulex. In addition, we evaluated survival rates of both thermal populations of Daphnia to acute exposure to temperature (i.e., 1.5 -2.5 h) over a wide gradient of temperatures (14, 18, 22, 26, 30, 32, 34, 36°C), see Fig. S4.1.

Measurements of demographic traits and survival in life-time exposure to temperature

Life table experiments started with neonate daphnids, i.e., less than 24-hours old, placed individually in 15 ml glass vials with 10 ml of a modi ed nutrient-free version of COMBO medium and Ankistrodesmus sp. as a food source in excess, about 2.5x10 6 cells/ml, so 3.6x10 5 cells/ml per day (based upon previous pilot experiments). We place the neonates in Panasonic incubators at either 14, 18, 20 or 22 C in 12:12 dark-light photoperiod without additional aeration. Initially, to mitigate for unexpected mortalities that could be related to individual's manipulation, we employed 12 individual neonates from each clonal linage. We measured initial body length of each neonate using a digital stereo microscope (Leica S9i). For each clonal linage we waited to observe the rst 6 individuals to produce eggs of the original 12, which then became the subjects of the subsequent experiments (i.e., n = 6 for each clonal linage, and therefore n = 30 for each of the ambient and warm adapted populations in each incubator). Every day, from Monday to Saturday, the experimental daphnids were checked for survival and the number of o spring produced (which were discarded a er counting). Once per week we cleaned and replaced the COMBO medium and Ankistrodesmus sp. by transferring daphnids into new sterile tubes. is procedure ensured that food was always abundant for the Daphnia and removed any build-up of waste metabolic products [START_REF] Kilham | E ects of algal food quality on fecundity and population growth rates of Daphnia[END_REF]. From Mondays to Fridays, juveniles produced were removed from the vial and counted. On Saturdays, juveniles were only estimated visually but not removed from the tubes. Additionally, to assure that algae was always available in suspension, all tubes were daily agitated by hand, a er which we always veri ed that the daphnid remained within the liquid medium. When animals were found dead, their nal length was recorded using a digital stereo microscope.

Replication across incubators was unfeasible for this experiment due to the size and length of the experiment. erefore, each week we rotated temperature treatments among incubators to avoid possible incubator e ects. Additionally, we rotated the test tube racks inside the incubators daily to account for possible di erences in light, temperature, and humidity that could occur based upon position within an incubator. e animals of each thermal population were treated as a cohort for which age-speci c survival (l x ) and mean age-speci c fecundity, i.e., average number of o spring per female (m x ), were calculated [START_REF] Pianka | Evolutionary Ecology[END_REF]. From this, we were able to calculate other important traits for the two thermal populations such as adjusted fecundity (l x m x ), as well as net reproductive rate, R 0 , and generation time (G). Net reproductive rate, R 0 , represents the accumulated adjusted fecundity, or the number of o spring produced by a female during its lifespan (equation 1, units: individuals).

[1] Generation time, G, represents the average age of all of the parents of o spring produced by a single cohort (equation 2, units: day):

[2] Finally, based on the previous calculated parameters, the intrinsic growth rate, r (units: day -1 ) for each cohort was estimated iteratively from the Euler-equation (equation 3):

[3]

Because o spring numbers were fully counted from Monday to Friday, but not Saturdays or Sundays (i.e., neonates that hatched a er the checks on Friday were not counted until Monday, reducing weekend resolution), we rst binned several days together (for tractability) before calculating fecundity (m x ). Although this method reduced temporal resolution, it was a necessary compromise for increased data reliability. us, instead of counting time (x) by day, one bin grouped data from Tuesday to ursday (yielding a mean for 3 days), and a second bin grouped data from Friday to Monday (similarly yielding a mean across 4 days). Finally, once a daphnid died, we measured its body size (i.e. from top of head to base of tail spine) using a stereo-binocular microscope (Leica S9i) which represented the size at maturity (in mm).

We conducted all statistical analyses using the R-statistical so ware, R version 4.0.3 (R Core Team 2021). First, we plotted clone survivorship grouped by thermal origin and temperature treatment with the survminer R-package. en, we compared the curves between thermal treatments using the non-parametric Kaplan-Meier estimator present in the survival package. A er verifying data complied with parametric assumptions of normality and equal variances, two-way analysis of variance (ANOVA) evaluated the e ects of temperature, Daphnia thermal origin, and their interaction on net reproductive rates and generation times independently. To verify at which temperature the ambient and warm populations di ered in demographic traits, we used pair-wise comparisons at each growing temperature, running a contrast analysis with the emmeans and pairs functions from the `emmeans` package [START_REF] Lenth | emmeans: Estimated Marginal Means, aka Least-Squares Means[END_REF]. Because the individual growth rate data were non-normally distributed, a permutational Analysis of Variance (Per-ANOVA) using the adonis function of the `vegan` package [START_REF] Oksanen | vegan: Community Ecology Package[END_REF] tested the e ects of temperature and population thermal origin of Daphnia on growth rates. Finally, we tested the e ect of growth temperatures and thermal origin on nal Daphnia body sizes using a permutational ANOVA. And then, we used a t-test (normality and homoscedasticity), a Welch's t-test (normality and heteroscedasticity) or a non-parametric Mann-Whitney test to evaluate di erences in means or medians of Daphnia body sizes at death at each growth temperature (i.e., depending on the data structure from each growth temperature).

Measurements of survival rates in acute exposures to temperature

We calculated the mean survival rates of D. pulex a er acute exposure to temperature by pooling the survivorship data of individuals used for both the ingestion and respiration experiments described in Chapter 2 (section 2.3). In each of these experiments, we used 5 starved adult daphnids from each thermal population (each one corresponding to one of the clonal populations) in each replicate (n=6) and exposed them to a short period of time to the assay temperatures. While for respiration experiment replicates were exposed over 1.5 hours at each assay temperature, the time of exposure was 2.5 hours for ingestion experiments.

e mean survival of the individuals contained in each replicate quanti ed survival (l x ). We estimated the temperature causing 50% mortality (LT50) during the course of the experiments and the slope of survival decline with temperature [START_REF] Jørgensen | Neural dysfunction correlates with heat coma and CTmax in Drosophila but does not set the boundaries for heat stress survival[END_REF]) by tting survival rates with temperature to a non-linear least-squares model, using a negative logistic curve (equation 4) with the nls()-function:

[4]
where T is the temperature in C, a is the slope of the decline, and b is the estimate of LT50. e 95% con dence intervals were calculated for each survival curve around the estimated LT50 using con nt2() function from the nlstools R-package [START_REF] Baty | A toolbox for nonlinear regression in R: e package nlstools[END_REF]. We considered survival curves with non-overlapping con dence intervals to be signi cantly di erent.

Results

Evolution of survival exhibits a temporal trade-off

Overall, temperature had a signi cant and consistent e ect on survival of D. pulex ( Figs 4.2, 4.3, S4.1 andTable 4.1). Maximum survival rates (i.e., life-span) declined from c. 100 days at 14 °C to c. 45 days at 26 °C. Comparatively, when daphnids were instead exposed to acute thermal stress (i.e., for a maximum of 2.5 hours), they survived at higher temperatures, up to 35-36°C. Background thermal histories of the Daphnia populations had a signi cant e ect on survival rates for long-term and acute exposure to temperature. Speci cally, ambient-origin daphnids exhibited higher life-time survival rates than warm-origin individuals at both extreme low and high temperatures (14 and 26 °C), no di erence in survival at 18 °C and lower survival at 22 °C. With acute thermal exposure, warm-origin daphnids showed consistently higher thermal tolerance (i.e., higher LT50 temperature and weaker slope of the decline in survival with no overlap between con dence intervals) at extreme high temperatures compared to the ambient-origin population. ese di erences in survival started to di er between thermal origin populations from c. 33 °C. Table 4.1. Summary statistics of survival curves for two contrasting thermal populations of D. pulex exposed to acute thermal conditions. Survival trends are calculated using a negative logistic model where 'a' represents the slope of the decline and 'b' the estimate of LT50 (i.e., the temperature at which half of the population died). Con dence intervals (ci) of survival curve parameters (a, b) are given as the low and high values of the 95% con dence. Survival curves with non-overlapping con dence intervals are considered as signi cantly di erent.

Fecundity, individual growth rates, and generation times fail to compensate for reduced lifetime survivorship at temperature extremes

Growth rates of D. pulex increased exponentially with warming for both thermal-origin populations (Fig. 4.4, Tables 4.2). Speci cally, we observed a vefold increase in growth rates at 26 °C compared to 14 °C. Net reproductive rates (i.e., the accumulated fecundity during a lifespan), however, showed unimodal trends, with the maximum value occurring at 22 °C, with about 2-3 times more neonates produced compared to temperature extremes (Fig. 4.5 and Tables 4.3, 4.4). Overall, generation times were twice as long at the cold extreme of 14 °C compared to the warm extreme of 26 °C (Fig. 4.6, Tables 4.3 and 4.4). Ambient-origin and warm-origin daphnids did not di er signi cantly in any of these three traits.

Discussion

Evolution in response to climate warming can involve selection for exposure to stressful temperatures that di er in duration (e.g., acute vs. chronic exposure) as well as on multiple potentially interacting traits. Here we examined the e ects of hundreds of generations of growth in experimentally warmed environments compared to ambient temperature conditions to evaluate the potential for trade-o s among both traits and time scales that a ect individual tness when populations evolve in response to habitat warming. Increased temperature variability, especially at the high end of the range, such as extreme temperature events, represents a potentially strong selective pressure. Nonetheless, increased mean temperature is also a strong selective pressure. us, we need to consider responses to both extreme temperatures and increasing mean temperature for a more comprehensive understanding of the e ects of climate change on species.

We showed a signi cant increase in acute-i.e., short-term-thermal tolerances in response to a c. fourteen-year ambient +4 °C selection treatment. is suggests that the warm-origin population has higher persistence than the ambient-origin population in acute extreme high temperature conditions, such as heat-wave events, which are becoming more common with increasing mean global temperatures [START_REF] Meehl | More Intense, More Frequent, and Longer Lasting Heat Waves in the 21st Century[END_REF][START_REF] Stott | How climate change a ects extreme weather events[END_REF][START_REF] Woodward | e e ects of climatic uctuations and extreme events on running water ecosystems[END_REF]. In contrast, we found that chronic exposure-i.e., longterm-to warming reduced survival rates, suggesting a trade-o between acute and chronic heat tolerance. While chronic exposure to temperatures may have detrimental e ects on survival, acute exposure to temperatures above critical thermal limits, as those experience during heat-waves, may bene t organisms by improving their upper thermal limits driven by thermal selection [START_REF] Macisaac | Inter-and Intraspeci c Variation in Acute ermal Tolerance of Daphnia[END_REF][START_REF] Geerts | Heat tolerance and its evolutionary potential along a latitudinal gradient in Daphnia magna[END_REF][START_REF] Geerts | Rapid evolution of thermal tolerance in the water ea Daphnia[END_REF][START_REF] Vasseur | Increased temperature variation poses a greater risk to species than climate warming[END_REF][START_REF] Yousey | Resurrected 'ancient' Daphnia genotypes show reduced thermal stress tolerance compared to modern descendants[END_REF]. In cases where environmental temperatures exceed critical limits, acute and chronic exposure usually yield di erent e ects on performance and survival [START_REF] Vasseur | Increased temperature variation poses a greater risk to species than climate warming[END_REF] as observed in our results. For instance, several studies have previously demonstrated rapid responses of the thermal sensitivity of organisms to temperature (reviewed in [START_REF] Parsons | Evolutionary Rates under Environmental Stress[END_REF][START_REF] Huey | Evolution of thermal sensitivity of ectotherm performance[END_REF][START_REF] Angilletta | e evolution of thermal physiology in ectotherms[END_REF].

ermal selection to higher growing temperature increased the survival at extreme high temperatures in D. melanogaster (e.g., [START_REF] Huey | ermal sensitivity of Drosophila melanogaster responds rapidly to laboratory natural selection[END_REF][START_REF] Cavicchi | Chromosomal Analysis of Heat-Shock Tolerance in Drosophila melanogaster Evolving at Di erent Temperatures in the[END_REF][START_REF] Sgrò | A comprehensive assessment of geographic variation in heat tolerance and hardening capacity in populations of Drosophila melanogaster from Eastern Australia[END_REF], crustaceans (Stillman & Somero 2000;[START_REF] Stillman | Acclimation capacity underlies susceptibility to climate change[END_REF]), a damsel y [START_REF] Carbonell | ermal evolution of life history and heat tolerance during range expansions toward warmer and cooler regions[END_REF], and in di erent Daphnia species [START_REF] Geerts | Rapid evolution of thermal tolerance in the water ea Daphnia[END_REF][START_REF] Yousey | Resurrected 'ancient' Daphnia genotypes show reduced thermal stress tolerance compared to modern descendants[END_REF]. For instance, individuals from a southern population of a crustacean tended to have higher thermal tolerances in acute exposures to temperature compared to a northern population (i.e., grown at lower temperatures) [START_REF] Gaston | Do upper thermal tolerances di er in geographically separated populations of the beach ea Orchestia gammarellus (Crustacea: Amphipoda)?[END_REF]. A positive relationship between acute heat knockdown temperature and latitude (i.e., higher values at lower latitudes) was observed in D. melanogaster from Australia [START_REF] Sgrò | A comprehensive assessment of geographic variation in heat tolerance and hardening capacity in populations of Drosophila melanogaster from Eastern Australia[END_REF]), however, populations from higher latitudes also had decreased chronic heat tolerance. e authors suggested that the extreme environmental temperatures reached the upper thermal limit estimated in their assay (around 41.5 °C), which represents a strong selective force. In general, studies using space-for-time substitutions to examine di erences in thermal evolution (i.e., using populations at di erent latitudes) have some important distinctions from our work where we examine the evolution occurring as a result of experimentally imposed warming. Tropical populations tend to live closer to their thermal optimum and have narrower thermal niches than temperate populations [START_REF] Perez | ermal trouble in the tropics[END_REF]. erefore, their ability to respond to increased variability is limited. e so-called "resurrection" experiments can provide us with a means to compare historical and recent populations, providing a record of organisms' change through time. An experiment using Daphnia magna showed a genetic increase in critical thermal maximum a er selection to 4 °C of experimentally imposed warming mirrored an increase in thermal tolerance in genotypes of natural populations from the 1960s and 2000s hatched from lake sediments [START_REF] Geerts | Rapid evolution of thermal tolerance in the water ea Daphnia[END_REF]. However, temporal trade-o s are not universally identi ed. For example, modern clones of Daphnia pulicaria evolved higher heat tolerance compared to historical populations [START_REF] Yousey | Resurrected 'ancient' Daphnia genotypes show reduced thermal stress tolerance compared to modern descendants[END_REF], but there was no di erence between acute and chronic exposures to temperature. Finally, in a recent study, a trade-o between acute and chronic exposure to temperature was reported, but in the opposite direction than in our experiments [START_REF] Johansson | Maximum thermal tolerance trades o with chronic tolerance of high temperature in contrasting thermal populations of Radix balthica[END_REF]). e authors found that populations of pond snails from a warm geothermal spring had higher chronic tolerance to thermal stress, but lower tolerance to extreme high temperatures in acute conditions. e di erence with our study may depend upon the temporal scale of the temperature uctuation. Our experimental communities experience daily and season temporal variability. In the system examined by [START_REF] Johansson | Maximum thermal tolerance trades o with chronic tolerance of high temperature in contrasting thermal populations of Radix balthica[END_REF], however, populations have experienced sustained temperatures over time, where organisms hardly ever experience acute thermal extremes (i.e., geothermal springs have greater temperature stability over time). Nonetheless, both studies support the idea of a trade-o between acute and chronic tolerance of high temperatures.

Classic trade-o theory (reviewed in [START_REF] Stearns | Trade-O s in Life-History Evolution[END_REF][START_REF] Anderson | Evaluating the tradeo between o spring number and survivorship across shes, amphibians, reptiles and mammals[END_REF][START_REF] Willi | A review on trade-o s at the warm and cold ends of geographical distributions[END_REF] would suggest that either there must be some compensation that occurs that sustains population growth (at least at replacement levels), or perhaps that D. pulex rarely encounters sustained temperature extremes in their ponds of origin in Dorset. Under laboratory conditions, survival rates started diverging between thermal origins at extreme temperatures when sustained-i.e., more than 15 days at 26 °C and 25 days at 14 °C. When examining demographic traits at the life-time scale, we saw no evidence of compensation between survivorship and fecundity in our experiments. In general, we found no di erence in net reproductive rates, intrinsic growth rate, or generation time between populations di ering in thermal origin. However, we observed consistent patterns with increasing temperatures. Speci cally, we found that intrinsic growth rates increased exponentially with temperature, net reproductive rates followed a unimodal response peaking at 22 °C degrees, and generation time decreased with temperature. Our results of thermal dependencies agreed with general thermal trends for these life-history parameters [START_REF] Gillooly | E ect of body size and temperature on generation time in zooplankton[END_REF][START_REF] Gillooly | E ects of Size and Temperature on Metabolic Rate[END_REF][START_REF] Cavalheri | Rapid evolution of thermal plasticity in mountain lake Daphnia populations[END_REF]. While our results seem to suggested that the reduced survival at the temperature extremes could contribute to faster extinctions compared to the ambient-origin populations, D. pulex populations have survived in these warmed experimental ponds for 13+ years. It therefore does not appear that they are likely to go extinct due to this apparently negative evolutionary response (i.e., at the population level). e typical temperatures experienced in Dorset, UK may make this outcome (i.e., sustained mean temperature around 26 °C for longer than 2 weeks) less likely, thereby reducing the apparent tness cost of the evolutionary response. Additionally, daphnids may escape extreme temperature events with dormant resting eggs produced through sexual reproduction. is is an aspect of fecundity that we did not examine here, so we are not able to evaluate the extent to which resting egg production can compensate for the observed reduced survivorship. In the literature, resting eggs in Daphnia and other zooplankters have been reported to increase with temperature as a way to cope with challenging temperatures [START_REF] Holm | Resting eggs in free living marine and estuarine copepods[END_REF][START_REF] Issa | Population dynamics and resting egg production in Daphnia: Interactive e ects of mercury, population density and temperature[END_REF]. ese resting eggs can survive stressful environmental conditions over long periods of time, and are vital to maintain long-term tness in these species [START_REF] Cáceres | How Long to Rest : e Ecology of Optimal Dormancy and Environmental Constraint[END_REF][START_REF] Gerber | Daphnia invest in sexual reproduction when its relative costs are reduced[END_REF].

While considering solely the life-time demographic parameters did not reveal a clear tness advantage to the observed evolutionary response, expanding our focus to include acute responses added clarity to the picture.

e improved survival of warm-origin daphnids to acute thermal stress suggests the possibility of a trade-o in survival across time scales. It is logical to think that survival in acute thermal stress would be selected for more strongly in the warm experimental ponds. For both treatments, during warm periods, such as in summer, increasing temperatures would expose communities to stressful conditions, in some cases surpassing critical limits. However, as treatments di ered in 4 °C, extreme high temperature events that expose populations to lethal or sub-lethal conditions were likely more frequent for experimentally warmed communities than for communities from ambient origin [START_REF] Vasseur | Increased temperature variation poses a greater risk to species than climate warming[END_REF]. us, selection may be strong enough for increased survival during acute exposure, that it outweighs the negative consequences at the longerterm chronic scale, especially when those negative e ects are con ned to temperature extremes and may additionally be partially compensated for by the production of resting eggs. Nonetheless, our results suggest that in ectothermic species lacking such evolutionary strategies (i.e., the production of dormant resting eggs), trade-o s that favour survival during extreme temperature events such as heat-waves at the expense of life-time survival could have the potential to result in signi cant negative impacts at the populationlevel (e.g., [START_REF] Fischer | Strong negative e ects of simulated heat waves in a tropical butter[END_REF]. We therefore suggest that strong selection for acute exposure that comes with unavoidable trade-o s at longer time scales could represent an under-recognized evolutionary trap for populations responding to climate warming, especially those without resting stages that can rescue populations following extreme temperature events.

Our work demonstrates that although thermal tolerance can evolve in response to mean experience temperatures in populations, variability in extreme high temperature may bring associated trade-o s across temporal scales (i.e., acute vs. chronic exposures). ese results arise because increased thermal tolerance in warm-origin populations for acute heat events can trade o with lower survival in chronic conditions to extreme high and warm conditions. In our experiments, however, we did not nd any compensatory e ects in fecundity, or any other trait, that could explain the di erences in survival between thermal populations. We may have missed this because the traits measured were not the appropriate ones to trace the di erence in survival such as resting egg production. An additional point to note regarding the decreased persistence of warm-origin consumer populations is the potential e ect on interacting resource species. Communities with warm-origin consumers could lead to a reduced e ect on resource species, compared to communities with coldevolved daphnids. In such a case, mortalities of consumers would release resource species from consumers' control, leading to higher biomass densities of resource species. is suggests that evolution of consumers in response to increased temperatures could weaken interactions between consumers and resources.

In general, our results highlight the importance of evaluating di erent temporal scales of exposure to thermal environment and stress for driving evolution. It is of vital importance that we increase understanding on these evolutionary responses to interpret the real environmental drivers, not only increased temperature means but also variability of extreme high temperatures, behind observed long term consequences of warming for populations and communities.

General discussion

Climatic warming will impact ecosystems in ways we are yet to fully understand. Our understanding is hindered by the complexity of the problem, as di erent species' physiological traits and ecological processes show di erent sensitivities to changing temperatures. In addition, species traits can evolve in response to warming when populations are, for instance, exposed to higher and maintained temperature conditions. A more mechanistic understanding is key to improve our knowledge and increase the predictive power on the ecological and evolutionary e ects of warming on species and trophic interactions. e main objective of this thesis has been to understand the ecological and evolutionary e ects of temperature on key traits of both resource and consumer species as well as on their interactions, to help us to better predict future scenarios of global warming in trophic interactions and community dynamics. In this discussion, I rst summarize the main and novel ndings of the chapters providing information on the thermal dependencies and evolutionary responses of important traits of consumers and resources.

en, I present general contributions of this thesis, discussing and synthesizing di erent aspects contained in the four chapters and nally, I brie y present an open question derived from my main ndings to advance towards a deeper understanding of the e ects of temperature on species, species interactions and how to scale this to multi-species systems.

Summary of results

Consumer-resource dynamics depend on multiple processes.

is thesis aimed at disentangling the ecological and evolutionary responses of these multiple processes to increasing temperatures. Ecological theory on consumer-resource interactions predicts population dynamics following simplifying assumptions.

ere are multiple ways to summarize the results from the di erent chapters. Although I followed an experimental approach, ecological theory was a big motivation and can be used to synthesize my results.

Here, I use thermal dependencies of parameters consider by theory for models of consumerresource dynamics as depicted in where C and R are the consumer and resource species biomass densities, respectively, at time t; e represents the consumer assimilation e ciency and f represents the functional response between consumption rate and resource densities. e parameter m corresponds to consumer metabolic costs, which can be considered as a biomass loss term or individual mortalities, depending on the selected units. r is the intrinsic growth rate of the resource population and K is the resource density at carrying capacity.

In chapters 1 and 2 I showed that the response of interaction strength (i.e., representing the linear functional response f between a consumer c and a resource r when assuming a Lotka-Volterra model where f = a rc ) to temperature increase was context-dependent. Warming increased interaction strength when the consumer fed on one resource but decreased interaction strength when feeding on the other. Such context-dependency was explained and predicted by di erences in the thermal sensitivities of species traits related to energy gain and loss for each interacting partner. Interaction strength decreased with temperature when the resources' energetic balance (i.e., the ratio of energy gain to energy loss) increased while that of the consumer declined. However, when the energetic balances of both interacting species declined with temperature, interaction strength increased. In chapter 2, I found that the temperaturedependence of interaction strength remained unchanged when the energetic balance of both interacting species evolved simultaneously. However, when the energetic balance of the resource and the consumer evolved in a di erent manner, the trend of interaction strength changed markedly and increased in magnitude following thermal evolution.

In chapter 3, I showed that resource intrinsic growth rate, r, and resource carrying capacity, K, followed unimodal and linear declining trends with temperature respectively. In this case, thermal evolution increased growth rates for both resource species. While for one species thermal optimum of growth rates shi ed towards higher temperatures, for the other it remained unchanged but with maximal rates increasing at the optimum, showing a vertical shi in magnitude. Evolution to new thermal environments showed marked di erences between species, increasing the carrying capacity for one resource and decreasing for the other. Finally, in chapter 4, I investigated thermal dependencies of consumer mortality, m, evaluated as survival rates, which represents the inverse of mortality rates, across two temporal scales-in acute and life-time exposure. Acute tests evaluated survival following the exposure to a range of temperatures over 1.5-2.5 hours, and life-long for exposures over organism's life span (up to 100 days). I found that survival decreased with temperature when consumers were exposed to higher temperatures during their life span. Survival a er acute exposure to increasing temperatures also decreased. However, survival was higher a er acute exposure and individuals persisted at higher temperatures than was possible during life-time exposure. When I examined evolutionary responses to increased temperature, I observed that thermal evolution increased thermal tolerance to extreme high temperatures in acute exposures to temperature but reduced persistence at extreme low and high temperatures in life-long exposures.

Main contributions

Thermal dependencies of energy gain and loss differ for both consumers and resources

Predicting the response of interacting populations to changing temperatures is challenging for multiple reasons. First, multiple processes that determine population dynamics are temperature dependent. Second, within a species, these dependencies on temperature can vary in form, sensitivity and magnitude. ird, di erent species can display di erent dependencies, potentially leading to idiosyncratic and/or context-dependent responses. And fourth, species interactions add an extra layer of complexity, because the strength of trophic interactions is also temperature dependent. To tackle this challenge, we have investigated how consumers and resources respond to warming by examining their overall energy balance by empirically determining the ratios of energy gain to loss across a wide temperature gradient.

For both resource species I found that metabolism (i.e., energy loss) and photosynthesis (i.e., energy gain) had similar qualitative responses with temperature, increasing exponentially until they reached an optimal temperature and then declined sharply. However, both resources di ered in their quantitative responses, displaying di erent thermal optima and activation energies. While thermal optima of metabolic rates were consistent for both resources and thermal populations (i.e., warm and ambient origin), photosynthesis had lower optimal temperatures, which led to thermal mismatches between energy gain and loss as temperature increased. ese di erences in thermal sensitivities of energy gain and loss translated into di erences in their energetic balances. Although both resources displayed a unimodal relationship with temperature, C. reinhardtii exhibited a wider thermal range below the optimal temperature, where the energetic balance increased with warming. ese results suggested that energetic restrictions derived from increases in temperature will start at lower temperatures and hence for a wider range of temperatures in Desmodesmus sp. compared to C. reinhardtii.

For the consumers, I found that metabolism (i.e., energy loss) followed a unimodal pattern with temperature but ingestion (i.e., energy gain) diverged depending on the food source. Ingestion declined with temperature when Daphnia fed on C. reinhardtii, but it was temperature independent instead when feeding on Desmodesmus sp. e lower thermal sensitivity of energy gain resulted in general energetic mismatches across temperatures. In consequence, warming decreased consistently the consumer's energetic balance, suggesting that increases of temperature are energetically detrimental for consumers.

How interactions change with temperature: a predictive approach based on the thermal dependencies of consumer-resource energetic balances

e understanding of the response of species' energetic balances to temperature allows us to examine how temperature a ects species interactions. In particular, I used and compared the changes on energetic balances of interacting species to predict responses on interaction strength. Measuring the impacts of temperature on species interaction strength are vital to better predict the e ects of warming on communities in the long term. eory, for example, shows that increases in the interaction strength can lead to dramatic oscillations of consumer and resource densities over time, triggering further extinctions at warmer temperatures [START_REF] Hoekman | Turning up the heat: Temperature in uences the relative importance of top-down and bottom-up e ects[END_REF][START_REF] Shurin | Warming shi s topdown and bottom-up control of pond food web structure and function[END_REF][START_REF] Velthuis | Warming advances top-down control and reduces producer biomass in a freshwater plankton community[END_REF]. On the other hand, reductions in interaction strength with warming can increase the stability of populations by slowing down the oscillations of interacting species populations [START_REF] Vasseur | A Mechanistic Approach for Modeling Temperature-Dependent Consumer-Resource Dynamics[END_REF][START_REF] Binzer | e dynamics of food chains under climate change and nutrient enrichment[END_REF][START_REF] Rall | Universal temperature and body-mass scaling of feeding rates[END_REF].

In my experiments, if I had relied upon solely the response of ingestion rates to determine the thermal response of interaction strength, I would have predicted declines for C. reinhardtii and invariant values for Desmodesmus sp. Moreover, if I considered only thermal dependencies of metabolism of the interacting species to gain intuition about the response of interaction strength, it would also lead to inaccurate results. Consumers were more restricted by their metabolic demands than resources, because the thermal optimum of metabolism was signi cantly lower for consumers than for resource species (i.e., c. 39 °C for resources and c. 29 °C for the consumer).

erefore, from this information we would deduce that because the metabolism of consumers is more negatively impacted by high temperatures than that of resource species, the e ect of the consumer on both resource species (i.e., interaction strength) would decrease with increasing temperatures. However, using the approach based on energetic balances of both interacting species instead, I was able to correctly predict trends of interaction strength with temperature. Speci cally, I showed that when thermal dependencies of energetic balances for interacting species matched, as observed for the pair Daphnia-Desmodesmus sp., interaction strength increased. However, the strength of the interaction decreased when energetic balances di ered, as seen for the pair Daphnia-C. reinhardtii. ese results demonstrate that this framework provides a novel means to use the thermal dependencies of key physiological responses of consumers and resources. In addition, it also gives additional depth and a mechanistic understanding to the interpretation of how consumer-resource interactions depend on temperature.

Evolutionary responses in species energetic balances can inform predictions of interaction strength across temperatures

e thermal dependencies of physiological traits of consumers and resources can evolve, adding an additional layer of complexity to understand how consumer-resource interactions will be a ected by climatic warming. In my experiments, I found that some populations evolved to warming conditions, but others not. Speci cally, I showed that thermal evolution changed metabolic and net photosynthesis rates to more homeostatic responses (i.e., these rates were less impacted by temperature) for C. reinhardtii. Consumer responses were also modi ed due to thermal evolution. Metabolic rates di ered between thermal populations across temperatures when per capita rates were not corrected by di erences in biovolume. Additionally, consumer ingestion had contrasting responses following thermal evolution when feeding on each food source. In contrast, thermal evolution increased metabolic rates across temperatures for Desmodesmus sp. e e ects of evolution on these parameters resulted in di erences in energetic balances for organisms. Speci cally, thermal evolution increased the energetic balance in C. reinhardtii across temperatures by decreasing its metabolic costs, but the contrary was observed for Desmodesmus sp. where evolution decreased its energetic balance. e outcomes of consumer energetic balances, however, di ered depending on the food source. When consumers fed on C. reinhardtii (i.e., the resource species that showed signs of thermal adaptation in energetic balances), thermal evolution increased its energetic balance at intermediate and high temperatures, but not in cold conditions, where unevolved consumers instead exhibited larger energetic balances. Evolved consumers feeding on Desmodesmus sp., where thermal evolution diminished the energetic balance of the resource, exhibited overall larger energetic stasis (i.e., energetic balance) across temperatures.

Evolution in response to warming has the ability to alter interspeci c interactions in a number of ways, with changes that can appear idiosyncratic if we only examine the outcomes to the interactions themselves. Examining the underlying physiological evolution can help to provide needed context to understand the consequences of evolution for interspeci c interactions. When I examined the e ects of evolution on the thermal dependency of consumer-resource interactions, I found that the way in which the interacting species evolve or not to warming impacted the overall results of the interaction. Speci cally, the e ects of evolution on energy gain and loss parameters resulted in di erences in energetic balances for interacting organisms. I found that the temperature-dependence of interaction strength remained unchanged when both interacting species evolved in ways that similarly altered their energetic balances. is resulted in a cryptic e ect, with evolutionary processes yielding patterns similar to expectations from solely ecological processes [similar to [START_REF] Brans | Cryptic eco-evolutionary feedback in the city: Urban evolution of prey dampens the e ect of urban evolution of the predator[END_REF]]. However, interaction strength changed markedly when thermal evolution of energetic balances of the two interacting species was uneven. In summary, I showed that by considering the e ects of evolution to the ratio of consumerresource energetic balances we can better predict the impacts of climatic warming on consumer-resource interactions.

Thermal sensitivities of additional traits expand our understanding of the effects of warming on consumers and resources

Finally, in addition to parameters related to energy gain and loss for individuals, we need to consider the response to warming of other important life history traits, because ultimately, it is the combination of the responses of multiple traits what determines the organism's tness. I showed that the thermal dependencies of these additional traits were consistent between resource species (i.e., unimodal for growth rates, increasing saturating for nutrient acquisition and a linear decline for carrying capacity) and consumers (i.e., exponential increase for growth rates, unimodal for net reproductive rates and linear declines for generation times and survival rates). e contrasting decline in carrying capacity combined with the increase in nutrient acquisition with warming suggests that there is a decrease on e ciency in biomass conversion with warming for both resource species. For a constant e ciency in biomass conversion across temperatures, the more nutrients are processed, the larger the population size at carrying capacity should be. However, I observed the opposite: more nutrients were required with increasing temperatures, but population size decreased. erefore, these results indicate that both species became less e cient in converting nutrients into population biomass with increasing temperatures (similar to [START_REF] Marañón | Unimodal size scaling of phytoplankton growth and the size dependence of nutrient uptake and use[END_REF][START_REF] Marañón | Nutrient limitation suppresses the temperature dependence of phytoplankton metabolic rates[END_REF][START_REF] Bernhardt | Metabolic theory and the temperaturesize rule explain the temperature dependence of population carrying capacity[END_REF]). e traits described above are potentially under directional selection in response to changing temperatures, such that the temperature dependency of these traits can evolve in response to warming. Di erent traits can trade o with each other, or even compensate others, to determine tness. erefore, to understand the tness implications of evolutionary changes to temperature, we also need to examine population traits across temperatures following evolution. Speci cally, thermal evolution of C. reinhardtii increased its population growth rate, carrying capacity and nutrient acquisition. For Desmodesmus sp., population growth rate and nutrient acquisition were also higher in the warm-origin genotype, however, carrying capacity was lower. It has been argued that the thermal dependence of population growth rate is a direct consequence of the thermal dependence of metabolic rates [START_REF] Savage | E ects of body size and temperature on population growth[END_REF]). For C. reinhardtii, growth rates were overall larger across temperatures for the warm-origin genotype. is could result from the lower metabolic costs of the warm-origin genotype across temperatures (as seen in chapter 2). Additionally, the di erences observed in trends of carrying capacities with temperature and their magnitudes between thermal-origin genotypes could be related to the di erences observed in metabolic rates between thermal populations [START_REF] Bernhardt | Metabolic theory and the temperaturesize rule explain the temperature dependence of population carrying capacity[END_REF]. Speci cally, I found that metabolic rate of the warm-origin genotype of C. reinhardtii exhibited lower thermal dependency compared to the ambient genotype. is could explain the weaker response in the decline of carrying capacity with temperature for the warm-evolved C. reinhardtii. Moreover, the larger values of carrying capacity for the same genotype across temperatures could be explained by the larger rate of nutrient acquisition across temperatures. erefore, evolutionary responses in metabolic rates and nutrient acquisition favoured a larger carrying capacity and its lower thermal dependency, which is an advantage over the ambient-origin C. reinhardtii genotype. For Desmodesmus sp., however, metabolic rates were similar between genotypes across temperatures, which translated into a similar trend for carrying capacity with temperature. e larger rate of nutrient acquisition by the warm genotype could not explain the lower values of carrying capacity across temperatures compared to the ambient-origin genotype. Finally, although thermal evolution favoured in general the warm-origin genotype of C. reinhardtii, some associated costs can materialise for this population. For instance, in previous studies the increase in growth rates and reduction in metabolism as a consequence of evolution can be linked to earlier maturation, which can impact negatively populations in the long-term [START_REF] Norin | Ecological and evolutionary consequences of metabolic rate plasticity in response to environmental change[END_REF][START_REF] White | Metabolic scaling is the product of life-history optimization[END_REF].

Selection pressures from warming can be complex and can di er across time scales, so considering how populations respond to acute and life-time exposure can help to give a more complete picture of the implications of evolutionary responses. Trade-o s can emerge both between traits, as discussed before, and across time scales, when considering how populations respond to acute and life-time exposure to temperature. In fact, an examination of consumers' survival at two time-scales revealed an additional trade-o that can occur for populations responding to climate warming-the need to survive acute thermal exposures and the need to persist at sustained higher mean temperatures. When examining consumer traits, I found that evolved consumers (i.e., warm-origin daphnids) persisted better at higher temperatures during acute exposures to temperature. However, life-long exposure to temperature reduced survival rates of evolved consumers, suggesting a trade-o between acute and chronic heat tolerance. e higher tolerance of evolved consumers to acute temperature exposure suggests that di erences between thermal populations could be driven by di erences in the frequency of extreme weather events (i.e., heat waves) rather than changes in average temperatures [START_REF] Huey | Predicting organismal vulnerability to climate warming: Roles of behaviour, physiology and adaptation[END_REF]. Extreme high temperatures experienced by warm-origin daphnids likely entailed a strong selective pressure, however we found a temporal trade-o in the long-term dynamics. ese temporal trade-o s are relevant to ongoing climate change because it is characterized by both an increase in mean temperatures and an increase in temperature variability, resulting on a larger proportion of extreme high temperature events [START_REF] Meehl | More Intense, More Frequent, and Longer Lasting Heat Waves in the 21st Century[END_REF][START_REF] Stott | How climate change a ects extreme weather events[END_REF][START_REF] Woodward | e e ects of climatic uctuations and extreme events on running water ecosystems[END_REF]. Compensatory interactions between traits have been observed previously in the literature in populations as a way to maintain tness and prevent extinctions in the face of environmental change [START_REF] Villellas | Demographic compensation among populations: What is it, how does it arise and what are its implications?[END_REF][START_REF] Sheth | Demographic compensation does not rescue populations at a trailing range edge[END_REF]). In my system, however, I did not nd any compensatory e ect in any of the demographic traits measured that could help o set the observed di erences in life-time survival rates between thermal populations across temperatures.

Finally, among organisms' traits, body size constitutes an important parameter that can determine population responses to temperature. I found a consistent systematic reduction in cell size and body volume for both resource and consumer populations exposed to long-term conditions (up to 14 years) of +4 °C warming, which is in line with the general shrinking e ect for ectotherms with warming [START_REF] Daufresne | Global warming bene ts the small in aquatic ecosystems[END_REF][START_REF] Sheridan | Shrinking body size as an ecological response to climate change[END_REF]. Desmodesmus sp. not only decreased in size with warming, but also changed the proportion of cell aggregates of di erent sizes. While the ambient-origin genotype had a higher proportion of 4-celled aggregates, the warm-origin genotype had a larger proportion of single cells or 2-celled aggregates. Consumers used in ingestion and metabolism experiments (chapter 1 and 2) di ered markedly between populations with thermal evolved individuals exhibiting smaller sizes (see Appx. B Supp. Methods S2.1). However, body size did not di er between thermal origins for consumers growing at 18 and 22°C as shown in chapter 4 (see Appx. C, Fig. S4.3 and S4.4). e di erence between these two sets of experiments lies in the samples used. While results of chapter 4 depicted variances of body size at death for at least 5 di erent clonal populations for each thermal origin, individuals used for ingestion and respiration experiments only considered the largest individuals from each clonal population.

In general, these results showed the mechanisms behind species adaptations to long-term exposure to warming. It highlights how populations can deal to selecting pressures and track environmental change, but these thermal advantages can bring trade-o s, showing the costs associated to evolutionary responses of species.

Open question: Scaling-up from species responses to pairwise interactions to multi-species systems

Predicting the impacts of climate change on ecosystems is one of the biggest scienti c challenges of our time. One of the less trivial aspects of this challenge is to scale up from individual responses to responses of species interactions and to responses at the community level (e.g., [START_REF] Montoya | Climate change, biotic interactions and ecosystem services[END_REF]Lurgi et al. 2012a). One of the approaches to facilitate this scaling-up process is to focus on a single trait, the metabolism or organisms, as the trait that rules and governs everything, as proposed, for example, by the Metabolic eory of Ecology (MTE) (Brown 2004). MTE posits that a number of population, community and ecosystem processes can be simply predicted by the aggregation of individual metabolisms. Take the response of respiration in response to increasing temperatures, where communitylevel respiration is estimated from the sum of the respiration rates of all individuals within the community (Yvon-Durocher et al. 2010a, b, 2012). However, the reality is more complex. Recent studies have shed light on how to appropriately manipulate the sum of individual species response data in order to predict the function of the whole community [START_REF] Ghedini | Metabolic scaling across succession: Do individual rates predict community-level energy use?[END_REF]. However, metabolism is not the only trait that matters for populations and species interactions when temperature increases. My approach showed that knowing metabolic losses is not enough to predict species-and interaction-level responses to warming. Instead, it is the balance between metabolic losses and energetic gains that matters, and energetic gains cannot be inferred from metabolism alone. e question that emerges is how feasible this approach is for predicting the e ects of changing temperatures on species-rich systems. is task is daunting, as di erent species can have di erent responses to warming in terms of energy gain and loss, leading to di erent responses on their energetic balances that ultimately determine interaction strength. One possibility is to focus and empirically estimate the energy gain of species as I showed this is the parameter that governs the response of thermal mismatches, given that the temperature dependency of energy loss is quite universal across species. erefore, to scale-up from pairwise interactions to specie-rich systems would require to empirically measure the thermal dependencies of net photosynthesis for primary producers, and ingestion rates for consumers. Metabolic rates could simply be assumed to increase exponentially with temperature with a slope (i.e., values of activation energy, Ea) of c. 0.7 for consumers and 0.5 for resources. ese values emerge from those used by theory and they are a reasonable approximation for metabolism because the thermal ranges at which metabolism peaks are typically sub-lethal temperatures for the organism. Because in ecological communities most trophic interactions are weak [START_REF] Wootton | Measurement of interaction strength in nature[END_REF], I suggest to focus on strong interactions, which are likely to be the most important for community dynamics, even if weak interactions can have consequences for the overall stability of the system [START_REF] Vasseur | A Mechanistic Approach for Modeling Temperature-Dependent Consumer-Resource Dynamics[END_REF][START_REF] Binzer | e dynamics of food chains under climate change and nutrient enrichment[END_REF]. is would require some previous knowledge of the natural history of the system of interest. From this, we then can calculate species' energetic balances and infer interaction strength, which would enable us to model community dynamics, predict consumer and resource biomasses across temperatures, and forecast scenarios where consumers or resources can face extinction. andc) show cases of inter-TM. In (a) the thermal dependency of consumer energetic balance matches that of the resource, so no mismatch in the interaction is expected. At low temperature (i), increases of temperature lead to increases of energy availability for both organisms. en, at intermediate temperatures (ii), increases of temperature reduce the energy availability for both organisms, causing intraspeci c thermal mismatches (Intra-TM) in both species. us, both organisms su er from energy de cits in the same way with temperature. Finally, at high temperatures (iii), the ratio falls below 1 for both species, meaning that the energy gain cannot compensate for the energy loss, so energy de cits will be strong for both organisms. In (b) thermal dependency of the consumer energetic balance di ers from that of the resource, so inter-TMs are expected with the consumer a ected from energy de cits at lower temperatures than the resource. At low temperature (i), increases of temperature translate into an increase of energy availability for both organisms.

en, at intermediate temperatures (ii), increases of temperature reduce the energy available to the consumer, but not the resource, which still increases. is causes an inter-TM because the consumer su ers from energy de cits while the energy available to the resource still increases with temperature. At high temperatures (iii), the consumer struggles to cope with energy losses as the ratio falls below 1, while the resource species still maintains an energy balance over unity. However, increases of temperature in this thermal region will reduce the energy available for resource species. In (c) similarly to (b), thermal dependency of the energetic balance of consumer di ers from that of the resource, so an inter-TM is expected, but the resource su ers from energy de cits at lower temperatures compared to the consumer. Predicted temperature scenarios (i, ii, iii) of case (c) show the opposite situation compared to those in scenario (b), with the resource instead su ering from energetic de cits at lower temperatures than does the consumer. In nature, scenarios a) and b) are most likely to happen for ectothermic species, while case c) may occur hypothetically in a situation where an endotherm feeds on a thermally sensitive ectotherm. Coloured regions depict energetic balance trends with increasing temperatures. In blue rising trends, and in orange and red declining trends over and below unity respectively. Black arrows show species' intraspeci c thermal mismatches, i.e., negative e ects on species energetic balances due to warming. Red arrows show interspeci c thermal mismatches between interacting species with two distinguishable thermal regions, where: 1) trends of energetic balances contrast between the interacting species; and 2) both species reduce their energetic balance with increasing temperature. Vertical coloured-dashed lines in black depict the temperature at which the G/L ratio is maximized (Tm) and the crossover temperature (Tc) where energy gain equals energy loss (ratio = 1). In blue and red, vertical-dashed lines depict optimum temperatures for net photosynthesis and respiration respectively.

Table S1.1. Sharpe-School eld parameter estimates with associated standard errors (SE), t-values, residual standard error, degrees of freedom (DF) and number of iterations to convergence from models describing the response of respiration and net photosynthesis rates with temperature for C. reinhardtii and Desmodesmus sp., and respiration rates for D. pulex. E a is activation energy (eV), E h is high temperature de-activation energy (eV), T h is the temperature at which enzyme is ½ active and ½ suppressed due to high temperatures ( C) and T ref is standardisation temperature at which rates are not inactivated by high temperatures. In March 2020, incubator temperature of clonal stock cultures was raised to 20 C. Finally, tests of acute thermal range for algae respiration and net photosynthesis took place in November 2020. erefore, resource batch cultures were kept under exponential, nutrientreplete conditions in COMBO freshwater medium at 20 C for approximately eight months before physiological data collection.

Clonal cultures of the consumer, Daphnia pulex, originated from the same experimental mesocosms.We collected zooplankton samples from Dorset mesocosms by serial ltration (> 500 µm) in October 2019. Identi cation of daphnids to species level was by means of morphological features [START_REF] Bledzki | Freshwater Crustacean Zooplankton of Europe[END_REF]) using a digital stereo microscope (Leica S9i) and con rmed by a freshwater taxonomist (pers. comm. Dr. Antonio Guillén Oterino, April 9, 2020). From these samples, we isolated ve gravid females, that constituted the ve clonal lineages, of Daphnia pulex by placing them in Erlenmeyer asks in modi ed nutrientfree COMBO medium (to prevent bacterial proliferation) in incubators at 18 C. Identical culturing conditions to the algae stock cultures ensured that consumers and resources experienced identical light and temperature conditions prior to experiments.

Daphnia were fed daily (M-F) with a homogenous mixed algal suspension consisting of C. reinhardtii, Desmodesmus sp. and Scenedesmus obliquus isolated from same Dorset mesocosms and maintained individually in semi-continuous batch cultures in COMBO medium in identical culturing conditions. e daily feeding regime consisted of adding a highly dense suspension of mixed algae comprising about a 10 % of total culture volume. Every week we ltered approximately 2/3 of each clonal stock culture volume in order to remove waste materials, possible kiromones, as well as any ephippia if present, which may induce diapause of cladocera. We then added an equivalent volume of fresh modi ed nutrientfree medium and the corresponding daily algal suspension. To reduce algae sedimentation, D. pulex clonal stock cultures were maintained on an orbital shaker (Heidolph Unimax 2010, orbit 20 mm, at 90-100 rpm) inside the incubators. As with the algal cultures, from March 2020 onward, we raised the culture temperature to 20 C. Tests of acute thermal response for Daphnia respiration and ingestion rates took place in June-July 2020, so consumers were kept under culturing conditions at 20 C over three-four months before experiments took place.

S1.2 -Starvation of algal cells and daphnids

Starvation of algal cells started 48 hours before the experiments, with eld-collected stock clonal cultures at the mid-logarithmic phase. Algal starvation was obtained by concentrating 50 ml aliquots of each algal species using an orbital centrifuge at 3,000 rpm over 15 minutes [START_REF] Shirwastav | Adaptability of growth and nutrient uptake potential of Chlorella sorokiniana with variable nutrient loading[END_REF][START_REF] Boonchai | E ect of nutrient starvation on nutrient uptake and extracellular polymeric substance for microalgae cultivation and separation[END_REF]. en, supernatant was discarded (nutrientreplete COMBO medium) and replaced by the same volume with modi ed nutrient-free COMBO medium. Cells were then re-suspended in the new nutrient-fee medium and the process was repeated two more times. Finally, cultures were brought back to culturing conditions (12:12 D: L photoperiod at 20°C) in the depleted-nutrient media for 48-hours until further experiments. e main goal of this procedure was to deplete nitrogen and phosphorus pools within the cells to get as close as possible to basal metabolic conditions over the course of the experiments. Mean densities of starved algal cells employed for resources' respiration and net photosynthesis experiments were set to about 60,000 cells/ml for C. reinhardtii and 215,000 cells/ml for Desmodesmus sp., based on previous pilot tests. For Daphnia samples we starved 5 adult daphnids-one from each clonal batch culture-for each replicate in culture tubes containing only media at culturing conditions for c. 24 hours. us, each replicate contained a total of 5 adult daphnids comprised of 1 daphnid from each clonal lineage. is starvation time is considered the standard for hind-gut clearance on D. pulex [START_REF] Schlechtriem | E ect of temperature on the fatty acid composition and temporal trajectories of fatty acids in fasting Daphnia pulex (Crustacea, Cladocera)[END_REF].

S1.3 -Algae preservation by freezing and ow cytometry methods

We cryopreserved algal samples for later analysis by ow cytometry whenever algae density was a response variable [similar to [START_REF] Bestion | Phytoplankton biodiversity is more important for ecosystem functioning in highly variable thermal environments[END_REF]]. Instances included algal samples collected at the end of algal respiration and net photosynthesis rates, as well as initial and nal algal densities sampled from D. pulex ingestion rates. is procedure enabled us to accurately batch process a large number of samples collected across days and experiments using ow cytometry. For each replicate, a 150 µl sample of well-mixed algae suspension was preserved using 15 µl of 1% sorbitol solution individually in wells of a 96-well plate and incubated for about 1 hour in the dark before being frozen at -80 °C. Sorbitol protects algal cell walls during the process of deep freezing, preventing the cells from lysing. For batch processing, sample plates were later defrosted at ambient room temperature (~ 20 -25 C) and analysed by ow cytometry (BD FACSCanto II high throughput sampler) to estimate cell densities. Parameters of ow cytometric lasers were optimized as follows: FSC: 136, SSC: 258, FITC: 484, PE: 432, PerCP-Cy5: 297, PE-Cy7: 570, APC: 440, APC-H7: 472, V450: 373 and V500: 484. Sample plates were run on the ow cytometer at a 0.5 µl /s ow rate, with two times 100 µl mixing and a cleaning volume of 200 µl between each individual sample to avoid carry-over contamination between consecutive samples. e ow cytometer processed a sample volume of 10 µl from each replicate sample well.

en, we extracted algal density counts from ow cytometry les using the Bioconductor ' owCore' [START_REF] Ellis | owCore: owCore: Basic structures for ow cytometry data[END_REF] and 'tidyverse' [START_REF] Wickham | Welcome to the Tidyverse[END_REF]) R-packages. Extracted data provided information on cell counts and cytometric laser properties such as red uorescence (PerCP.Cy5), a proxy of chlorophyll-a content, and forward scatter (FSC) a proxy of cell size. To remove counts of potential bacteria or debris present in our samples that would otherwise cause overestimates of algal density, we ltered the data by removing any cell count where log10(PerCP.Cy5) < 2 and log10(FSC) < 3.4. ese threshold values were below minimum observed values for live cells of tested species.For algal density counts, two technical replicates were routinely collected for each sample replicate, so nal density counts were obtained as the mean of these two measurements. Finally, as sample replicates were diluted by 10% with the sorbitol solution for cryopreservation, cytometer densities obtained were corrected by a factor dilution of 1.1 in order to calculate the real cell densities.

S1.4 -Data manipulation and R packages employed

We used R statistical so ware (4.0.3) (R Core Team 2021) for data manipulation, analysis and plotting. e 'tidyverse' package was the primary package used for data manipulation and 'ggplot2' [START_REF] Wickham | ggplot2: Elegant Graphics for Data Analysis[END_REF] for creating the graphs.

As part of Daphnia ingestion rates' experiments, we veri ed that initial algal densities did not di er statistically between controls and consumer treatments within temporal blocks using Post-Hoc pairwise tests (i.e., for all post-hoc tests p > 0.05). For this we used 'emmeans' and 'pairs' functions from the 'emmeans' package [START_REF] Lenth | emmeans: Estimated Marginal Means, aka Least-Squares Means[END_REF]. No signi cance di erence between these treatments at the beginning of the experiment implied that any di erence at the end of the experiment were only caused by the presence of the consumers. As part of the data processing, we removed two extreme opposite outliers in the ingestion rate values for D. pulex feeding on C. reinhardtii at 36 C, one from each temporal block: replicates D1 and D5 (n= 4) and one replicate for ingestion on Desmodesmus sp. at 36 C. We similarly removed two replicates in the interaction strength data, one at 22 C for Desmodesmus sp. and one at 36 C for C. reinhardtii. To identify outliers, we analysed distributions, means and variances of the datasets. Replicates that were inconsistent with dataset variances and at least three standard deviations away from the mean (minimum and maximum thresholds (T min , T max = mean ± 3 * SD) for each algal species were considered outliers. A possible explanation for these outliers could be due to a lack of precision in homogenising the samples before sampling, so we considered that they were likely related to methodological errors. ermal performance curves were t using 'rTPC' , 'nls.multstart' (Pad eld et al. 2021) and 'minpack.lm' [START_REF] Elzhov | minpack.lm: R Interface to the Levenberg-Marquardt Nonlinear Least-Squares Algorithm Found in MINPACK, Plus Support for Bounds[END_REF] packages. Bootstrapping using the case resampling method employing 'rTPC' , 'nls.multstart' and 'car' [START_REF] Fox | An R Companion to Applied Regression[END_REF] packages yielded con dence intervals of TPC parameters.

We tted values of interaction strength to general linear models (GLM) by conducting a full linear regression model with interaction between temperature and algal species (Interaction Strength ~ Temperature * Algal species), performed a two-way analysis of variance (ANOVA), as well as obtained slopes and intercepts for each algal species and summary statistics using 'emtrends' function from 'emmeans' and 'stats' (R Core Team 2021) R-packages.

S1.5 -Conversion of consumer gain and loss rates into energetic equivalents Conversion of Daphnia respiration rates to energetic equivalents

Per capita consumer respiration rate, R c , is calculated as the di erence in slopes of oxygen concentration with time in consumer and control replicates:

(eq. S1)

where m t is the slope of the linear regression between oxygen saturation and time for replicates containing Daphnia adults, m c is the mean slope of controls for each temporal block, and d is the number of adult daphnids alive at the beginning of the experiment in Daphnia treatment replicates. e value of d was used to control for mortality. It was generally 5, but in exceptional cases consumer numbers dropped during the acclimation ramp-up. erefore, units of per capita respiration rates are:

(eq. S2)

We next transformed per capita respiration rate, R c , to an energy equivalent, R e c , in order to make respiration rates comparable to ingestion rates, with units: Hence, we used the following transformation:

We assumed that 1 mg of O 2 equals 14.06 Joules of energy [START_REF] Peters | Ecological implications of body size[END_REF][START_REF] Rall | Temperature, predator-prey interaction strength and population stability[END_REF] e conversion from mL to L, simply requires multiplication by 1000. e speci c conversion values for biovolume, biomass and calori c value depend upon which resource species upon which the Daphnia feeds. When D. pulex feeds on Chlamydomonas reinhardtii, we calculated the biovolume of our samples as 343 µm 3 /cell using manual measurements following the methods of [START_REF] Hillebrand | Biovolume calculation for pelagic and benthic microalgae[END_REF]. e biomass conversion factor used was 0.28 10 -12 g/µm 3 [START_REF] Montagnes | Combined e ect of temperature and food concentration on the grazing rate of the rotifer Brachionus plicatilis[END_REF][START_REF] Finkel | Size-scaling of macromolecules and chemical energy content in the eukaryotic microalgae[END_REF]. And nally, the calori c value for this species (i.e., the amount of energy provided in Joules per gram) is equal to 22.397 x 10 3 Joules/g [START_REF] Feinberg | Fuel Options from Microalgae with Representative Chemical Composition[END_REF]). Hence, multiplying the speci c values of biovolume, the biomass conversion factor, the calori c value and the volume correction factor for C. reinhardtii yields a conversion factor of 2.15 x 10-3 to get energy equivalents of ingestion rates:

(eq. S8)

When D. pulex feeds on Desmodesmus sp., the calculated biovolume of our samples [following Hillebrand et al., (1999b)] was 310 µm 3 /cell. e biomass conversion factor used was 0.139 10 -12 g/µm 3 [START_REF] Rocha | e relationship between cell carbon and cell volume in freshwater algal species used in zooplanktonic studies[END_REF] , based on Scenedesmus quadricauda. is species is the most similar species [i.e., in terms of morphology and biovolume (≃ 270 µm 3 / cell)] to our Desmodesmus species for which a biomass conversion factor was available in the literature. e calori c value used for this species was 23 x 10 3 Joules/g [START_REF] Tibbetts | Nutritional Evaluation of Whole and Lipid-Extracted Biomass of the Microalga Scenedesmus sp. AMDD Isolated in Saskatchewan, Canada for Animal Feeds: Proximate, Amino Acid, Fatty Acid, Carotenoid and Elemental Composition[END_REF]).

e aggregated conversion factor for Desmodesmus sp. to get energy equivalents of ingestion rates is thus 0.99 x 10-3: (eq. S9)

Finally, as not all the algal cellular components ingested by the consumer will be assimilated, we calculated the nal per capita ingestion rates, I E , by multiplying per capita raw ingestion rates in energy units, rI E , by a unitless assimilation e ciency (W):

(eq. S10)

We assumed that assimilation e ciencies remained constant across temperatures with W = 14% when D. pulex fed upon C. reinhardtii [START_REF] Wetzel | Limnology: Lake and River Ecosystems[END_REF]) and W = 10% when it instead fed upon Desmodesmus sp. Information on the assimilation e ciency of D. pulex feeding on Desmodesmus sp. in the literature is scarce, but assuming that this species has a di erent cell wall chemical composition compared to C. reinhardtiilarger quantities of carbon xed in the cell wall are in form of cellulose and pectin-this suggests that Desmodesmus is likely more di cult to assimilate for the consumer compare to C. reinhardtii. For this reason, we assume that assimilation e ciency must be lower for this species. Additionally, It has been reported that D. pulex feeding on Scenedesmus acuminatus shows an assimilation e ciency of near 7% [START_REF] Infante | Investigations on the 'incorporation of di erent algae by some zooplankton species -Ùntersuchungen über die Ausnutzbarkeit verschiedéner Algen durch das gooplankton[END_REF]. is species has more intricate cell structures than our species of Desmodesmus. For this reason, we considered that assimilation e ciency for D. pulex feeding on Desmodesmus sp. should be somewhere between 7 and 14%. erefore, we conservatively used 10% as a constant value of assimilation e ciency for Desmodesmus sp. Table S2.1 Sharpe-School eld parameter estimates with associated standard errors (SE), t-values, residual standard error, degrees of freedom (DF) and number of iterations to convergence from models describing the response of respiration and net photosynthesis rates with temperature for C. reinhardtii and Desmodesmus sp., and respiration rates for D. pulex. Rates are biovolume-and biomass-corrected for the two alga and D. pulex respectively. Ea is activation energy (eV), Eh is high temperature de-activation energy (eV),

is the temperature at which enzyme is ½ active and ½ suppressed due to high temperatures ( C) and Tref is standardisation temperature at which rates are not inactivated by high temperatures. Colours depict thermal origin of species' populations, in blue ambient-origin, and in red, warm-origin. Formulas above represent linear models' formulas with fitting (R 2 ) by thermal origin (see table S3.1 for statistical details). Colours depict thermal origin of species' populations, in blue ambient origin, and in red, warm origin. We compute algal biovolume from FSC ow cytometry laser data (see methods in in Appx. B Supp. Methods S2.1). for each replicate when populations achieved stationary phase in the growth curve, so at the end of the growth experiments.

For both algal species we assessed the median biovolume di erences using a Mann-Whitney statistical test, the non-parametric alternative to the unpaired two-samples t-test.

Figure I. 1 .

 1 Figure I.1. Global surface temperature changes predicted relative to 1850-1900 based on the di erent CO 2 emission scenarios according to the IPCC -Working group I ( gure adapted from IPCC 2021b).

Figure I. 2 .

 2 Figure I.2. Schematic diagram showing di erences in thermal sensitivities of species traits related to energy gain (G, in blue) and loss (L, in red) in panel a) and thermal dependencies of the energetic balance, i.e., the ratio of energy gain to loss in panel b).We can translate from the thermal dependencies of energy gain and loss by calculating the ratio between energy gain and loss across temperatures. is ratio yields the energetic balance that describes the thermal regions where we expect an initial increase with temperature (around the thermal region of temperature i), then a slowdown until it reaches an optimum (Tm). A er the optimum, the organism decreases its energetic balance (temperature ii) where thermal mismatches would materialise for the organism (intra-STM), until it reaches a critical threshold temperature (Tc), where energy gain cannot keep up with the metabolic demands (temperature iii). Above this temperature, further extinctions will be expected if warming persists.

Figure I. 3 .

 3 Figure I.3. Schematic diagram showing di erences in energetic balances (G/L ratio) of two interacting species.Blue-shaded areas correspond to a positive energetic balance where energy gain increases faster with temperature than energy loss. Orange-shaded areas correspond to a decreasing (intra-TM) but still positive energetic balance with increasing temperatures. Red-shaded areas correspond to a negative energetic balance, i.e., where energy loss exceeds energy gain. At low temperatures (i), for both species, the energetic balance of the organism increases with increasing temperature and gain exceeds loss. At intermediate temperatures (ii), energy gain exceeds loss for both species, but the ratio declines for the consumer, leading to a decline in the energy balance and the emergence of intraspeci c thermal mismatches (Intra-TM). At high temperatures (iii), energy loss for the consumer exceeds energy gain and the ratio falls below one, so the organism cannot ful l its energetic demands. e resource also su ers from energetic de cits, but the G/L ratio still remains over one. ermal mismatches between interacting species (Inter-TM) arise at temperatures at which one of the two interacting species starts to su er from energetic de cits while the other does not. We distinguish two distinct thermal regions within the Inter-TM: (1) where energetic balances di er between interacting species, and (2) where the energetic balances of both species decline with increasing temperature.

Fig

  Fig. I.4. A typical asymmetrical ermal Performance Curve -TPC-(black solid line) of an ectotherm (modi ed from[START_REF] Dowd | ermal variation, thermal extremes and the physiological performance of individuals[END_REF][START_REF] Sinclair | Can we predict ectotherm responses to climate change using thermal performance curves and body temperatures?[END_REF])) where CT min is the minimum critical temperature, CT max is maximum critical temperature and T opt is the optimal temperature, Ea is the activation energy and Eh is the deactivation energy. Green dashed line shows the assumed exponential increase of metabolic rates with temperature described by the MTE.

Figure I. 5 .

 5 Figure I.5. Conceptual representation of the thesis. Each chapter covers the study of thermal dependencies, and potential evolutionary responses, of di erent constituent parameters of consumer-resource models.Chapter 1 explores the thermal dependency of interaction strength, f, based on energetic imbalances of interacting species. Chapter 2 focuses on the evolutionary responses to temperature of interaction strength based on individual species traits related to energy gain and loss. Chapter 3 examines the temperature dependencies and evolutionary responses of resource population traits, such as growth rate, r, and carrying capacity, K. And nally, Chapter 4 focuses on consumer's traits, investigating mortality/survival (i.e., parameter m) to temperature across two temporal scales, as well as other important demographic traits using two thermal contrasting populations of consumers.

  and I.7), as resources, and the planktonic herbivore Daphnia pulex (Fig. I.8) as consumer. ese taxa are very well studied, cosmopolitan keystone freshwater species.

Figure I. 6 .

 6 Figure I.6. Microscopic pictures of the freshwater green algae Chlamydomonas reinhardtii isolated from Dorset freshwater mesocosms platform, UK, in 1000x magni cation.

Figure I. 7 .

 7 Figure I.7. Microscopic pictures of the freshwater green algae Desmodesmus sp. isolated from Dorset freshwater mesocosms platform, UK, in 1000x (a) and 200x magni cation (b).

Figure 1 . 1 .

 11 Figure 1.1. Species thermal mismatches of interacting consumer (a, b) and resource (c, d) species. a) and c) represent ermal Performance Curves (TPCs) of energy gain (G, in blue) and loss (L, in red) parameters. e slope of the rate is the activation energy (E a ), the temperature at which the rate peaks is the optimum temperature (T opt ), the slope of the rate a er the peak is the deactivation energy (E h ), the maximal value of rate performance occurs at MRP, and the temperature of energy gain rate in ection (T m

Figure 1

 1 Figure 1.2. ermal performance curves (TPCs) of energy gain and loss and energetic balance for Chlamydomonas reinhardtii. In a), red corresponds to per capita respiration rates, and blue to per capita net photosynthesis rates. TPC trends depict calculated predicted values using a nonlinear mixed e ect model tted to the parameter data using the Sharpe-School eld equation model. Bold points represent mean values with error bars showing ± SEM (n = 6). Light points denote raw values. In b), the energetic balance is computed as the net photosynthesis (P) to respiration (R r ) ratio (P/R r ) using predicted values of each rate obtained from models. Vertical black-dashed lines correspond to temperatures at which the maximal value of the energetic balance is obtained (T m = 30.7 C) and the crossover temperature (T c = 36.85 C) when the P/R r ratio equals one. Intraspeci c thermal mismatches are expected for temperatures above T m . In a) and b), vertical coloured dashed lines depict optimum temperatures of net photosynthesis in blue (T opt P = 31.6 C) and respiration in red (T opt R = 39 C). To increase the clarity of a), we decided to restrict the y-axis to the values here presented.

Figure 1

 1 Figure 1.3. ermal performance curves (TPCs) of energy gain and loss and energetic balance for Desmodesmus sp. In a), red corresponds to per capita respiration rates, and blue to per capita net photosynthesis rates. TPC trends depict calculated predicted values using a nonlinear mixed e ect model tted to the parameter data using the Sharpe-School eld equation model. Bold points represent mean values with error bars showing ± SEM (n = 6). Light points denote raw values. In b), the energetic balance is computed as the net photosynthesis (P) to respiration (R r ) ratio (P/R r ratio) using predicted values of each rate obtained from models. e vertical black dashed line corresponds to the temperature at which the energetic balance is maximised (T m = 19.15 C) and the horizontal dotted line shows a value of P/R r ratio equal to one. Intraspeci c thermal mismatches are expected for temperatures above T m . In a) and b), vertical coloured dashed lines depict optimum temperatures of net photosynthesis in blue (T opt P = 27.40 C) and respiration in red (T opt R = 39.34 C).

Figure 1 .

 1 Figure 1.4. ermal norms of energy gain and loss and energetic e ciencies for the consumer D. pulex feeding on either C. reinhardtii (a-b) or Desmodesmus sp. (c-d). In a) and c), red corresponds to energy loss (per capita respiration rates, R c ), and blue to energy gain (per capita ingestion rates, I E ) both transformed into energy equivalents (J L -1 Daphnia -1 h -1 ). e thermal norm of consumer respiration depicts calculated predicted values using the Sharpe-School eld equation model, and ingestion rates depict calculated predicted values for each resource species using GLMs. Bold data points represent mean values with error bars showing ± SEM (n = 6 replicates per tested temperature for each parameter, except for ingestion at 36°C with n= 4 C for C. reinhardtii due to outliers). Light points denote raw values. In b) and d), the energetic balance is calculated as the ingestion (I) to respiration (R c ) ratio of D. pulex feeding on C. reinhardtii (b) or Desmodesmus sp. (d). e horizontal black dotted line indicates a value of I/R c ratio equal to one, where energy gain equals loss. Energetic balances show intraspeci c thermal mismatches for Daphnia with increasing temperature for the whole thermal range tested when feeding on either resource species. Vertical black-dashed lines show critical temperatures (Tc; I E / R c ratio =1) occurring at 20.7 C when D. pulex feeds on C. reinhardtii and at 22.5 C when it feeds on Desmodesmus sp. Vertical dashed lines in red depict the optimum temperature of D. pulex respiration rates (= 29.45 C).

Figure 1

 1 Figure 1.5. E ects of temperature on hourly per capita Interaction strength (IS). Interaction strengths are computed as the log response ratio of D. pulex feeding either on Desmodesmus sp. (in purple) or on C. reinhardtii (in turquoise). Bold data points represent mean values of IS with error bars showing ± SEM (n = 6, except for C. reinhardtii at 36 C and Desmodesmus sp. at 22 C where IS values had 5 replicates instead due to the presence of an outlier). Light points denote raw values. Beta values (β) represent the slope of the linear regression between temperature and IS for each resource, showing the signi cance value for each regression (p) (see Tables S1.4 and S1.5 and Suppl. Methods S1.4 for statistical details).

Figure

  Figure 2.1. ermal Performance Curves (TPCs) of respiration (a, c) and net photosynthesis (b, d) corrected by biovolume for two contrasting thermal genotypes of C. reinhardtii (a, b) and Desmodesmus sp. (c, d). Data points denote values of either oxygen consumption (i.e., respiration) or production (i.e., net photosynthesis) corrected by biovolume (µm 3 ), and TPC trends depict calculated predicted values of Sharpe-School eld models. TPC trends depicted in light colours denote nonparametric bootstrapping estimating model uncertainty and con dence intervals, and sharp-trends predictions of the TPC for each genotype. Blue colour corresponds to ambient-origin and red to warm-origin genotypes. Respiration rates of warm-origin C. reinhardtii were only consider from 18 to 42 C due to a lack of model t for the full thermal range. Net photosynthesis and respiration rates for Desmodesmus sp. also account for coenobia (i.e., cell unit) cell di erence between ambient and warm.

Figure 2

 2 Figure 2.2. Ambient-to-warm ratios of respiration (a, c) and net photosynthesis (b, d) for two contrasting thermal genotypes of C. reinhardtii (a-b) and Desmodesmus sp.(c-d). Ambient-to-warm (A/W) ratios are calculated using the predicted values of Sharpe-School eld models for each parameter. Units of both parameters are mg O2 L -1 min -1 µm -3 . Values of A/W ratios below unity correspond to thermal areas where warm-origin genotypes respire or photosynthesised more than ambient ones. Conversely, for values larger than one, ambient-origin genotypes outscore those of warm origin.

Figure 2

 2 Figure 2.3. ermal performance curves (TPCs) of respiration for two thermal contrasting populations of D. pulex. In a) respiration rate is expressed as Joules per litre, hour and individual (units: J/l h ind.), and in b) the same respiration rate corrected by mean body mass per replicate (units: J/l µg). TPC trends depict calculated predicted values using Sharpe-School eld model and points denote raw values (n= 48 for each thermal population). TPC trends depicted in light colours denote nonparametric bootstrapping estimating model uncertainty and con dence intervals for each population. Colours of data points and predictions represent populations' thermal origin, in blue for ambient-origin organisms and in red for warm-origin organisms.

Figure 2

 2 Figure 2.4. E ects of temperature on Daphnia pulex mass-corrected ingestion rates when feeding on C. reinhardtii (a) or Desmodesmus sp. (b). Ingestion rates are calculated in Joules per litre, hour and µg per replicate for feeding either on ambient-origin algal populations in blue or warm-origin populations in red. Data points denote raw values (n = 6 per tested temperature, hence N = 96 by algal species, with the exception of 2 outliers for C. reinhardtii and 1 for Desmodesmus sp.). Formulas above represent linear models' formulas with tting (R 2 ) by thermal origin (see Tables 2.2 and 2.3 for statistical details).

Figure 2

 2 Figure 2.5. ermal performance curves (TPCs) of energy gain and loss (a, c) and energetic balances (b, d) for ambient (a, b) and warm (c, d) adapted populations of C. reinhardtii. In a) and b), red corresponds to per capita respiration rates, and blue to per capita net photosynthesis rates, both corrected by cells' biovolume (µm 3 ). TPC trends depict calculated predicted values using the nonlinear Sharpe-School eld equation model. Bold points represent mean values with error bars showing ± SEM (n = 6). Light points denote raw values. In b) and d), energetic balances are computed as the net photosynthesis (P) to respiration (Rr) ratio (P/Rr) using predicted values of each rate obtained from models. Vertical black-dashed lines correspond to temperatures at which the maximal value of the energetic balance is obtained (ambient Tm = 30.7 C and warm Tm = 29 C) and the crossover temperature (ambient Tc = 37.01 C, warm Tc = NA) when the P/Rr ratio equals one. Vertical coloured dashed lines depict optimum temperatures of net photosynthesis in blue (ambient T opt P = 31.6 C, warm T opt P = 32.1 C) and respiration in red (ambient T opt R = 38.6 C, warm T opt R = 40.2 C).

Figure 2 .

 2 Figure 2.6. ermal performance curves (TPCs) of energy gain and loss (a, c) and energetic balances (b, d) for ambient (a, b) and warm (c, d) origin populations of Desmodesmus sp. In a) and b), red corresponds to per capita respiration rates, and blue to per capita net photosynthesis rates, both corrected by cells' biovolume (µm 3 ). TPC trends depict calculated predicted values using the nonlinear Sharpe-School eld equation model. Bold points represent mean values with error bars showing ± SEM (n = 6). Light points denote raw values. In b) and d), energetic balances are computed as the net photosynthesis (P) to respiration (Rr) ratio (P/Rr) using predicted values of each rate obtained from models. Vertical black-dashed lines correspond to temperatures at which the maximal value of the energetic balance is obtained (ambient Tm = 30.7 C and warm Tm = 14 C) and the crossover temperature (ambient Tc = NA, warm Tc = NA) when the P/Rr ratio equals one. Vertical coloured dashed lines depict optimum temperatures of net photosynthesis in blue (ambient T opt P = 26.7 C, warm T opt = 30.4 C) and respiration in red (ambient T opt R = 39.3 C, warm T opt R = 39.5 C).

Figure 2 .

 2 Figure 2.8. ermal reaction norms of energy gain and loss corrected by consumer biomass (a, c) and energetic balances (b, d) for two thermal contrasting populations of D. pulex, from ambient (a-b) or warm origin (c-d), feeding on C. reinhardtii from the same thermal source. In a) and c), red corresponds to energy loss (biomass corrected respiration rates), and blue to energy gain (biomasscorrected ingestion rates) both transformed into energy equivalents (J L -1 h -1 µg -1 ). e thermal norm of consumer respiration depicts calculated predicted values using a Sharpe-School eld model, and ingestion rates depict calculated predicted values for each interacting pair using GLMs. Bold data points represent mean values with error bars showing ± SEM (n = 6 replicates per tested temperature for each parameter). Light points denote raw values. In b) and d), the energetic balance is calculated as the ingestion (I) to respiration (R) ratio for ambient consumer-resource pair (b) or for warm origin pair (d). e horizontal black dotted line indicates a value of I/R ratio equal to one, where energy gain equals loss. Vertical black-dashed lines show critical temperatures (T c ; I/ R ratio = 1) occurring at 20.7 C ambient pairs and at 22.5° C for warm pairs. Vertical dashed lines in red depict the optimum temperature of D. pulex respiration rates (T opt Amb = 30.07° C, T opt Warm = 32.98 °C).

Figure 2 . 7 .

 27 Figure 2.7. Ratios of energetic balances for ambient to warm populations of resource species, C. reinhardtii (a) and Desmodesmus sp. (b). Ratios are calculated using predicted values of energetic balances for ambient-and warm-origin populations of each species, for instance for C. reinhardtii we use predictions presented in Figs 2.5b and 2.5d, and for Desmodesmus sp. those presented in Figs 2.6b and 2.6d.

Figure 2 .

 2 Figure 2.9. ermal reaction norms of energy gain and loss corrected by consumer biomass (a, c) and energetic balances (b, d) for two thermal contrasting populations of D. pulex, from ambient (a-b) or warm origin (c-d), feeding on Desmodesmus sp. from the same thermal source. In a) and c), red corresponds to energy loss (biomass-corrected respiration rates), and blue to energy gain (biomass corrected ingestion rates) both transformed into energy equivalents ((J L -1 h -1 µg -1 ). e thermal norm of consumer respiration depicts calculated predicted values using a Sharpe-School eld model, and ingestion rates depict calculated predicted values for each interacting pair using GLMs. Bold data points represent mean values with error bars showing ± SEM (n = 6 replicates per tested temperature for each parameter). Light points denote raw values. In b) and d), the energetic balance is calculated as the ingestion (I) to respiration (R) ratio for ambient consumer-resource (b) or for warm origin pair (d). e horizontal black dotted line indicates a value of I/R ratio equal to one, where energy gain equals loss. Vertical black-dashed lines show critical temperatures (T c ; I/ R ratio =1) occurring at 20.7° C ambient pairs and at 22.5° C for warm pairs. Vertical dashed lines in red depict the optimum temperature of D. pulex respiration rates (T opt Amb = 30.07 C, T opt Warm = 32.98° C).

Figure 2 .

 2 Figure 2.10. Ratios of energetic balances for ambient to warm populations of D. pulex feeding on C. reinhardtii (a) or Desmodesmus sp. (b). Ratios are calculated using predicted values of energetic balances for ambient and warm populations on each algal species, for instance for C. reinhardtii we use predictions presented in Figs 2.8b and 2.8d, and for Desmodesmus sp. those presented in Figs 2.9b and 2.9d.

Figure 2 .

 2 Figure 2.11. E ects of temperature on per capita interaction strength between Daphnia pulex and C. reinhardtii (a) or Desmodesmus sp. (b). Interaction strengths are computed as the log response ratio of D. pulex from ambient thermal origin (in blue) or warm thermal origin (in red) on resources from the same background thermal histories. Data points denote raw values (n = 6 per tested temperature, hence N = 96 by algal species, with the exception of 4 outliers for C. reinhardtii and 3 for Desmodesmus sp.). Formulas above represent linear models' formulas with tting (R 2 ) distinguishing by thermal origin (seeTable 2.4 for statistical details).

  To test the e ects of both temperature and populations' thermal origin, on growth rates we tted the r data to a Sharpe-School eld model[START_REF] School Eld | Non-linear regression of biological temperature-dependent rate models based on absolute reaction-rate theory[END_REF][START_REF] Barneche | Warming impairs trophic transfer e ciency in a long-term eld experiment[END_REF]. is model (equation 2) characterises a classical ermal Performance Curve (TPC) and is de ned by four parameters:[2]

Figure 3 . 1 .

 31 Figure 3.1. Thermal Performance Curves (TPCs) of intrinsic growth rates, r, of two contrasting thermal populations of C. reinhardtii (a) and Desmodesmus sp. (b). Data points denote replicate values of growth rates for each population at each test temperature (n=6 for C. reinhardtii and n=4 for Desmodesmus sp.). TPC trends depict calculated predicted values of Sharpe-Schoolfield models. TPC trends in light colours denote nonparametric bootstrapping estimating model uncertainty and confidence intervals for each population. Blue colour corresponds to ambient origin and red to warm-origin genotypes.

Figure 3 .

 3 Figure 3.2. ermal dependencies of carrying capacity, K, corrected by mean cell volume and cell-aggregate di erences (µm 3 ml -1 ) of two contrasting thermal populations of C. reinhardtii (a) or Desmodesmus sp. (b). Data points denote the K values in blue colour for the ambient, and in red for the warm genotypes (n = 6 for C. reinhardtii and n = 4 for Desmodesmus sp. at each experimental temperature). e solid lines and shaded regions represent the predictions and 95% con dence intervals of the linear models for each genotype. Equations above represent linear models with tting (R 2 ) by thermal origin (see Table3.2 for statistical details).

Figure

  Figure 3.3. ermal Performance Curves (TPCs) of nitrate removal rates (mg NO 3 -L -1 h -1 µm 3 ) of two contrasting thermal populations of C. reinhardtii (a) and Desmodesmus sp. (b). Data points denote the values of nitrate removal rates (mg NO 3-L -1 h -1 cell -1 ) corrected by mean biovolume (µm 3 ), as well as by cell aggregate and size di erence. ermal response trends depict predicted values of Sharpe-School eld models for C. reinhardtii and a logarithmic model for Desmodesmus sp. In (a) thermal response trend TPC trends depicted in light colours denote nonparametric bootstrapping estimating model uncertainty and con dence intervals for each genotype. In (b) solid lines and shaded regions represent the predictions and 95% con dence intervals of the logarithmic models for each genotype. Blue colour corresponds to ambient origin and red to warm origin isolates.

Figure 4 . 1 .

 41 Figure 4.1. Experimental design comparing the e ects of acute and life-long exposure to temperature on survival rates and life-long exposures on demographic traits. We isolated two contrasting thermal populations of Daphnia pulex from a long-running study of experimental warming in arti cial ponds in Dorset, UK, that experienced up to 14 years of either ambient or ambient +4 °C conditions. We cultured them in common garden conditions in incubators for more than 15 generations and then exposed them to either acute (i.e., short-term, c. 1.5-2.5 h) or lifetime (i.e., long-term, up to 100 days) exposure to temperature and measured survival rates. In addition, we also measured additional demographic traits such as intrinsic growth rates, net reproductive rates and generation times for both thermal populations.

Figure 4 . 2

 42 Figure 4.2 Kaplan-Meier life-long survival curves for two contrasting thermal populations of D. pulex at di erent growth temperatures: 14 (a), 18 (b), 22 (c) and 26 °C (d). Colours of survival curves denote the thermal origin of Daphnia populations, in blue for ambient-origin organisms and in red for warm-origin organisms. Shaded areas around the lines represent the 95 % con dent intervals. e p-value represent the probability that survival curves of both Daphnia population origins are equal at each eassay temperature (α = 0.05), derived from the Kaplan-Meier statistical method.

Figure 4 . 3

 43 Figure 4.3 Survival curves and LT50 estimates (i.e., time when 50% of the individuals of died) for two contrasting thermal populations of D. pulex exposed to acute temperature conditions. Survival curves are calculated tting survival data of individuals used in both ingestion (n= 192) and respiration (n = 96) experiments to a negative logistic curve. Blue depicts ambient thermal origin of daphnids, and red, warm origin (n = 144, for each thermal population). Estimates of LT50 for both survival curves is marked on the temperature axis by a population-coloured triangle. Filled coloured-squares on value 0.50 of Daphnia survival show the 95% con dence intervals of LT50 for each thermal population.

Figure 4 .

 4 Figure 4.4. E ects of rearing temperatures and thermal origin of two thermal contrasting populations of D. pulex on growth rates, r. I calculated growth rates from the Euler equation for daphnids growing at four temperatures: 14, 18, 22 and 26°C. Blue colour corresponds to ambient origin and red to warm origin populations (n=5 at each rearing temperature). Data are plotted as treatment means with error bars ± 1 s.e.m.

Figure 4 .

 4 Figure 4.5. E ects of rearing temperature and thermal origin of two thermal contrasting populations of D. pulex on net reproductive rates, R 0 for daphnids growing at four temperatures: 14, 18, 22 and 26 °C. Reproductive rates represents the number of o spring produced by a female during its lifespan. Blue colour corresponds to ambient-origin and red to warm-origin populations (n=5 at each rearing temperature). Data are plotted as treatment means with error bars ± 1 s.e.m.

Figure 4 .

 4 Figure 4.6. E ects of rearing temperature and thermal origin of two thermal contrasting populations of D. pulex on generation times, G at four temperatures: 14, 18, 22 and 26°C. Generation times represents the average age of all of the parents of o spring produced by a single cohort. Blue colour corresponds to ambient origin and red to warm origin populations (n=5 at each rearing temperature). Data are plotted as treatment means with error bars ± 1 s.e.m.

  Fig. GD.1. is type of model describes the rate of change in consumer (equation 1) and resource (equation 2) densities over time, in a simpli ed way (see General Introduction):

Figure GD. 1 .

 1 Figure GD.1. Summary of key ndings of this thesis contained in di erent chapters.Each chapter covers the study of thermal dependencies, and potential evolutionary responses, of di erent constituent parameters of consumer-resource models. Chapter 1 explores the thermal dependency of linear functional response, f, based on energetic balances of interacting species. Chapter 2 focuses on the evolutionary responses to temperature of interaction strength based on individual species traits related to energy gain and loss. Chapter 3 examines the temperature dependencies and evolutionary responses of resource traits, such as growth rate, r, and carrying capacity, K. Finally, Chapter 4 focuses on consumer's traits, investigating mortality (i.e., parameter m) by estimating survival to temperature across two temporal scales, as well as other important demographic traits using two thermal contrasting populations of consumers.

Figure S1. 1 .

 1 Figure S1.1. Possible scenarios of interspeci c thermal mismatches (Inter-TM) in a consumerresource interaction. Energetic balances (i.e. gain-to-loss ratios) on the top represent those of the consumer and on the bottom, those of the resource. Coloured shaded-regions depict energetic balance trends with increasing temperatures, in blue rising trends, and in orange and red declining trends over and below unity respectively. Scenario (a) depicts no inter-TM while b)and c) show cases of inter-TM. In (a) the thermal dependency of consumer energetic balance matches that of the resource, so no mismatch in the interaction is expected. At low temperature (i), increases of temperature lead to increases of energy availability for both organisms. en, at intermediate temperatures (ii), increases of temperature reduce the energy availability for both organisms, causing intraspeci c thermal mismatches (Intra-TM) in both species. us, both organisms su er from energy de cits in the same way with temperature. Finally, at high temperatures (iii), the ratio falls below 1 for both species, meaning that the energy gain cannot compensate for the energy loss, so energy de cits will be strong for both organisms. In (b) thermal dependency of the consumer energetic balance di ers from that of the resource, so inter-TMs are expected with the consumer a ected from energy de cits at lower temperatures than the resource. At low temperature (i), increases of temperature translate into an increase of energy availability for both organisms.en, at intermediate temperatures (ii), increases of temperature reduce the energy available to the consumer, but not the resource, which still increases. is causes an inter-TM because the consumer su ers from energy de cits while the energy available to the resource still increases with temperature. At high temperatures (iii), the consumer struggles to cope with energy losses as the ratio falls below 1, while the resource species still maintains an energy balance over unity. However, increases of temperature in this thermal region will reduce the energy available for resource species. In (c) similarly to (b), thermal dependency of the energetic balance of consumer di ers from that of the resource, so an inter-TM is expected, but the resource su ers from energy de cits at lower temperatures compared to the consumer. Predicted temperature scenarios (i, ii, iii) of case (c) show the opposite situation compared to those in scenario (b), with the resource instead su ering from energetic de cits at lower temperatures than does the consumer. In nature, scenarios a) and b) are most likely to happen for ectothermic species, while case c) may occur hypothetically in a situation where an endotherm feeds on a thermally sensitive ectotherm.

Figure S1. 2 .

 2 Figure S1.2. Consumer and resource species' thermal mismatches based on species energetic balances from results. Energetic balances (i.e. gain-to-loss ratios) are calculated from predicted values of energy gain and loss parameters. On the top represent those of the consumer, calculated as the ingestion-to-respiration ratio, feeding either on Chlamydomonas reinhardtii (1-a) or Desmodesmus sp. (2-b). On the bottom, energetic balances of resource species (Chlamydomonas reinhardtii 1-c, Desmodesmus sp. 2-d) are calculated as net photosynthesis-to-respiration ratio.Coloured regions depict energetic balance trends with increasing temperatures. In blue rising trends, and in orange and red declining trends over and below unity respectively. Black arrows show species' intraspeci c thermal mismatches, i.e., negative e ects on species energetic balances due to warming. Red arrows show interspeci c thermal mismatches between interacting species with two distinguishable thermal regions, where: 1) trends of energetic balances contrast between the interacting species; and 2) both species reduce their energetic balance with increasing temperature. Vertical coloured-dashed lines in black depict the temperature at which the G/L ratio is maximized (Tm) and the crossover temperature (Tc) where energy gain equals energy loss (ratio = 1). In blue and red, vertical-dashed lines depict optimum temperatures for net photosynthesis and respiration respectively.

  Fig. 5. Values presented here come from linear models testing the e ect of temperature on IS values for each algae species in the form of: model = lm(IS ~ Temperature). To estimate the slopes we used emtrends(model, "Algae Species", "Temperature") and for the intercepts emmeans(model, "Algae species",by="Temperature", at = list(Temperature = 0). Highlighted estimates of p-values represent signi cance levels lower than 0.05.

  ) and converted minutes to hours by multiplying R c by 60: us, we have: (eq. S3)

Figure S2. 1

 1 Figure S2.1 Biovolume and biomass di erences between populations from two thermal origins of C. reinhardtii (a), Desmodesmus sp. (b) and D. pulex (c) respectively. Colours depict thermal origin of species' populations, in blue ambient origin, and in red, warm origin. We compute algal biovolume using manual measurements (width and length) of more than 142 cells of C. reinhardtii (ambient n=72, warm n= 70) and 288 cells of Desmodesmus sp. (ambient and warm n= 144). en, biovolume was calculated using the formula of a spheroid in µm 3 . For C. reinhardtii populations, we analysed biovolume di erence using the Welch's t-test -unequal population variances, but normality assumed -and for Desmodesmus sp. the non-parametric Mann-Whitney test. For D. pulex, we used all the manual measurements of length for experimental individuals used in respiration and ingestion experiments. Each data point in c) represents the average body mass among ve individuals contained in each replicate a er conversion into biomass using a conversion factor between body length and mass, and assed the di erences by a Student t-test.

Figure S3. 1 .

 1 Figure S3.1. Thermal dependencies of carrying capacity, expressed as cells/ml for two contrasting thermal populations of C. reinhardtii (a) and Desmodesmus sp. (b). Data points denote densities at carrying capacity in blue colour for ambient, and red for warm populations (n = 6 for C. reinhardtii n = 4 for Desmodesmus sp. at each tested temperature). Equations above represent linear models with fitting (R 2 ) by thermal origin (see Table3.2 for statistical details).

Figure S3. 2 .

 2 Figure S3.2. Biovolume differences across temperatures between populations from two thermal origins of C. reinhardtii (a) and Desmodesmus sp. (b).Colours depict thermal origin of species' populations, in blue ambient-origin, and in red, warm-origin. Formulas above represent linear models' formulas with fitting (R 2 ) by thermal origin (see tableS3.1 for statistical details).

Figure S3. 3 .

 3 Figure S3.3. Biovolume di erences between populations from two thermal origins of C. reinhardtii (a) and Desmodesmus sp. (b).Colours depict thermal origin of species' populations, in blue ambient origin, and in red, warm origin. We compute algal biovolume from FSC ow cytometry laser data (see methods in in Appx. B Supp. Methods S2.1). for each replicate when populations achieved stationary phase in the growth curve, so at the end of the growth experiments. For both algal species we assessed the median biovolume di erences using a Mann-Whitney statistical test, the non-parametric alternative to the unpaired two-samples t-test.

Figure S4. 1 .

 1 Figure S4.1. Overall survival curves for two contrasting thermal populations of D. pulex in a) from ambient-origin and in b) from warm-origin at di erent growing temperatures. Colours of survival curves depict the rearing temperature for each thermal population, dark-blue represents rearing temperatures at 14°C, in light-green at 18°C, in yellow at 22°C and in red for individuals reared at 26°C. e p-value represent the probability that survival curves of Daphnia reared at di erent four temperatures are equal across rearing temperatures. is value is derived from the Kaplan-Meier statistical method. Signi cance levels considered for p-value lower than 0.05.

Figure S4. 2 .

 2 Figure S4.2. Di erences in D. pulex size at death between thermal origins and growing temperatures. Data points denote values of Daphnia body size measured as length in mm for each replicate (n=30 at each rearing temperature) at four temperatures, 14, 18, 22 and 26°C. Tops and bottoms of boxes correspond, respectively, to the 25th and 75th percentiles, horizontal lines correspond to medians, and whisker extents correspond to 1.5 × the interquartile range. Blue colour corresponds to ambient origin and red to warm origin populations.

Figure S4. 3 .

 3 Figure S4.3. Body size di erences between two contrasting thermal populations of D. pulex grown at four di erent temperatures, 14 (a), 18 (b), 22 (c) and 26 (d) °C. Data points denote values of Daphnia body size measured as length in mm for each replicate at each growing temperature. We removed outliers following the methods in Appx. A. S1.4. Tops and bottoms of boxes correspond, respectively, to the 25th and 75th percentiles, horizontal lines correspond to medians, and whisker extents correspond to 1.5 × the interquartile range. Violin shapes show the kernel probability density of the data at di erent length values. Blue colour corresponds to ambient origin and red to warm origin populations. Statistical summaries on top of each temperature treatment show statistical tests outputs for means and median di erences. we assessed di erences between thermal populations in mean Daphnia lengths in a) and d), and in median lengths in b) and c). For each growing temperature, if data complied with parametric assumptions we used a t-test (normal distribution and homoscedasticity) or a Welch's t-test (normal distribution but heteroscedasticity), otherwise we employed non-parametric Mann-Whitney statistical tests (b, c).

Figure S4. 4 .

 4 Figure S4.4. Body size (mm) distributions of two contrasting thermal populations of D. pulex grown at four di erent temperatures, 14 (a), 18 (b), 22 (c) and 26 (d) °C. Histogram plots represent frequency of Daphnia body size distribution measured as body length (mm) at death. Blue colour corresponds to ambient origin and red to warm origin populations. Vertical dashed lines depict mean body length for each thermal origin population at each growing temperature.

  [START_REF] Iles | Toward predicting community-level e ects of climate: Relative temperature scaling of metabolic and ingestion rates[END_REF][START_REF] Listmann | Swi thermal reaction norm evolution in a key marine phytoplankton species[END_REF][START_REF] Pad Eld | Rapid evolution of metabolic traits explains thermal adaptation in phytoplankton[END_REF][START_REF] Schaum | Adaptation of phytoplankton to a decade of experimental warming linked to increased photosynthesis[END_REF][START_REF] Jin | Fast adaptation of tropical diatoms to increased warming with tradeo s[END_REF][START_REF] Liang | Molecular mechanisms of temperature acclimation and adaptation in marine diatoms[END_REF]. ese thermal adaptations potentially translated into direct positive impacts on ecosystem functioning, such as signi cant increases in primary production, which can lead to increases in carbon sequestration by the evolved populations[START_REF] Pad Eld | Rapid evolution of metabolic traits explains thermal adaptation in phytoplankton[END_REF][START_REF] Schaum | Adaptation of phytoplankton to a decade of experimental warming linked to increased photosynthesis[END_REF]. Adaptive responses to warming have also been observed for consumers such as the water eaDaphnia (van Doorslaer et al. 2009;[START_REF] Van Doorslaer | Experimental thermal microevolution in community-embedded Daphnia populations[END_REF][START_REF] De Block | Local genetic adaptation generates latitude-speci c e ects of warming on predator-prey interactions[END_REF][START_REF] Geerts | Rapid evolution of thermal tolerance in the water ea Daphnia[END_REF][START_REF] Riessen | Water temperature alters predation risk and the adaptive landscape of induced defenses in plankton communities[END_REF]

Table 2 .3. Statistical results of two-way ANOVA for the e ects of temperature and populations' thermal origin on mass-corrected ingestion rates (J L -1 h -1 µg -1 ) in a short-term experiment with Daphnia pulex feeding either on C. reinhardtii or Desmodesmus sp

 2

	Algal species fed upon	T. origin Parameter	Estimate	SE		t-value p-value R2
				Intercept	0.0554	0.0194		2.864	0.005
			A					0.15
				Slope	-0.00156	0.000715	-2.178	0.032
	C. reinhardtii			Intercept	0.0492	0.0189		2.597	0.01
			W					0.03
				Slope	-0.00104	0.000689	-1.512	0.134
				Intercept	0.00836	0.0137		0.607	0.545
			A					0.03
				Slope	0.00067	0.0005		1.337	0.184
	Desmodesmus sp.		Intercept	0.0497	0.0136		3.646	<0.001
			W					0.06
				Slope	-0.0007	0.0004		-1.460	0.147
	Response	Algal species		Parameter		df	MS	F	p-value
	Ingestion	C. reinhardtii		Temperature		1	0.0082	6.61	0.012
				ermal origin		1	0.0012	1.01	0.318
				Temperature: ermal origin	1	0.0003	0.27	0.604
				Residuals		90	0.0353
		Desmodesmus sp.	Temperature		1	0.000007 0.0109	0.917
				ermal origin		1	0.000469 0.7263	0.396
				Temperature: ermal origin	1	0.002522 3.9096	0.05
				Residuals		91	0.0254

. Daphnia populations were only paired with resources from the same thermal origin, i.e., ambient-origin consumers with ambientorigin resources and vice versa. e full model tests the e ect of temperature on ingestion values with interaction of thermal origin in the form of lm(ingestion ~ Temperature * thermal origin), for C. reinhardtii: F 3,90 = 2.631, p = 0.05, and R2 = 0.08; and for Desmodesmus sp.: F 3,91 = 1.55, p = 0.2, and R2 = 0.04. Highlighted estimates of p-values represent signi cance levels lower than 0.05.

Table 2

 2

.4 for statistical details).

Table 3 .2. Statistical results of the e ects of temperature and populations' thermal origin on densities at carrying capacity, K (µm 3 ml -1 ), for two freshwater algal species, C. reinhardtii and Desmodesmus sp

 3 . e table shows independent model outputs for each algal species: a two-way ANOVA test for C. reinhardtii and a non-parametric Permutational ANOVA for Desmodesmus sp. (see methods in section 3.3). Highlighted estimates of p-values represent signi cance levels lower than 0.05.

	Response	Algal species	Parameter	df	MS	F-model	p-value
			Temperature	1	3.601e+18	78.12	< 0.001
			ermal origin	1	1.241e+18	26.91	< 0.001
		(a) C. reinhardtii	Temperature: ermal origin	1	2.763e+17	5.99	0.016
			Residuals	92	4.610e+16
	Carrying capacity, K
			Temperature	1	8.1103e+17	5000*	< 0.001
			ermal origin	1	1.4273e+18	5000*	< 0.001
		(b) Desmodesmus sp.	Temperature: ermal origin	1	1.1370e+15	51*	0.82
			Residuals	60	2.4570e+16

* Interations

Table 4 .2. Statistical results of Permutational analysis of variance (Per-ANOVA) for the e ects of temperature and Daphnia thermal origin on growth rates (day -1 )

 4 . e table shows model outputs for the permutational ANOVA (adonis function). Highlighted estimates of p-values represent signi cance levels lower than 0.05.

	Response	Parameter	df	MS	F-model	R2	p-value
	Growth rates (r)	Temperature	1	1.67	82.952	0.695	0.001
		ermal origin	1	0.0017	0.087	0.0007	0.913
		Temperature: ermal origin	1	0.0055	0.274	0.002	0.716
		Residuals	182	0.0201		0.3

Table 4 .3. Statistical results of two-way ANOVA for two separate models testing the e ects of temperature and populations' thermal origin on two D. pulex demographic traits

 4 . e full model tests the e ect of temperature on di erent demographic traits with interaction of thermal origin in the form of lm(trait ~ Temperature * thermal origin), for Net reproductive rate (R 0 ): F 7,32 = 9.518, p < 0.001, and R2 = 0.67; and for Generation times (G).: F7,31 =26.22, p < 0.001, and R2 = 0.85. Highlighted estimates of p-values represent signi cance levels lower than 0.05.

	Response	Parameter	df	MS	F	p-value
	Net Reproductive rate (R 0 )	Temperature	3	2144.1	21.27	< 0.001
		ermal origin	1	0.1	0.001	0.979
		Temperature: ermal origin	3	94.9	0.941	0.432
		Residuals	32	100.8
	Generation times (G)	Temperature	3	735.6	60.48	< 0.001
		ermal origin	1	0.5	0.043	0.837
		Temperature: ermal origin	3	8.2	0.677	0.573
		Residuals	32	12.2

Table 4 .4. Statistical results of contrast analysis between ambient and warm thermal origin of daphnids for the e ects of temperature and populations' thermal origin on di erent D. pulex demographic traits.

 4 Demographic traits measured are net reproductive rate (R 0 ) and generation time (G). We employed a contrast analysis between ambient and warm-origin populations for each demographic trait independently running pair-wise comparisons with the emmeans and pairs functions of the `emmeans` package. Highlighted estimates of p-values represent signi cance levels lower than 0.05.

	Demogr. trait	Contrast	Temperature Estimate	SE	df	t-ratio	p-value
	Net Reproductive rate (R 0 )	Ambient -warm	14	-2.63	6.35	32	-0.414	0.681
			18	1.40	6.35	32	0.220	0.827
			22	-6.42	6.35	32	-1.011	0.320
			26	7.99	6.35	32	1.258	0.217
	Generation times (G)	Ambient -warm	14	1.76	2.21	32	0.798	0.430
			18	-2.30	2.21	32	-1.04	0.305
			22	0.16	2.21	32	0.073	0.942
			26	1.23	2.21	32	0.586	0.562

Table S1 .4. Statistical results of ANOVA for the e ects of temperature and algae species on interaction strength in a short-term experiment with Daphnia pulex feeding either on C. reinhardtii or Desmodesmus sp.

 S1 For the full model testing the e ect of temperature on IS values with interaction of algae species in the form of lm(IS ~ Temperature * Algae species), F 90 = 9.97, SE = ± 0.009 , p = 0.00215, and R 2 = 0.2717. Highlighted estimates of p-values represent signi cance levels lower than 0.05.

	Response		Parameter			df MS		F	p-value
	Species C. reinhardtii Interaction Strength	Rate Respiration	Parameter Temperature T ref T ref E a Algal species 7.49e-08 Estimate 6.86e-08 0.57 Temperature: Algal species 4.21e-08 SE 2.76e-08 0.20 E h 13.74 69.54 T h 40.92 5.66 Residuals	t-value p-value 1 0.000084 1.78 0.082 2.48 < 0.01 2.91 < 0.01 1 0.000934 1 0.001544 0.20 0.84 7.22 < 0.001 90 0.0000763	Residual standard 1.10 DF error 1.343e-07 44 12.24 < 0.001 Num. 0.29699 convergence 20.24 < 0.001 41
		Net photosynthesis	E a E h	1.44 5.27	0.34 1.17	4.27 4.48	< 0.001 < 0.001	3.014e-07 44	50
			T h	33.16	0.99	33.39	< 0.001
			T ref	6.446e-09	3.378e-09 1.91	0.06
		Respiration	E a E h	0.50 20.00	0.26 827.9	1.91 0.02	0.06 0.98	1.557e-08 44	52
	Desmodesmus sp.		T h T ref	40.89 3.998e-08	45.82 8.059e-09 4.961 0.89	0.37 < 0.001
		Net photosynthesis	E a E h	0.66 1.66	0.44 0.34	1.49 4.83	0.14 < 0.001	2.587e-08 44	59
			T h	29.38	7.75	3.79	< 0.001
			T ref	0.655	1.681e-04 3.899	< 0.001
	D. pulex	Respiration	E a E h	1.078 1.993	0.457 0.3605	2.356 5.527	0.02 < 0.001	0.0005772 44	20
			T h	28.74	5.403	5.320	< 0.001

Table S1.5. E ect of temperature on Interaction Strength (IS) values of D. pulex feeding either on C. reinhardtii or Desmodesmus sp. Model summary from the results presented in

  Ecological and evolutionary implications of warming on predator-prey dynamics

	Species	Rate	ermal origin	Parameter	Estimate	SE	t-value	p-value	Residual standard error	DF	Num. iterations convergence
				T ref	7.344e-11	3.905e-11	1.881	0.066
			Ambient	E a E h	0.50 20	0.264 80.24	1.899 0.025	0.064 0.9802	1.803e-10	44	68
	Species	Rate Respiration	ermal origin	Parameter T h T ref	Estimate 40.88 7.496e-11	SE 45.12 5.863e-11	t-value 0.906 1.278	p-value 0.3699 0.2078	Residual standard error	DF	Num. iterations convergence
	Desmodesmus sp.	Respiration	Ambient Warm Ambient	T ref E a E a E h E h T h T h T ref T ref E a E h	3.400e-10 0.55 0.70 20 11.67 40.78 40.97 4.677e-10 3.988e-10 0.783 1.624	1.318e-10 0.189 0.366 1.114e+03 28.12 3.17 57.38 1.016e-10 1.546e-10 0.535 0.282	2.580 2.911 1.911 0.018 0.415 12.865 0.714 4.603 2.580 1.464 5.758	0.013 0.0625 0.9858 0.005 0.680 0.4790 < 0.001 < 0.001 0.014 0.150 < 0.001	6.305e-10 3.175e-10 2.958e-10	44 44 44	54 55 64
		Net photosynthesis	Warm	E a E h T h T ref	0.315 20 27.07 2.578e-10	0.202 9.343e+03 8.079 1.136e-10	1.555 0.002 3.351 2.268	0.128 0.998 < 0.001 0.028	5.034e-10	38	57
	C. reinhardtii		Warm	T h T ref E a E h	42 3.687e-10 0.63 2.334	43.07 2.045e-10 1.16 1.162	97.521 1.802 1.329 2.009	< 0.001 0.07 0.1907 0.050	4.056e-10	44	82
			Ambient	E a T h E h T ref	1.42 33.81 5.373 0.011	0.33 6.653 1.262 0.002	4.288 5.082 4.257 4.613	< 0.001 < 0.001 < 0.001 < 0.001	1.444e-09	44	53
	D. pulex	Net photosynthesis Respiration	Warm Ambient Warm	T h E a E h T ref E a E h T h T ref T h E a E h	33.18 1.375e-09 0.854 2.135 0.543 2.63 31.58 0.010 36.19 0.587 9.711	0.971 2.596e-10 0.321 0.614 0.165 0.713 4.354 0.003 2.30 0.178 5.634	34.163 5.296 2.657 3.475 3.292 3.692 7.254 3.137 15.674 3.299 1.724	< 0.001 < 0.001 0.01 0.001 0.001 < 0.001 0.003 < 0.001 < 0.001 0.001 0.091	0.00849 9.609e-10 0.01435	44 44 43	1 76 52
				T h	35.28	0.64817	54.442	< 0.001
	156

Table S3 .1. Statistical results of the e ects of temperature and populations' thermal origin on per capita mean cell volume at carrying capacity (µm 3 cell -1 ), for each of the two freshwater algal species, C. reinhardtii or Desmodesmus sp

 S3 . e table shows model outputs for independent nonparametric permutational ANOVA tests for each algae species (aovp function from the 'lmPerm' package in the form of: summary(aovp(K_data ~ Temperature * ermal origin, data, seqs=T)). Highlighted estimates of p-values represent signi cance levels lower than 0.05.

	Response	Algal species	Parameter	df	MS	Iter	p-value
			Temperature	1	15	0.17	0.486
		C. reinhardtii	ermal origin Temperature: ermal origin 1 1	55526 4	5000 51	< 0.001 1
	Mean cell volume at carrying capacity		Residuals	182	121
	(µm 3 cell -1 )		Temperature	1	487	5000	< 0.001
		Desmodesmus sp.	ermal origin Temperature: ermal origin 1 1	215002 5000 176 1240	< 0.001 0.075
			Residuals	380

Table S4 .1. Statistical results of Permutational analysis of variance (Per-ANOVA) for the e ects of temperature and thermal origin on body size of D. pulex at death (mm

 S4 ). e table shows model outputs for the permutational ANOVA using the adonis function from `vegan` R-package. Highlighted estimates of p-values represent signi cance levels lower than 0.05.

	Response	Parameter	df	MS	F-model	R2	p-value
	Body size	Temperature	1	0.01	2.871	0.013	0.08
		ermal origin	1	0.01	2.946	0.013	0.08
		Temperature: ermal origin	1	0.00045	0.129	0.0006	0.38
		Residuals	221	0.0034		0.97

Acknowledgements

is PhD manuscript is the culmination of four (almost ve) years full of hard work and perseverance. However, this is not the product of a single person. Without the help of supervisors, colleagues, friends and family this work could have never been possible.

's Horizon 2020 research and innovation programme (Grant 441 Agreement Number 726176

Chapter 4

The impact of acute and life-long exposures to temperature on survival and other demographic traits of consumers Keywords: temperature, survival rates, heat tolerance, trade-offs, growth, life-history traits, thermal evolution, zooplankton

Manuscript in prep.

Álvarez-Codesal, S., Faillace, C. A., Garreau, A., Matos L., Lalot B., Synodinos, A. D., & Montoya, J. M.

Appendix A

Supplementary materials for Chapter 1

Table S1.2. Summary table of estimated ermal Performance Curve's (TPC) parameters and con dence intervals of resource and consumer rates. Parameters show mean values of the activation energy (Ea), the optimum temperature (T opt ), the maximum rate of performance (MRP) (i.e., at optimum temperature), and the deactivation energy (E h ) of those rates showing unimodal trends with temperature. Values in brackets show 95% con dence intervals (ci) for each parameter obtained from case bootstrapping. Signi cance codes from the nonlinear regression Sharpe-School eld model parameters (E a , Eh) are: '***' 0.001 '**' 0.01 '*' 0.05. ‡. D. pulex respiration units are Joules Daphnia -1 L -1 h -1 ). 4 testing the e ect of temperature on ingestion rates for D. pulex feeding on each algal species in the form of lm(ingestion ~ Temperature). For the model for C. reinhardtii, F 1,44 = 7.573, while for that of Desmodesmus sp. F 1,45 = 1.187. Highlighted estimates of p-values represent signi cance levels lower than 0.05.

Supplementary methods

S1.1 -Lineage isolation, culturing and timings of experiments

We collected all organisms (consumer and resources) from open-air freshwater mesocosms located at the River Lab, East Stoke, Dorset, UK in 2019. Mesocosms consisted of plastic tanks of approximately 1m 3 volume and 50 cm depth that mimicked small shallow freshwater systems uctuating naturally with air temperature (unheated ponds -Yvon-Durocher et al. 2011). We collected phytoplankton samples in January 2019 by serial ltration of approximately 212 L of water from eight mesocosms. We targeted the 2-30 µm fraction for small phytoplankton species. Over the next three months, we pre-isolated algal species by transferring single cells into COMBO medium [START_REF] Kilham | COMBO: A de ned freshwater culture medium for algae and zooplankton[END_REF]) using microcapillary pipetting under an inverse microscope (Nikon Eclipse Ts2R). We gradually adjusted the maintenance conditions of pre-isolated populations from the eld conditions, 6 C and 8L:16D photoperiod, to culture conditions at 18 C and 12L:12D over a period of ve weeks in laboratory incubators (Panasonic MLR-352-PE) and with a light PAR intensity of 67 -70 µmol m -2 s -1 . Next, we streaked isolates on agar plates to reduce bacterial contamination and enhance isolation.

In April 2019, we isolated targeted algal species from our "pre-isolated" cultures using a sorting ow cytometer FACSCanto II at the CNRS Arago Laboratory, in Banyuls-sur-Mer, France. is technique allowed us to obtain pure clonal lineage cultures by sorting single cells from our highly dense and fairly clean samples of our pre-isolates. e ow cytometer allowed us to select and transfer single cells in each well of a 96-well plate containing 200 µl volume of medium. Clonal linages were maintained in the same incubator conditions previously described. A month later (May 2019) viable cultures-those where algal densities were visually high-from the clonal lineages in -96well plates were transferred into 2 ml volume of medium and since then maintained in semi-continuous batch cultures until the start of the experiments. Maintenance consisted of transferring %10 of the old sample (20 µl) into 2 ml of fresh medium every two weeks.

In Autumn 2019 we used 18S rDNA sequencing to identify unique clonal lineages of our species. Large volumes of dense samples of clonal lineages were freeze-dried and sent to the Integrated Microbiome Resource lab at Dalhousie University (Halifax, Canada) for extraction, library preparation, and sequencing according to the procedures described in [START_REF] Comeau | Microbiome Helper: a Custom and Streamlined Work ow for Microbiome Research[END_REF]. Following PCR-ampli cation of amplicon fragments, PacBio Sequel 2 long-read sequencing using full-length 18S fusion primers (forward: NSF4/18 = CTGGTTGATYCTGCCAGT; reverse: EukR = TGATCCTTCTGCAGGTTCACCTAC) identi ed algal clones to species and discriminated among unique clones. We identi ed one unique clone for each of the two species, Chlamydomonas reinhardtii and Desmodesmus sp.

ese clones were subsequently selected for the experiment and kept in semi-continuous batch cultures until the start of the experiments.

Conversion of Daphnia ingestion rates to energetic equivalents

Per capita raw ingestion rate, rI , is measured as the di erence in resource density at the beginning and the end of the experiment in the presence and absence of consumers (consumer and control replicates respectively) and corrected for consumer numbers. erefore: (eq. S4)

where D T0 = algal densities in the Daphnia replicates at the beginning of the experiment (T0), D T150 = algal densities in the Daphnia replicates at the end of the experiment (T150), C o is the mean value of algal densities at the beginning of the experiment (T0) in controls within each of 2 temporal blocks, C 150 is the mean value of algal densities at the end of the experiment (T150) in controls within each of 2 temporal blocks, y = the number of daphnids introduced into each Daphnia replicate, and t is the length of the experiment, 2.5 hours.

Hence, raw ingestion rate has the following units:

(eq. S5)

We next transformed per capita raw ingestion rate, rI, into energetic equivalents of per capita raw ingestion rates, rI E , in order to make ingestion rates (i.e., energy gain) comparable to respiration rates (i.e., energy loss). Units of per capita raw ingestion rates in energy equivalents, rI E , are:

(eq. S6)

We used the following transformation Which means:

(eq. S7)

Supplementary methods

S2.1 -Biovolume and biomass corrections of individual traits

Because body mass of daphnids and biovolume of algae populations di ered signi cantly between thermal origins (Fig. S2.1), we did a mass and biovolume correction respectively to all individual per capita rates of energetic traits, i.e., respiration, net photosynthesis and ingestion.

For biovolume corrections of algal traits, we used the ow cytometry FSC laser data from each individual replicate as a proxy for mean cell length. In a previous pilot experiment we found that FSC data had a good correlation with mean cell length, where cell length (um) = 3.63 + 0.000208 × FSC (R 2 = 0.85).

en, mean cell length was transformed into mean biovolume (µm 3 ) per replicate using the formula of an spheroid: Biovolume (um) = π ⁄ × width 2 × length [START_REF] Hillebrand | Biovolume calculation for pelagic and benthic microalgae[END_REF] where width was set to a xed value for each algal populations, calculated from manual measurements of more than 72 cells per population using an inverse microscope (Nikon Eclipse Ts2R). Also, because populations of Desmodesmus sp. di ered in the frequency of cell aggregates, we corrected the per capita rates corrected by biovolume by the proportion of cell numbers per coenobia. While ambient population showed a larger proportion of 4-celled coenobia (24% singe cells, 30% 2-cells, 46% 4-cells), the warm population showed a higher percentage of single cells instead (71% singe cells, 20% 2-cells, 9% 4-cells).

For experiments with Daphnia, we rst assessed survival at the completion of the experiments as the percentage of daphnids alive per replicate. Immediately a er, we preserved them in 80% ethanol to batch process them for size determination. en, we obtained mean body length (i.e. from top of head to base of tail spine) per replicate measuring all preserved individuals, using a digital stereo microscope (Leica S9i). Generally, the number of daphnids in each replicate were ve, but in some cases some individuals died during the acclimation. Additionally, in exceptional cases some individuals degraded or broke down during preservation, so these were not included in calculations of the means. Mean body mass per replicate was calculated using an speci c conversion factor for Daphnia pulex: m = 10.674 × l 2.093 , where 'l' is length in μm and 'm' mass in μg dry weight [START_REF] Lynch | Measurement of the carbon balance in Daphnia[END_REF], which were then used to correct the per capita rates of Daphnia by mean biomass. Finally, per capita rates, either mass or biovolume corrected, for consumers or resources were transformed into energy equivalents to make quantitatively comparable energy gains and losses (Appx. A. S5). In addition, for ingestion rates of Daphnia, we applied speci c assimilation e ciencies for each resource species upon which the Daphnia fed.