Quentin Queiros
email: quentin.queiros@slu.se

David J Mckenzie

Gilbert Dutto

Shaun Killen

Claire Saraux

Quentin Schull

Fish shrinking, energy balance and climate change

Keywords: size decline, energy expenditure, feeding behaviour, temperature, small pelagic fish, respirometry, experiments

A decline in size is increasingly recognised as a major response by ectothermic species to global warming. Mechanisms underlying this phenomenon are poorly understood but could include changes in energy balance of consumers, driven by declines in prey size coupled with increased energy demands due to warming. The sardine Sardina pilchardus is a prime example of animal shrinking, European populations of this planktivorous fish are undergoing profound decreases in body condition and adult size. This is apparently a bottom-up effect coincident with a shift towards increased reliance on smaller planktonic prey. We investigated the hypothesis that foraging on smaller prey would lead to increased rates of energy expenditure by sardines, and that such expenditures would be exacerbated by warming temperature. Using group respirometry we measured rates of energy expenditure indirectly, as oxygen uptake, by captive adult sardines offered food of two different sizes (0.2 or 1.2 mm items) when acclimated to two temperatures (16°C or 21°C). Energy expenditure during feeding on small items was tripled at 16°C and doubled at 21°C compared to large items, linked to a change in foraging mode between filter feeding on small or direct capture of large. This caused daily energy expenditure to increase by ~10% at 16°C and ~40% at 21°C on small items, compared to large items at 16°C. These results support that declines in prey size coupled with warming could influence energy allocation towards life-history traits in wild populations. This bottom-up effect could partially explain the shrinking and declining condition of many small pelagic fish populations and may be contributing to the shrinking of other fish species throughout the marine food web. Understanding how declines in prey size can couple with warming to affect consumers is a crucial element of projecting the consequences for marine fauna of ongoing anthropogenic global change.

Introduction

Ongoing global warming constitutes a major threat for biodiversity, especially in marine ecosystems, with some scenarios of future temperature increases reaching +5°C in 2100 [START_REF] Ipcc | Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change[END_REF](IPCC, , 2014;;[START_REF] Orr | Anthropogenic ocean acidification over the twenty-first century and its impact on calcifying organisms[END_REF]. For ectotherms such as fishes, warming results in large increases in their physiological rates [START_REF] Clarke | Why does metabolism scale with temperature?[END_REF][START_REF] Seebacher | Physiological plasticity increases resilience of ectothermic animals to climate change[END_REF]. While ongoing global warming might therefore be expected to boost growth rates in ectotherms [START_REF] Morrongiello | Fishing constrains phenotypic responses of marine fish to climate variability[END_REF][START_REF] Seebacher | Physiological plasticity increases resilience of ectothermic animals to climate change[END_REF], it has in fact been correlated with a progressive decline in adult body size of many fish species in the wild (e.g. in [START_REF] Baudron | Warming temperatures and smaller body sizes: synchronous changes in growth of {North} {Sea} fishes[END_REF][START_REF] Gardner | Declining body size: a third universal response to warming?[END_REF][START_REF] Sheridan | Shrinking body size as an ecological response to climate change[END_REF], but see [START_REF] Audzijonyte | Fish body sizes change with temperature but not all species shrink with warming[END_REF]. The factors that contribute to this shrinking of fishes are poorly understood; it is coherent with how warming might affect macroecological phenomena such as Bergmann's rule and James' rule, and is associated with a significantly higher proportion of younger age classes and a generalised decline in individual size-at-age in populations [START_REF] Daufresne | Global warming benefits the small in aquatic ecosystems[END_REF]. Shrinking of fishes may also be linked to the Temperature-Size rule (TSR), the phenomenon whereby warm temperatures cause more rapid early growth of ectotherms but a decline in their final adult size, when compared to conspecifics reared in a cooler regime [START_REF] Atkinson | Temperature and Organism Size-A Biological Law for Ectotherms?[END_REF]. The mechanisms involved in the TSR remain to be elucidated, it is observed in wild populations but can also be reproduced under controlled conditions in the laboratory [START_REF] Forster | Warming-induced reductions in body size are greater in aquatic than terrestrial species[END_REF][START_REF] Horne | Temperature-size responses match latitudinal-size clines in arthropods, revealing critical differences between aquatic and terrestrial species[END_REF].

Although there has been recent theoretical focus on whether the TSR relates to respiratory physiology [START_REF] Verberk | Shrinking body sizes in response to warming: explanations for the temperaturesize rule with special emphasis on the role of oxygen[END_REF], early work focussed upon whether changes in energy budget and allocation may be a major driver of fish shrinking with warming [START_REF] Gardner | Declining body size: a third universal response to warming?[END_REF][START_REF] Pauly | Gasping fish and panting squids: oxygen, temperature and the growth of water-breathing animals[END_REF]. The availability and quality of food resources can affect individual growth rates and adult body size through energy trade-offs among growth, survival and reproduction [START_REF] Stearns | Trade-Offs in Life-History Evolution[END_REF][START_REF] Stearns | The evolution of life histories[END_REF], and such effects may be exacerbated if energy requirements are increased by warming. That is, it is unlikely that temperature per se is the only variable involved in the size decline in wild populations, since few exceptions to this rule are spreading across years, in particular studies that investigated food resources as a driver explaining the TSR (e.g. in [START_REF] Diamond | Environmental Dependence of Thermal Reaction Norms: Host Plant Quality Can Reverse the Temperature-Size Rule[END_REF][START_REF] Lee | Macronutrient Balance Modulates the Temperature-Size Rule in an Ectotherm[END_REF][START_REF] Ljungström | Body size adaptions under climate change: zooplankton community more important than temperature or food abundance in model of a zooplanktivorous fish[END_REF][START_REF] Millien | Ecotypic variation in the context of global climate change: revisiting the rules[END_REF].

Temperature and food resources are both environmental variables whose variations can challenge an individual's energy balance and that can drive fish life-history traits through physiological processes. Thus, while the higher physiological rates due to warming cause an increase in energy demands, energy availability for marine fishes is predicted to decline due to climatic stressors that affect primary production and marine animal biomass [START_REF] Ariza | Global decline of pelagic fauna in a warmer ocean[END_REF][START_REF] Bopp | Response of diatoms distribution to global warming and potential implications: A global model study[END_REF][START_REF] Daufresne | Global warming benefits the small in aquatic ecosystems[END_REF][START_REF] Lotze | Global ensemble projections reveal trophic amplification of ocean biomass declines with climate change[END_REF]. Ocean warming can amplify vertical stratification and limit nutrient mixing [START_REF] Roemmich | Climatic Warming and the Decline of Zooplankton in the California Current[END_REF] which causes declines in plankton abundance at the base of the food web and leads to communities dominated by smaller-sized species and individuals [START_REF] Bopp | Response of diatoms distribution to global warming and potential implications: A global model study[END_REF][START_REF] Bopp | Multiple stressors of ocean ecosystems in the 21st century: projections with CMIP5 models[END_REF][START_REF] Daufresne | Global warming benefits the small in aquatic ecosystems[END_REF][START_REF] Richardson | Climate Impact on Plankton Ecosystems in the Northeast Atlantic[END_REF][START_REF] Ward | A size-structured food-web model for the global ocean[END_REF].

The first impacts of such changes at low trophic levels could be observed on planktivorous species, such as small pelagic fishes (e.g. [START_REF] Brosset | Spatio-temporal patterns and environmental controls of small pelagic fish body condition from contrasted Mediterranean areas[END_REF][START_REF] Van Beveren | Rapid changes in growth, condition, size and age of small pelagic fish in the Mediterranean[END_REF]. These species represent about 25 % of worldwide fishery landings by weight (FAO, 2018), supporting the economy of several countries [START_REF] Alheit | Decadal-scale variability in populations[END_REF][START_REF] Fréon | Sustainable exploitation of small pelagic fish stocks challenged by environmental and ecosystem changes: a review[END_REF]. Fluctuations of their populations can have critical economic and social consequences, as observed following the collapse of the Peruvian anchovy in the early 1970s [START_REF] Alheit | Decadal-scale variability in populations[END_REF][START_REF] Allison | Vulnerability of national economies to the impacts of climate change on fisheries[END_REF][START_REF] Schwartzlose | Worldwide large-scale fluctuations of sardine and anchovy populations[END_REF]. Population fluctuations of small pelagics are being exacerbated by ongoing global change [START_REF] Brochier | Climate change scenarios experiments predict a future reduction in small pelagic fish recruitment in the Humboldt Current system[END_REF][START_REF] Shannon | Impacts of fishing and climate change explored using trophic models[END_REF], so these species represent key models to evaluate energetic mechanisms underlying shrinking of adult fish size.

In fact, small pelagic planktivorous fishes in the Mediterranean Sea are a major example of shrinking [START_REF] Albo-Puigserver | Changes in Life History Traits of Small Pelagic Fish in the Western Mediterranean Sea[END_REF][START_REF] Brosset | Spatio-temporal patterns and environmental controls of small pelagic fish body condition from contrasted Mediterranean areas[END_REF]. There is an ongoing and profound decrease in individual body size and condition of sardine (Sardina pilchardus) and anchovy (Engraulis encrasicolus), which appears to be a consequence of bottom-up control mediated by changes in plankton composition and abundance [START_REF] Brosset | Linking small pelagic dietary shifts with ecosystem changes in the Gulf of Lions[END_REF][START_REF] Saraux | Small pelagic fish dynamics: A review of mechanisms in the Gulf of Lions[END_REF].

This was associated with a major regime change in the mid-2000s, with shifts of nutrient inputs, water mixing and plankton production [START_REF] Feuilloley | Concomitant changes in the environment and small pelagic fish community of the Gulf of Lions[END_REF]. Since 2008, these species' diet has shifted progressively from large prey (> 1 mm, especially cladocerans) to increased reliance on smaller prey (< 1 mm, especially copepods), which indicates changes in the plankton community towards smaller species [START_REF] Brosset | Linking small pelagic dietary shifts with ecosystem changes in the Gulf of Lions[END_REF]. Smaller zooplankton can be less nutritious [START_REF] Zarubin | Intraspecific differences in lipid content of calanoid copepods across fine-scale depth ranges within the photic layer[END_REF], so a decline in zooplankton size could entrain a decrease in rates of energy acquisition by their predators. Identifying a clear mechanistic link between a decrease in plankton size and fish growth, and ultimately population dynamics, is crucial since fish shrinking is spreading to new ecosystems and species (see [START_REF] Bensebaini | Interactions between demersal fish body condition and density during the regime shift of the Gulf of Lions[END_REF][START_REF] Véron | Major changes in sardine growth and body condition in the Bay of Biscay between 2003 and 2016: Temporal trends and drivers[END_REF].

Challenges to energy balance when prey become smaller could be further exacerbated in fishes if prey size also influences foraging behaviour. Here, the sardine is also an interesting model species. Sardines spontaneously modify their feeding behaviour according to the size of their prey, using diffuse filter-feeding when prey is small but direct capture when prey is large [START_REF] Garrido | Laboratory investigations on the effect of prey size and concentration on the feeding behaviour of Sardina pilchardus[END_REF][START_REF] Garrido | Diet and feeding intensity of sardine Sardina pilchardus: Correlation with satellite-derived chlorophyll data[END_REF]. A recent long-term experiment on captive sardines showed that, for the same food ration, a reduction in food size could significantly impair growth and body condition [START_REF] Queiros | Food in the Sea: Size Also Matters for Pelagic Fish[END_REF]. Sardines filter feeding on small particles had to consume twice as much as those capturing large particles to achieve the same growth and body condition [START_REF] Queiros | Food in the Sea: Size Also Matters for Pelagic Fish[END_REF]. We suspected that the two foraging modes had different energetic costs for the same degree of resource acquisition, with costs being higher for sustained aerobic swimming during filter-feeding compared to brief bursts of swimming to capture prey [START_REF] Costalago | Feeding of European pilchard (Sardina pilchardus) in the northwestern Mediterranean: from late larvae to adults[END_REF][START_REF] Queiros | Food in the Sea: Size Also Matters for Pelagic Fish[END_REF]. At the same time, food availability could be highly significant in the wild, filtration could be effective in very rich areas such as upwellings whereas particulate feeding might be more advantageous in areas with lower prey density [START_REF] Costalago | Comparison of the feeding apparatus and diet of European sardines Sardina pilchardus of Atlantic and Mediterranean waters: Ecological implications[END_REF].

The current study focused on this complex predator-prey interaction in a captive population of adult sardines. We investigated the hypothesis that foraging on smaller prey would lead to increased rates of energy expenditure by sardines, and that these energy requirements would be exacerbated with warming temperature. To assess the energetic consequences of feeding sardines on prey of different sizes and at different abundances, we used group respirometry to measure rates of oxygen uptake and provided prey as commercial pellets of two different sizes at a range of ration levels. We compared animals acclimated to two temperatures within the species' thermal range, either a cool 16°C or warm 21°C. Thus, the effects on oxygen consumption of particle size and temperature were investigated according to 5 scenarios: [START_REF] Li | Effects of short-term fasting on spontaneous activity and excess post-exercise oxygen consumption in four juvenile fish species with different foraging strategies[END_REF] change from large to small particles at cool temperature; (2) change from large to small particles at warm temperature; (3) rise in temperature with fish fed on large particles; (4) rise in temperature with fish fed on small particles, and (5) change from large to small particles while also increasing temperature. To that end, we focussed on overall daily energetic costs but also a careful comparison of energetic costs incurred during and after feeding for each scenario.

Material and methods

Animal capture and husbandry

Sardines were captured by commercial purse-seiner and transferred to the IFREMER Palavasles-Flots research station, with the same fishing and husbandry procedures as described tailed in [START_REF] Queiros | Food in the Sea: Size Also Matters for Pelagic Fish[END_REF]. Over the first week, sardines were acclimated to tanks and weaned onto commercial aquaculture pellets. They were fed with a mixture of Artemia nauplii and commercial aquaculture pellets (mix of 0.2 and 1.2 mm diameter), with increasing proportions of pellets and decreasing proportions of Artemia throughout the week, concluding exclusively with pellets. After 2-3 weeks, sardines were transferred into indoor 1m 3 holding tanks, until experimentation. Water temperature was not set during this period but followed natural fluctuations from 15 to 20°C (SST at the time of capture was 14°C).

Experimental design

Eighty sardines were distributed among 8 experimental tanks in groups of 10 animals (volume 50 L), to ensure similar distributions of body mass and condition among tanks (Fig. S1), and fish densities comparable to those of [START_REF] Queiros | Food in the Sea: Size Also Matters for Pelagic Fish[END_REF]. Fish were acclimated to the new tanks while temperature was gradually changed from 19°C to either 16°C or 21°C over one week. Before the experiments began, fish were fed with commercial pellets twice a day, a mix of 0.2 and 1.2 mm to avoid preference bias for pellet size. These eighty sardines were used for both experiments 1 and 2, described below, and these two experiments were performed sequentially in the same setup.

The tanks were modified to function as open automated respirometers [START_REF] Mckenzie | Aspects of respiratory physiology and energetics in rainbow trout (Oncorhynchus mykiss) families with different size-atage and condition factor[END_REF][START_REF] Mckenzie | Effects of stocking density and sustained aerobic exercise on growth, energetics and welfare of rainbow trout[END_REF][START_REF] Queiros | Is starvation a cause of overmortality of the Mediterranean R Core Team[END_REF] using the principles of cyclical intermittent stopped flow [START_REF] Steffensen | Some errors in respirometry of aquatic breathers: How to avoid and correct for them[END_REF], as described below. Four tanks were held at each of the two temperatures, each set of four was supplied by water from a single reservoir where water temperature was regulated by an Ice 3000 (Aquavie) at 16°C or by a Red Line heater (Zodiac) at 21°C. Water in the reservoir was vigorously aerated, to maintain oxygen saturation and ensure thorough mixing. Water was delivered to tank respirometers by submersible pumps (Eheim 3400); within each respirometer the water was also gently but thoroughly mixed by a submersible pump (Newa Maxi 500) to avoid any thermal or oxygen gradients (see Supplementary Material and Fig. S2).

All respirometers were exposed to a 12L:12D photoperiod (L: light, D: darkness) with a natural sunlight spectrum and 30 minute progressive dawns and sunsets. Individual total length and body mass was measured every two weeks under anaesthesia (140 mg L -1 benzocaine). To estimate total tank biomass each day, body mass gain (or loss) was assumed to be linear between successive bi-weekly measures. Total biomass was then used to adjust rations and to calculate oxygen consumption. No mortality was observed during the experiments.

Protocols

Experiment 1: Effects of prey size, prey abundance and temperature on daily energy expenditure.

To investigate effects of prey size, we offered sardines one of two commercial pellets that had similar composition in terms of lipids and proteins but differed in size, being either 0.2 mm or 1.2 mm in diameter, for a period of six weeks. These sizes fall within the natural range of sardine prey [START_REF] Nikolioudakis | Diet of sardine Sardina pilchardus: An "end-to-end" field study[END_REF], but elicit two markedly different foraging modes, being either filtering on 0.2 mm pellets or particulate capture of 1.2 mm pellets (Queiros et al., 2019). Eight prey abundances were studied, as pellet rations ranging from 0.1 to 1.8 % of the total fish mass per tank: 0.1%, 0.2%, 0.3%, 0.4%, 0.6%, 1.0%, 1.4%, 1.8%. The combination of two sizes and eight rations resulted in 16 feeding treatments for each of the 2 temperatures (Figure 1). Sardines were fed once a day at 09:00 in the morning. Daily feeding treatment for a tank was randomly assigned but comprised 2 replicates of each feeding treatment per tank over the entire experiment (i.e. 8 replicates per feeding treatment x temperature).

The cyclical measures of oxygen uptake rate (MO2 in mg kg -1 h -1 ) provided an indirect estimate of metabolic rate and, therefore, energy use, while the sardines fed, digested and exhibited diurnal patterns of spontaneous activity. Methodological details are provided below. A continual cycle of 15 min stopped flow to measure MO2 alternated with 15 min flush with aerated water was used, except at feeding when flow was stopped for 30 min (at rations of 0.1%, 0.2%, 0.3% and 0.4%) or 60 min (at rations of 0.6%, 1.0%, 1.4% and 1.8%), to ensure the entire ration was consumed before flushing. Food was distributed 5 minutes after flow was stopped, when water level had stabilized in all respirometers.

Bias due to behavioural responses to the act of feeding (e.g. anticipation caused by human presence near tanks at the typical feeding time) was controlled for by sham-feeding events, where the typical feeding gestures were performed but no food was provided. These shams were performed twice a day (9:00 am and 2:00 pm) for 2 days in all tanks, in the middle and at the end of experiment 1.

Experiment 2: Effects of prey size, prey abundance and temperature on features of foraging behaviour.

In this experiment we studied features of the foraging modes, filtration or particulate capture, in more detail, considering duration and maximum intensity (Figure 1). To this end, sardines were fed twice a day (9:00 am and 2:00 pm) for 3 weeks with 8 treatments: one of two food sizes (0.2 and 1.2 mm) at four rations (0.1, 0.2, 0.3 and 0.4% of tank biomass). The combination of two sizes and four rations resulted in 8 feeding treatments for each of the 2 temperatures (16°C and 21°C). Based on the results of Experiment 1, rations were chosen not to cause satiety. Similar to Experiment 1, MO2 was measured throughout and for 30 min during feeding (food distributed after 5 min). Combining these data with those of Experiment 1 (Fig. S3), we obtained a total of 24 replicates per feeding treatment x temperature for food rations between 0.1% and 0.4%. Any bias due to behavioural responses to the act of feeding were assessed by two sham events, as described above. [C], on the maximal intensity during feeding [D]) and on the duration of the feeding activity [E].

Respirometry

Water oxygen levels were recorded every 5 seconds in the tank respirometers, with an O2 optode (Oxy-10 mini; PreSens Precision Sensing GmbH, /www.presens.de) and associated software (Pre-Sens Oxy 4v2). Water O2 saturation never fell below 70% during the 15 min of stopped flow and never below 60% after feeding. Saturation was rapidly restored when the tanks were flushed with a flow of aerated water from the reservoir.

Oxygen uptake by the sardines caused a linear decline in water O2 concentration over time during each stopped flow phase ('closed phase'). The MO2 was calculated in mg O2 kg -1 h -1 , using least-square regression of the slope, considering oxygen solubility at the appropriate temperature (measured continuously) and salinity (measured daily); tank volume (50 L), and fish biomass [START_REF] Mckenzie | Aspects of respiratory physiology and energetics in rainbow trout (Oncorhynchus mykiss) families with different size-atage and condition factor[END_REF]. Only slopes with R 2 ≥ 0.95 were kept for further analyses (<5% of slopes were removed from analyses). Gas exchange across the water surface being negligible, no correction was applied when estimating sardine oxygen consumption [START_REF] Mckenzie | Aspects of respiratory physiology and energetics in rainbow trout (Oncorhynchus mykiss) families with different size-atage and condition factor[END_REF][START_REF] Queiros | Is starvation a cause of overmortality of the Mediterranean R Core Team[END_REF].

Respirometry data analyses

Basal and daily oxygen consumption

Basal O2 uptake rate of dayi was expressed as the lowest 15%-quantile (Chabot et al., 2016a) of the daily O2 consumption of the previous day (from 06:00 a.m. dayi-1 to 06:00 a.m. dayi). This rate of oxygen uptake was then used as a baseline for calculating daily oxygen consumption on dayi, expressed in mg O2 kg -1 d -1 , as an increase from this basal rate. This normalisation avoided bias linked to a change in fish biomass during experiments, short-term effects of a previous meal, or a small change in temperature, salinity, minor human disturbance, etc. Daily MO2 was calculated as the area under the curve (AUC) of MO2 over time, from 06:00 a.m. and for 24 hours (Figure 1, point A) using the 'DescTools' package in R (Andri Signorell 2021). The AUC was calculated over two periods: (i) raw data from 06:00 a.m. until noon, to catch the peak of oxygen consumption observed during the meal period and (ii) smoothed values of the oxygen consumption after 12:00 a.m. (oxygen consumption smoothed using lowess function) to avoid outliers due to, for example, minor disturbance in the room, that might distort daily estimations (Fig. S3).

Oxygen consumption during feeding

When focusing on effects of a meal on MO2, these were calculated relative to a control baseline that was estimated as the mean of the preceding 2.5 hours. This was done to avoid bias when either lights were turned on 1.5 hour before the 1 st daily meal, or there were remnant effects of digestion of that 1 st meal for the 2 nd meal period. Since it took up to 2 minutes to feed all tanks (i.e. between 5 and 7 minutes after the beginning of the closed phase), we first needed to establish the start of the feeding event for each tank. To do so, we identified a break in the rate of oxygen decline in the water during the initial minutes of the 'closed phase', using the 'segmented' package [START_REF] Muggeo | segmented: an R Package to Fit Regression Models with Broken-Line Relationships[END_REF]. Once this was identified, oxygen consumption was calculated, in mg O2 kg -1 h -1 , as the linear decline of oxygen concentration from there until 2 min before the end of the 'closed phase' (Figure 1, point B).

Oxygen consumption during digestion

The start of the digestion period was considered to begin 90 min after the start of the meal period, this being the maximal duration of the feeding and then flush periods across the different rations. Thus, with feeding at 09:00, the oxygen consumption during digestion was calculated, in mg O2 kg -1 d -1 , as the AUC of the oxygen consumption over time between 10:30 a.m. of dayi and 06:00 a.m. of dayi+1 (Figure 1, point C). This oxygen consumption was expressed as an increase from the basal O2 uptake of dayi as estimated above.

Maximal oxygen consumption during feeding

To reveal dynamics of metabolic rate after feeding (Fig. S5), MO2 was estimated as a moving average at 30 second intervals during the closed feeding period, using linear regressions over 1 minute on smoothed data for 12 measures of tank oxygen concentration. This revealed the maximum oxygen consumption, in mg O2 kg -1 h -1 , achieved during each meal period (Figure 1, point D).

Duration of the feeding period

To estimate feeding duration, in minutes, we identified the end of the meal as the breakpoint when oxygen concentration stopped decreasing severely after feeding, taken to indicate the end of feeding-related activity (Figure 1, point E). That is, a broken-line regression was performed on oxygen consumption values calculated every 30 seconds (also every 30 seconds over 1 minute), starting at the peak of oxygen consumption as estimated above.

Statistical analyses

Effects of food rations, prey (particle) size and temperature, on oxygen consumption and feeding duration, were assessed using linear mixed-effects models. We built a series of models including three fixed effects (food size, food ration and temperature), as well as their interactions. Because of variability among tanks within each food ration x food size x temperature treatment, we also introduced a random tank intercept effect. The best-fitting model was selected based on the lowest AICc values (Burnham and Anderson, 2002) following [START_REF] Zuur | Mixed effects models and extensions in ecology with R, Statistics for Biology and Health[END_REF]. When the difference between these models in AICc (ΔAICc) was lower than two, the most parsimonious model was selected (Burnham and Anderson, 2002). Food ration was log-transformed for models of MO2 during feeding and maximal MO2 during feeding.

Then, food ration was second order polynomial transformed to model feeding activity.

Finally, the effects of prey (particle) size and temperature on oxygen consumption were investigated according to 5 scenarios: (1) a change from large to small particles at cool temperature; (2) a change from large to small particles at warm temperature; (3) a rise in temperature with fish fed on large particles; (4) a rise in temperature with fish fed on small particles, and ( 5) a change from large to small particles while also increasing temperature (see arrows in Figure 2). As such effects also depend on the food ration when the interaction with food ration was significant, we performed pairwise comparison to test significance of scenarios using selected best-fitting models as previously described. Results of scenarios over food ration are expressed as absolute and relative increases. Results are indicated as mean [95% CI]. Upper and lower 95% CI values of relative differences over food ration were calculated following [START_REF] Kohavi | Controlled experiments on the web: survey and practical guide[END_REF].

All data analyses were performed under R (R Core Team, 2020) and linear mixed-effects models were built using the 'lme4' package [START_REF] Bates | Fitting Linear Mixed-Effects Models Using lme4[END_REF]. All statistical tests were considered significant at p-values < 0.05.

Results

When fasted, MO2 was low and statistically similar throughout the day (black curve in Figure 2). When sardines were fed, MO2 peaked during the feeding period after 09:00, then decreased for the rest of the day for all feeding treatments and both temperatures. Oxygen consumption increased with food ration and rearing temperature but, during feeding at both temperatures, MO2 was higher when feeding on the small particles (Figure 2). 5) change from large particles to small particles while also increasing temperature.

Daily oxygen consumption

During fasting days, median daily MO2 (i.e. the AUC relative to basal daily oxygen consumption) was the lowest, demonstrating the clear effects that feeding and/or digestion exerted on daily energy expenditure (Figure 2, Fig. S6).

The best linear mixed-effect model included double interactions between food ration and food size and between food ration and temperature (Tables S1 andS2, Fig. S6,S7). An increase in ration consistently caused a significant increase in daily oxygen consumption when considering either food size or temperature. When considering only food size effects, slopes were significantly different (p < 0.001) and the increase was smaller for large particles (slope [95% CI]; 420 [324;515] mg of O2 kg -1 d -1 ) than for small particles (714 [618;810] mg of O2/kg/d, graph Daily in Figure 3, Table S3).

When comparing large to small particles over all food rations, scenarios ( 1) and (2) were not significant since food size x temperature interaction was not retained during model selection.

Daily MO2 exhibited a mean [95% CI] relative increase of 13 [1;37]% for small particles at 16°C, while this increase was 10 [3;22]% at 21°C (graph Daily in Figure 3, Table 1).

Figure 3: Smooth functions of [A] daily, [B] while feeding, [C] while digesting, [D] maximal oxygen consumptions (relative to basal oxygen consumption, see details in Material and

Methods) and [E] feeding duration according to the food ration for the 4 experimental treatments: cool temperature and large particles (solid blue lines), cool temperature and small particles (dotted blue lines), warm temperature and large particles (solid red lines) and warm temperature and small particles (dotted red lines). Arrows represent the mean relative increase of the oxygen consumption/feeding duration according to 4 scenarios summarized in top-left panel: scenario 1 = meal modification from large particles to small particles at cool temperature, (2) meal modification from large particles to small particles at warm temperature, (3) increasing temperature when fish fed on large particles and (4) increasing temperature when fish fed on small particles. Only food size x food ration had a significant effect on feeding duration.

Table 1: Absolute and relative differences (estimates and 95% confidence intervals) for the 5 scenarios for which oxygen consumption were compared: [START_REF] Li | Effects of short-term fasting on spontaneous activity and excess post-exercise oxygen consumption in four juvenile fish species with different foraging strategies[END_REF] change from large particles to small particles at cool temperature; (2) change from large particles to small particles at warm temperature; (3) rise in temperature for fish fed on large particles; (4) rise in temperature for fish fed on small particles, and ( 5) change from large particles to small particles while also increasing temperature. Scenarios were tested using pairwise comparisons. Both differences were calculated by pairwise comparisons and 95% CI of relative differences were estimated following [START_REF] Kohavi | Controlled experiments on the web: survey and practical guide[END_REF]. Absolute differences are given in mg of O2 kg -1 d -1 for daily and during digestion, in mg of O2 kg -1 h -1 for maximal and during feeding, and in minutes for feeding duration.

Oxygen consumption during feeding

During fasting days, median MO2 at the time of sham feeding was centered on zero (Fig. S8),

indicating that the increase in MO2 observed during all true feeding events resulted from actual energy expenditure to feed and not from behavioural responses by the sardines to feeding gestures.

The MO2 during feeding was significantly related to the three double interactions (food ration

x food size, food ration x temperature and food size x temperature, Tables S4 andS5, Fig. S8, S9). When considering only food size effects, slopes were significantly different (p < 0.001) and the increase was smaller for large particles (slope [95% CI]; 95 [85;105] mg of O2 kg -1 h -1 )

than for small particles (129 [119;139] mg of O2 kg -1 h -1 , Table S3).

Food size had a strong and significant effect on MO2 during feeding. 1).

Oxygen consumption during digestion

Similar to the daily MO2, best linear mixed-effect model for MO2 during digestion included double interactions between food ration and food size and between food ration and temperature (Tables S6 andS7, Fig. S10,S11). Slopes differed significantly (p < 0.001); the lowest slope was estimated for sardines on large particles (slope [95% CI]; 300 [213;388] mg of O2 kg -1 d -1 ) while the highest slope was obtained for sardines on small particles ( 533[445;621] mg of O2 kg -1 d -1 , graph Digestion in Figure 3).

When comparing large to small particles averaged over all food rations, scenarios ( 1) and ( 2)

were not significant since interaction between food size and temperature was not retained in the selected model. Indeed, mean [95% CI] MO2 during digestion decreased by 3 [-13,-1]% at 16°C, while this decrease was 3 [-6;-1]% at 21°C (graph Digestion in Figure 3, Table 1).

Maximal consumption during feeding

Similar to the MO2 during feeding, maximal MO2 during feeding was significantly correlated with the three double interactions (Tables S8 andS9, Fig. S12,S13). Slopes differed significantly (p = 0.001); the lowest slope was estimated for sardines on small particles (slope [95% CI]; 87 [67;106] mg of O2 kg -1 h -1 ) while the highest slope was obtained for sardines on large particles (132 [113;152] mg of O2 kg -1 h -1 , graph Maximum in Figure 3, Table S3).

Food size had a strong and significant effect on maximal MO2 during feeding since food size

x temperature interaction was retained during model processing. When sardines fed on small particles at 16°C, their mean [95% CI] maximal MO2 rose by 48 [24;84]% by comparison to large particles, while such increase was 48 [29;75]% at 21°C (graph Maximum in Figure 3, Table 1).

Feeding duration

Contrary to the previous MO2 features, the selected model for the feeding duration included interaction between food ration and food size but not with temperature since food ration x temperature and food size x temperature interaction were not retained (Tables S10 andS11, Fig. S14,S15). Slopes differed significantly between the two food sizes (p = 0.004). Indeed, the feeding duration decreased with increasing food ration when sardines fed on small particles (slope [95% CI]; -3 [-6;0] min) while it increased when sardines fed on large particles (4 [1;7] min, Table S3).

When comparing large to small particles averaged over all food rations, scenarios ( 1) and ( 2)

were not significant since interaction between food size and temperature was not retained in the selected model. Mean [95% CI] feeding duration increased by 42 [-11;339]% (graph Feeding duration in Figure 3, Table 1).

Temperature effects

Temperature had significant effects on all oxygen consumptions and on the feeding duration (Tables S1 to S11). Indeed, food ration x temperature interaction was included in all selected models on MO2 and food size x temperature interaction was included in models on MO2

during feeding and maximal MO2 during feeding. Moreover, in the model on feeding duration, temperature was retained without its interactions (Tables S10).

When studying interaction of food ration and temperature, slopes were significant different between the two temperatures in all MO2 models and they were always smaller at cool than at warm temperature. Thus, slopes were smaller at 16°C than at 21°C for daily MO2, MO2 during digestion, MO2 during feeding, and maximal MO2 during feeding (Table S3).

Surprisingly, slopes were very similar when considering either large particles or cool temperature effects (e.g. slopes [95% CI] for daily MO2,420 [324;515] and 413 [317;509], respectively) and either small particles or warm temperature effects (for daily MO2, 714

[618;810] and 721 [626;817], respectively, suggesting similar effects of prey shrinking and temperature warming over food ration on MO2 (see Table S3).

When comparing cool to warm conditions, in scenarios (3) and (4) there was no significant effect of temperature on daily MO2, MO2 during digestion or on feeding duration, because food size x temperature interaction was not retained within selected models. On the other hand, warming effects were significant on MO2 during feeding (p-values < 0.001) but only scenario (4) was significant on maximal MO2 during feeding (p-value = 0.02). Thus, the temperature change from 16°C to 21°C caused mean MO2 during feeding to increase by 26

[16;37]% in fish fed on small particles, and by 49 [11;129]% in fish fed on large particles. This temperature change caused mean maximal MO2 during feeding to increase by 26 [16;39]% in sardines fed with small particles (Figure 3, Table 1).

Cocktail effects of the global warming

Smaller particle size and higher temperature resulted in a mean [2;6] min without temperature effect, Figure 4, Table 1).

Figure 4: Smooth functions of [A] daily, [B] while feeding, [C] while digesting, [D] maximal oxygen consumptions and [E] feeding duration according to the food ration for the 2

experimental treatments representing past and future environmental conditions, i.e. cool temperature and large particles (solid blue lines) and warm temperature and small particles (dotted red lines), respectively. Arrows represent the mean relative increase of the oxygen consumption/feeding duration according to the global warming (scenario 5), i.e. meal modification from large particles to small particles with increasing temperature, and summarized in top-left panel (feeding duration is not significantly affected by temperature increase, see Results).

Discussion

This study investigated how a modification of food resources under climate warming might jeopardize energy balance of small pelagic species, using sardines in the Mediterranean Sea as a case study. To do so, we used in-vivo group respirometry to investigate the effects of prey (food) size and availability (ration) on sardine energy expenditure, and how this was influenced by temperature. Our results demonstrate that both food size and temperature had significant effects on multiple measures of energy expenditures, over daily and hourly timescales. While temperature significantly increased expenditures overall, food size had a major impact on energy expenditure for activity during feeding itself. That is, the results indicate that food resources and temperature are major environmental drivers that can dramatically increase energy expenditures of fishes and disturb their energy balance in a scenario of future climate change, in warmer waters with smaller prey. As such, the results also provide experimental evidence that such challenges to energy balance may contribute to the ongoing shrinking of fish populations.

Daily oxygen consumption measured in this study was corrected against a baseline of standard metabolism (Chabot et al., 2016a), so represents daily energy expenditure on activity. The results suggested greater expenditure for days where sardines fed on small particles, due to higher oxygen consumption during either feeding and/or digestion. The very marked increase in oxygen consumption during actual feeding on small items must reflect different costs of foraging mode, with filtering being more expensive than particulate feeding.

While this confirms our hypothesis and helps explain the decreased growth and body condition of sardines fed for an extended period on small items [START_REF] Queiros | Food in the Sea: Size Also Matters for Pelagic Fish[END_REF], the magnitude of the effect is quite remarkable. Both MO2 and duration of the meals provide a more detailed understanding of the widely different energy costs of the two foraging modes.

First, the higher maximal MO2 when fish fed on small particles indicates greater energy requirements for the continuous aerobic swimming in filter-feeding compared to rapid bursts to capture large particles [START_REF] Costalago | Feeding of European pilchard (Sardina pilchardus) in the northwestern Mediterranean: from late larvae to adults[END_REF]. [START_REF] Queiros | Food in the Sea: Size Also Matters for Pelagic Fish[END_REF] had already noted that the duration of feeding activity was longer when sardines fed on small particles, it presumably represents the time needed to filter the entire tank volume and, therefore, might not be expected to change much with ration. It is interesting therefore that feeding duration on small particles was in fact lower at low or high rations than at intermediate ones. Low duration at low ration might suggest rapid loss of interest if food acquisition was very poor, while at high ration it might indicate satiation. For particulate feeding, more particles to catch should translate into longer duration, which was observed until a ration threshold where a plateau would indicate satiation. Overall, we expected feeding duration to be longer on small particles at low ration but longer on large particles, but this was only true for rations below 0.6 %, after which duration was similar for both particle sizes. Finally, all these results indicate that higher energy expenditure by sardines filter feeding on small particles can explain why they would have to eat twice as much as when feeding on large pellets to achieve similar growth or body condition [START_REF] Queiros | Food in the Sea: Size Also Matters for Pelagic Fish[END_REF].

Our finding that oxygen consumption during the digestion increased with the food ration, for both particle sizes, presumably reflects the so-called specific dynamic action of feeding (SDA) response [START_REF] Mccue | Specific dynamic action: A century of investigation[END_REF]. This reflects the energy needed for the digestion, absorption and assimilation of a meal (Chabot et al., 2016b), hence the energetic 'costs of growth'. Therefore, larger meals require greater energy investment but then provide a great return in terms of tissue accretion and growth (Fu et al., 2005a(Fu et al., , 2005b;;[START_REF] Jordan | Effects of Ration Size and Hypoxia on Specific Dynamic Action in the Cod[END_REF][START_REF] Norin | Fish face a trade-off between 'eating big' for growth efficiency and 'eating small' to retain aerobic capacity[END_REF]. The fact that a doubling of ration from 0.4% to 0.8% only caused a 17% or 55% increase in apparent SDA (based on estimated slopes), in fish fed large items at 16 °C or small items at 21°C, respectively, might seem limited. This increase with doubling of ration is low compared to other fish species (see [START_REF] Secor | Specific dynamic action: A review of the postprandial metabolic response[END_REF]. Furthermore, the high surface area to volume ratio of small particles should speed up digestion by promoting enzymatic processes and, thereby, reduce a part of digestion costs (discussed in [START_REF] Legler | Water Temperature and Prey Size Effects on the Rate of Digestion of Larval and Early Juvenile Fish[END_REF]. On the other hand, a large SDA response can indicate that lots of nutrients were assimilated, notably amino acids for protein synthesis, with high costs of turning these into tissues but that reflect robust growth [START_REF] Fraser | Protein Metabolism in Marine Animals: The Underlying Mechanism of Growth[END_REF][START_REF] Mccue | Specific dynamic action: A century of investigation[END_REF][START_REF] Secor | Specific dynamic action: A review of the postprandial metabolic response[END_REF]. That is, a large SDA would imply good growth, which is coherent with the fact that sardines fed on large particles exhibited higher growth and greater condition in previous studies (see [START_REF] Queiros | Food in the Sea: Size Also Matters for Pelagic Fish[END_REF].

There is another mechanism that might increase energy expenditure during 'digestion' of large particles, being the costs of recovery from rapid bursts of anaerobic swimming used for prey capture. The metabolic cost of such recovery, so-called 'excess post-exercise oxygen consumption' (EPOC) can be divided into 3 phases in fishes: rapid, plateau, slow [START_REF] Zhang | A three-phase excess post-exercise oxygen consumption in Atlantic salmon Salmo salar and its response to exercise training[END_REF]. While the rapid phase is very short (< 1 hour), both plateau and slow phases can require several hours to return to standard metabolism. This can be more than 10 hours for salmon although the duration is certainly species dependent (C. G. [START_REF] Lee | Excess post-exercise oxygen consumption in adult sockeye (Oncorhynchus nerka) and coho (O. kisutch) salmon following critical speed swimming[END_REF][START_REF] Li | Effects of short-term fasting on spontaneous activity and excess post-exercise oxygen consumption in four juvenile fish species with different foraging strategies[END_REF][START_REF] Js Plambech | Excess post-hypoxic oxygen consumption in Atlantic cod Gadus morhua[END_REF][START_REF] Svendsen | Excess posthypoxic oxygen consumption in rainbow trout (Oncorhynchus mykiss): Recovery in normoxia and hypoxia[END_REF][START_REF] Zhang | A three-phase excess post-exercise oxygen consumption in Atlantic salmon Salmo salar and its response to exercise training[END_REF]. Considering that we estimated energy expenditure of digestion starting at 1.5 hours after providing the meal, this would omit the rapid phase of EPOC, although the phenomenon may have contributed to the final phases of metabolic costs of feeding. A potential role for EPOC in costs of feeding on large prey remains to be proven, since studies on individual sardines are technically extremely challenging. Overall, oxygen consumption due to digestion was lower for small compared to large particles, but the magnitude of the difference was much less than for the activity costs of feeding. Therefore, daily energy expenditure was mostly affected by what happened during the meal. The benefit of digesting small prey (in terms of energy expenditure for a same food ration) remained too weak to counterbalance the increased energy to capture shrinking plankton in the wild. Furthermore, the warm temperature also significantly increased metabolic rates, leading to overall higher energy expenditure during both meals and digestion [START_REF] Clarke | Why does metabolism scale with temperature?[END_REF][START_REF] Seebacher | Physiological plasticity increases resilience of ectothermic animals to climate change[END_REF], whatever the food size or ration. Higher energetic cost for digestion at warm temperatures has been reported for tunas, another species that swims continuously [START_REF] Klinger | The effect of temperature on postprandial metabolism of yellowfin tuna (Thunnus albacares)[END_REF] although relationships between costs of digestion and temperature are not necessarily linear [START_REF] Mckenzie | Local adaptation to altitude underlies divergent thermal physiology in tropical killifishes of the genus Aphyosemion[END_REF][START_REF] Tirsgaard | Effects of temperature on specific dynamic action in Atlantic cod Gadus morhua[END_REF].

Our study applied relatively short thermal acclimation times, which might tend to overestimate temperature effects. When natural populations are allowed to acclimatise over generations, baseline metabolism may show a much less marked effect of temperature (e.g. [START_REF] Wootton | Smaller adult fish size in warmer water is not explained by elevated metabolism[END_REF]. Such intergenerational experiments are not feasible for the Mediterranean sardine because their life cycle cannot be completed in captivity. Our experimental temperatures (16°C and 21°C) were well within the range that sardines have experienced in the Gulf of Lions over the last 40 years (12 -24°C ; [START_REF] Feuilloley | Concomitant changes in the environment and small pelagic fish community of the Gulf of Lions[END_REF]) and our rate of temperature change was slow (< 0.5°C/day) allowing acclimation at an ecologically realistic pace. Furthermore, by expressing oxygen consumption as a relative increase from MO2 baseline (the baseline was estimated daily as the lowest 15%-quantile rate for daily MO2 and MO2 during digestion, and as the mean of the preceding 2.5 hours for MO2 while feeding), effects of temperature on baseline metabolism were been taken into account in our study. Finally, although the effects of temperature were significant, potential acclimation across a few generations leading to similar baseline metabolism between generations would reinforce our results on the effects of food size.

Although food size had only quite minor effects on daily energy use, increasing it by 10 [3;22]% in fish fed on small particles at 21°C, long-term effects may be significant. Furthermore, sardines may feed continuously in the wild, not only once or twice a day, which would increase consequences of differences in energy expenditure during feeding. In the wild, sardines face predation and pathogens that require energy expenditure. Therefore, higher daily energy expenditure for feeding may well impair energy balance in the wild, resulting in less energy allocated towards survival and growth. For instance, lower swimming performance due to low energy reserves (e.g. swimming endurance [START_REF] Martínez | Condition, prolonged swimming performance and muscle metabolic capacities of cod Gadus morhua[END_REF][START_REF] Martínez | Does condition of Atlantic cod (Gadus morhua) have a greater impact upon swimming performance at Ucrit or sprint speeds[END_REF])) could isolate leaner individuals from schools, leading to a vicious circle, with lower food foraging and thus reinforcing lower energy reserves. Nonetheless, calorie-restricted sardines display better phenotypic plasticity to face fasting, which improves their ability to reduce their metabolic energy expenditures during long-term fasting [START_REF] Queiros | Is starvation a cause of overmortality of the Mediterranean R Core Team[END_REF].

Further, mitochondria from sardines fed with small particles exhibited lower basal oxidative activity but higher efficiency of ATP production than those fed with large particles, a mechanism that should help them spare energy [START_REF] Thoral | Changes in foraging mode caused by a decline in prey size have major bioenergetic consequences for a small pelagic fish[END_REF]. Nevertheless, although sardines may display plasticity or adaptation that ameliorates the energetic consequences of smaller prey and warmer temperatures, the situation of sardine populations in the Gulf of Lions remains very concerning.

Conclusion

This study supports the hypothesis of bottom-up control to explain the profound shrinking of small pelagic fish communities in the Gulf of Lions and is a hypothesis worth exploring to explain the spread of this phenomenon throughout the Mediterranean [START_REF] Albo-Puigserver | Changes in Life History Traits of Small Pelagic Fish in the Western Mediterranean Sea[END_REF][START_REF] Brosset | Spatio-temporal patterns and environmental controls of small pelagic fish body condition from contrasted Mediterranean areas[END_REF] to new ecosystems, and to species higher in the food web [START_REF] Bensebaini | Interactions between demersal fish body condition and density during the regime shift of the Gulf of Lions[END_REF][START_REF] Véron | Major changes in sardine growth and body condition in the Bay of Biscay between 2003 and 2016: Temporal trends and drivers[END_REF] Fig. S3: Boxplots of oxygen consumption during the 1 st meal in the morning (in blue) and the 2 nd meal in the afternoon (in grey) for the four feeding treatment x temperature (cool temperature and large particles, cool temperature and small particles, warm temperature and large particles and warm temperature and small particles).

Oxygen consumptions have been calculated relative to a control baseline that was estimated as the mean of the preceding 2.5 hours. This calculation avoided bias when lights were turned on 1.5 hour before the 1 st daily meal, and also potential remnant effects of digestion of that 1 st meal for the 2 nd meal period. No significant effect of the period (morning vs. afternoon) on the oxygen consumption over feeding treatment x temperature was found (ANOVA, p = 0.63). Blue and red colors represent cool (16°C) and warm (21°C) temperature, respectively. Sample size (i.e. number of meals) is given as 'n' at the bottom of each panel. Sample size is greater for the 4 smallest quantities (i.e. 0.1, 0.2, 0.3 and 0.4%) because oxygen consumption obtained from experiments 1 and 2 were pooled here. When a feeding duration could not be calculated (e.g. no breakpoint), data was removed from this analysis. (Burnham and Anderson, 2002) following Zuur et al. 2003. When difference in AICc (ΔAICc) was lower than two between these models, the more parsimonious model was selected (Burnham and Anderson, 2002). The selected models is represented in bold. Food ration was log-transformed for model selection. Table S5: Results of the selected mixed effect model on the oxygen consumption during feeding (Estimates,. Estimations of the predictors of all other fixed effects were based on the estimations of treatment 'warm temperature and small particles'. The selected model is presented using REML estimation. Food ration was log-transformed before regression. , 2002) following Zuur et al. 2003. When difference in AICc (ΔAICc) was lower than two 1106 between these models, the more parsimonious model was selected (Burnham and Anderson, 2002).

Fixed effects:

Predictors

1107

The selected models is represented in bold. Food ration was log-transformed for model selection.

Figure 1 :

 1 Figure 1: Conceptual framework of the two experiments on cocktail effects of food size (0.2

Figure 2 :

 2 Figure 2: Median oxygen consumption over time according to food ration for the 4

FiguresFig. S1 :

 S1 Figures

Fig. S2 :

 S2 Fig. S2: The entire setup was composed by (i) 2 large aerated buffer tanks that homogenized water quality between tanks and maintained constant water temperature over time and (ii) 8 small experimental tanks. Each 50L experimental tank, in which 10 individuals were reared, was modified as automated respirometer with a continuous water flow that ensured the homogeneity of the water parameters (indicated by yellow arrows). The renewal and excess water flows are indicated by white arrows. The two colors refer to the two water temperatures: 21°C in red and 16°C in blue.

Fig. S4 :

 S4 Fig. S4: Oxygen consumption over time from 06:00 a.m. and for 24 hours. The black line represents the original data of the oxygen consumption. The estimation of the daily oxygen consumption was calculated over a combination of two periods: (1) following original data from 06:00 a.m. until noon to catch the peak of oxygen consumption observed during the meal period (dashed blue line) and (2) smoothed values of the oxygen consumption after noon to avoid any outlier (e.g. peak at 19:30) that could distort daily consumption estimation (solid red line).

Fig. S5 :

 S5 Fig. S5: Smoothed oxygen concentration (A) and oxygen consumption (B) after the start of the meal. Oxygen consumptions were estimated every 30 seconds using linear regressions over 1 minute on smoothed oxygen concentrations (lines in A and corresponding points in B). The blue triangle represents the maximal oxygen consumption reached during the meal.

Fig. S6 :

 S6 Fig. S6: Boxplot of the daily oxygen consumption increase (relative to basal oxygen consumption and due to movement, food foraging and digestion) according to the food ration for the 4 experimental treatments: cool temperature and large particles (A), cool temperature and small particles (B), warm temperature and large particles (C) warm temperature and small particles (D). Dotted (for small particles) and solid lines (for large particles) represent the smooth increase of the median daily oxygen uptake in relation to the food ration. Grey bands represent 95% confidence intervals of smooth increases. White colour represents data during days of fasting, while light and dark grey represent small and large particles, respectively. Blue and red colours represent cool (16°C) and warm (21°C) temperatures, respectively. Only slopes (i.e. oxygen consumption) with R squared ≥ 0.95 were used. Sample size (i.e. number of days) is given as 'n' at the bottom of each panel. Outliers were removed for clarity purpose.

Fig. S7 :

 S7 Fig. S7: Diagnostic plots of the selected model for the daily oxygen consumption. A: Fitted values versus residuals. B: Q-Q plot of the residuals. C: Residuals versus Tank ID. D: Residuals versus Food ration. E: Residuals versus Food size. F: Residuals versus Temperature.

Fig. S8 :

 S8 Fig.S8: Boxplot of the oxygen consumption increase during feeding (relative to the previous 2.5h oxygen consumption) according to the food ration for the 4 experimental treatments: cool temperature and large particles (A), cool temperature and small particles (B), warm temperature and large particles (C) warm temperature and small particles (D). Dotted (for small particles) and solid lines (for large particles) represent the smooth increase of the median daily oxygen uptake in relation to the food ration. Grey bands represent 95% confidence intervals of smooth increases. White colour represents data during days of fasting, while light and dark grey represent small and large particles, respectively. Blue and red colours represent cool (16°C) and warm (21°C) temperatures, respectively. Only slopes (i.e. oxygen consumption) with R squared ≥ 0.95 were used. Sample size (i.e. number of meals) is given as 'n' at the bottom of each panel. Sample size is greater for food ration below 0.6% because results from experiments 1 and 2 are gathered here (n = 8 and n = 16 for experiment 1 and experiment 2, respectively). Outliers were removed for clarity purpose.

Fig. S9 :

 S9 Fig. S9: Diagnostic plots of the selected model for the oxygen consumption during feeding. A: Fitted values versus residuals. B: Q-Q plot of the residuals. C: Residuals versus Tank ID. D: Residuals versus Food ration. E: Residuals versus Food size. F: Residuals versus Temperature.

Fig. S10 :

 S10 Fig. S10: Boxplot of the oxygen consumption increase (relative to basal oxygen consumption) during the digestion (here 1.5 hour after the beginning of the meal period) according to the food ration for the 4 experimental treatments: cool temperature and small particles (A), cool temperature and large particles (B), warm temperature and small particles (C) warm temperature and large particles (D). Dotted (for small particles) and solid lines (for large particles) represent the increase of the median oxygen uptake during digestion in relation to the food ration. Grey bands represent 95% confidence intervals of smooth increases. White color represents data during days of fasting, while light and dark grey represent small and large particles, respectively. Blue and red colors represent cool (16°C) and warm (21°C) temperature, respectively. Sample size (i.e. number of meals) is given as 'n' at the bottom of each panel.

Fig. S11 :

 S11 Fig. S11: Diagnostic plots of the selected model for the oxygen consumption during digestion. A: Fitted values versus residuals. B: Q-Q plot of the residuals. C: Residuals versus Tank ID. D: Residuals versus Food ration. E: Residuals versus Food size. F: Residuals versus Temperature.

Fig. S13 :

 S13 Fig. S13: Diagnostic plots of the selected model for the maximum oxygen consumption during feeding. A: Fitted values versus residuals. B: Q-Q plot of the residuals. C: Residuals versus Tank ID. D: Residuals versus Food ration. E: Residuals versus Food size. F: Residuals versus Temperature.

Fig. S14 :

 S14 Fig. S14: Boxplot of the feeding duration according to the food ration for the 4 experimental treatments: cool temperature and small particles (A), cool temperature and large particles (B), warm temperature and small particles (C) warm temperature and large particles (D). Dotted (for small particles) and solid lines (for large particles) represent the variations of the median feeding duration on relation to the food ration. Grey bands represent 95% confidence intervals of smooth increases. Light and dark grey represent small and large particles, respectively.

Fig. S15 :

 S15 Fig. S15: Diagnostic plots of the selected model for the feeding duration. A: Fitted values versus residuals. B: Q-Q plot of the residuals. C: Residuals versus Tank ID. D: Residuals versus Food ration. E: Residuals versus Food size.

  Food ration) x Temperature + Food size -2875.4 5764.9 15.4 ~ log(Food ration) x Food size + Temperature x Food size -2875.7 5767.7 18.2 ~ log(Food ration) x Food size + Temperature -2880.3 5774.8 25.3 ~ log(Food ration) + Food size x Temperature -2880.8 5775.7 26.2 ~ log(Food ration) x Food size -2884.1 5780.4 30.8 ~ log(Food ration) + Food size + Temperature -2885.2 5782.6 33.1 ~ log(Food ration) + Food size -

  . Altogether, the results indicate that energy balance can be a major mechanism explaining shrinking of fish populations globally. Declines in prey size could impact the energy balance of individuals when their energy expenditures are increased by warmer temperatures, with future projections of prey resources predicting a decline of prey biomass and quality.

	sardine?	Marine	Environmental	Research,	170,	105441.
	https://doi.org/10.1016/j.marenvres.2021.105441

Table S2 :

 S2 Results of the selected mixed effect model on the daily oxygen consumption (Estimates, 95% confidence intervals and p-values). Estimations of the predictors of all other fixed effects were basedon the estimations of treatment 'warm temperature and small particles'. The selected model is presented using REML estimation.

	Fixed effects:
	Predictors	Estimates	95% CI	p-value
	(Intercept)	555.39	313.23 -797.54	<0.001
	Food ration	868.58	751.42 -985.74	<0.001
	Food size [Large]	106.34	-19.32 -232.00	0.097
	Temperature [Cool]	-41.06	-371.97 -289.84	0.807
	Food size [Large] x Food ration	-294.84	-430.28 --159.40	<0.001
	Temperature [Cool] x Food ration	-308.42	-443.85 --172.98	<0.001
	Random Effects:
	σ 2	100091.73
	τ00 Tank	48311.87
	ICC	0.33
	N Tank	8
	Observations	255
	Marginal R 2 / Conditional R 2	0.490 / 0.656

Table S4 :

 S4 Results of model selection on the oxygen consumption during feeding (df, logLik, AICc and ΔAICc). The best-fitting model was selected based on the lowest AICc values

Table S7 :

 S7 Results of the selected mixed effect model on the oxygen consumption during digestion (Estimates, 95% confidence intervals and p-values). Estimations of the predictors of all other fixedeffects were based on the estimations of treatment 'warm temperature and small particles'. The selected model is presented using REML estimation.

	Fixed effects:
	Predictors (Intercept) (Intercept) log(Food ration) Food ration Food size [Large] Food size [Large] Temperature [Cool] Temperature [Cool] log(Food ration) x Food size [Large] Food ration x Food size [Large] log(Food ration) x Temperature [Cool] Food ration x Temperature [Cool]	Estimates Estimates 324.08 212.24 72.58 643.27 -156.87 187.13 -70.01 -17.63 -15.81 -232.56 -20.29 -221.02	95% CI 95% CI 314.62 -334.98 33.29 -391.20 67.01 -78.72 536.00 -750.54 -168.88 --146.69 72.08 -302.18 -83.52 --56.74 -257.48 -222.22 -23.06 --9.52 -356.57 --108.56 -27.06 --13.52 -345.02 --97.01	p-value p-value 0.020 <0.001 <0.001 <0.001 0.002 <0.001 0.885 <0.001 <0.001 <0.001 <0.001 0.001
	Food size [Large] x Temperature [Cool] Random Effects:		14.05	2.76 -25.94	0.015
	σ 2 Random Effects: σ 2 τ00 Tank	83904.80 1106.87 22833.11
	τ00 Tank ICC	29.07 0.21
	ICC N Tank	8	0.03
	N Tank Observations	8 255
	Observations Marginal R 2 / Conditional R 2	509 0.410 / 0.536
	Marginal R 2 / Conditional R 2		0.863 / 0.867

Table S8 :

 S8 Results of model selection on the maximal oxygen consumption during feeding (df, logLik, 1104AICc and ΔAICc). The best-fitting model was selected based on the lowest AICc values(Burnham and 1105

	Anderson

Acknowledgments

We would like to thank colleagues at the IFREMER experimental station for their welcome and their fruitful advice during the conceptualization of the experiments. We would also like to express our thanks to the two anonymous reviewers for their comments that helped us improve the manuscript.

Funding

The study was funded by the MUSE Key Initiative Sea and Coast.

Data availability

Data and scripts are available here: https://zenodo.org/record/8413664.

Supplementary material

Material and methods

Each respirometer was shaped by a vertical PVC pipe and included three perforated semi-cylinders of PVC pipe in its interior section (Fig. S2). An external pump was connected to this system to collect water from one semi-cylinder and deliver it to the two other semi-cylinders, so water was constantly mixed in the respirometer (yellow arrows in Fig. S2). Outside of measurement period, respirometer water was renewed with water pumped from continuously aerated buffer tanks (300 L) into the same hemispheres that the external pump to maintain dissolved O2 concentrations close to saturation (i.e. 100 %)(white arrows in Fig. S2). Excess of water was collected through a PVC pipe and returned to its given buffer tanks. These buffer tanks were supplied with the same seawater and the temperatures were maintained equal to either 16°C (cool) or 21°C (warm), maintaining constant temperature in respirometers. Pumps in buffer tanks were controlled by an electrical timer and were turned off during measurements and water level settled at the overflow to provide a constant volume (50 L). Large buffer tanks were continuously supplied with water pumped from the sea, filtered through sand filter (30-40 µm) and sterilized with UV light. The photoperiod was adjusted to 12-12h cycle. S1: Results of model selection on the daily oxygen consumption (df, logLik, AICc and ΔAICc).

1049

The best-fitting model was selected based on the lowest AICc values (Burnham and Anderson, 2002) 1050 following Zuur et al. 2003. When difference in AICc (ΔAICc) was lower than two between these models, 1051 the more parsimonious model was selected (Burnham and Anderson, 2002) Zuur et al. 2003. When difference in AICc (ΔAICc) was lower than two between these 1092 models, the more parsimonious model was selected (Burnham and Anderson, 2002) (Burnham and Anderson, 2002) following Zuur et al. 2003. When difference in AICc (ΔAICc) was lower than two between these models, the more parsimonious model was selected (Burnham and Anderson, 2002). The selected models is represented in bold. Food ration was second order polynomial transformed for model selection.