Elvire Bestion
email: e.bestion@outlook.com

Andrea Soriano-Redondo

Julien Cucherousset

Staffan Jacob

Joël White

Lucie Zinger

Lisa Fourtune

Lucie Di Gesu

Aimeric Teyssier

Julien Cote

Altered trophic interactions in warming climates: consequences for predator diet breadth and fitness

Keywords: climate change, niche breadth, diet specialization, stable isotope analysis, gut microbiota, Zootoca vivipara

Species interactions are central in predicting the impairment of biodiversity with climate change. Trophic interactions may be altered through climate-dependent changes in either predator food preferences or prey communities. Yet, climate change impacts on predator diets remain surprisingly poorly understood. We experimentally studied the consequences of 2°Cwarmer climatic conditions on the trophic niche of a generalist lizard predator. We used a system of semi-natural mesocosms housing a variety of invertebrate species and in which climatic conditions were manipulated. Lizards in warmer climatic conditions ate a greater predatory to phytophagous invertebrate ratio and had smaller individual dietary breadths. These shifts mainly arose from direct impacts of climate on lizard diets rather than from changes in prey communities. Dietary changes were associated with negative changes in fitness-related traits (body condition, gut microbiota) and survival. We demonstrate that climate change alters trophic interactions through top-predator dietary shifts which might disrupt eco-evolutionary dynamics.

Introduction

Ongoing climate change is a major threat to biodiversity [1] and ecosystem functioning [2]. Climate warming notably alters community and ecosystem functioning through changes in trophic interactions with consequences for the fitness of all species [1,3,4]. This alteration may result from changes in species compositions in prey communities across trophic levels or from changes in the diet of predators. In ectotherms, all physiological processes are temperature-dependent [5]. Because a rise in temperature causes metabolic rates to increase more rapidly than ingestion rates [6,7], warmer temperatures can lead to energy loss and reduced survival in ectotherm predators. One way to avoid starvation in warmer climates is for predators to increase consumption rate [8], potentially through decreasing their selectivity towards certain prey. Alternatively, predators could shift their diet towards more energy-rich prey [9][10][START_REF] Vejříková | Distribution of Herbivorous Fish Is Frozen by Low Temperature[END_REF] which could lead to an increased dietary specialization [START_REF] O'gorman | Temperature effects on fish production across a natural thermal gradient[END_REF]. On the other hand, climate warming may change prey community composition resulting in modified predator diet [START_REF] Petchey | Environmental warming alters foodweb structure and ecosystem function[END_REF]. For instance, within the prey community, climate change should disproportionately affect prey species with higher trophic position [START_REF] Petchey | Environmental warming alters foodweb structure and ecosystem function[END_REF][START_REF] Voigt | Trophic levels are differentially sensitive to climate[END_REF], thus forcing their predators to feed on lower trophic levels. Changes in prey community composition with warmer climates might lead dietary generalists to better survive warmer climates as they would be less dependent on specific prey items [START_REF] Lurgi | Novel communities from climate change[END_REF]. Impacts of climate change on predator diet could thus come from temperature-dependent changes in predator energy and nutrient demands or from bottom-up changes in prey communities. Changes in predator diets could subsequently affect predator life history traits (e.g. body growth and condition [START_REF] Skinner | Effects of Diet Restriction and Diet Complexity on Life History Strategies in Side-Blotched Lizards (Uta stansburiana)[END_REF]) and extended phenotype (e.g. gut microbial communities [START_REF] Bolnick | Individuals' diet diversity influences gut microbial diversity in two freshwater fish (threespine stickleback and Eurasian perch)[END_REF]), leading to changes in fitness. Further, changes in diet should modify predator top-down control of lower trophic levels. Despite the importance of such climate-driven eco-evolutionary dynamics, no study to our knowledge has investigated the two mechanisms underlying climatedependent changes in predator diet and their consequences on their fitness. Here we studied the consequences of 2°C-warmer climatic conditions on the trophic niche of a generalist predator, the common lizard (Zootoca vivipara). We used a system of semi-natural mesocosms in which climatic conditions can be manipulated to create present-day climatic conditions and +2°C warmer climatic conditions, in line with IPCC predictions [START_REF]Climate change 2013: the physical science basis : Working Group I contribution to the fifth assessment report of the Intergovernmental Panel on Climate Change[END_REF]. We have previously shown that climatic conditions affected lizard population dynamics, dispersal and gut microbiota [START_REF] Bestion | Dispersal response to climate change: scaling down to intraspecific variation[END_REF][START_REF] Bestion | Live Fast, Die Young: Experimental Evidence of Population Extinction Risk due to Climate Change[END_REF][START_REF] Bestion | Climate warming reduces gut microbiota diversity in a vertebrate ectotherm[END_REF]. We aimed at understanding whether climatic conditions could have affected lizards through changes in diet and subsequent changes in central phenotypic traits (body condition (size-corrected body mass), gut microbiota) and fitness. We characterised lizard trophic niches through stable isotope analyses, using δ 15 N, which is a proxy of trophic position, and δ 13 C, which can signal the reliance on different primary producers [START_REF] Newsome | A niche for isotopic ecology[END_REF]. We further studied the pathways of climate impacts on lizard niche through structural equation modelling and investigated potential implications on lizard phenotype and fitness. We predicted that warmer climatic conditions should result in a decrease in lizard trophic positions because warming would decrease the abundance of predatory prey. Alternatively, an increase of energy demands at higher temperature should generate a shift towards a more generalized diet. The diet shift should be linked to lizard phenotypic traits and we should see no impact on lizard fitness when diet shifts can compensate increased energy demands and changes in prey communities.

Results

Impact of climatic conditions on lizard and invertebrate stable isotope values

δ 13 C values for both detritivorous and phytophagous invertebrates were higher in warmer climatic conditions but not for predatory invertebrates, while there were no significant differences between climatic conditions on δ 15 N values from all three invertebrate prey categories (Table S1A). Lizards from warmer climatic conditions had higher δ 13 Ccor values (i.e. δ 13 C corrected for prey δ 13 C) and non-significantly higher δ 15 Ncor values than individuals from present-day climatic conditions (Table 1, Fig. 1). Adults had higher δ 15 Ncor and δ 13 Ccor values than juveniles (Table 1, Fig. 1).

Impact of climatic conditions on lizard trophic niche

The population niche breadth, assessed by stable isotope standard ellipse areas (SEAc), was narrower in warmer climatic conditions for adults, while juveniles had a wider population niche breadth in warmer climatic conditions (no 95 % CI overlap, Fig 1b). Further, climate change led to a differentiation of populations along the two stable isotope axes as overlap among SEAc ellipses was smaller than expected by chance (adults: overlap = 0.13, p < 0.0001, juveniles: overlap = 0.08, p < 0.0001, Fig. 1). At the individual level, both adult and juvenile lizards were more specialized in warmer than in present-day climatic conditions (Fig. 2a, Table 1). They consumed fewer phytophagous invertebrates and more predatory invertebrates in warmer climatic conditions than in presentday conditions ( phytophagous invertebrate abundance (coef = -0.36*-0.29 = 0.10). There was also a positive effect of age on predatory specialization (coef = 0.17) (Fig. 3, Table S2A). Diet represents the predator specialization (PC1, Fig. S2A). The best path model includes direct effect of climate and indirect effect of climate through changes in predatory and phytophagous invertebrate abundances, but not on detritivorous invertebrate abundances (Table S2A). Solid and dashed lines represent positive and negative values, respectively, and their width is proportional to the value of the patch coefficient (shown with mean and 95% CI). N = 327.

Implications of diet change on lizards' body condition, microbiota and survival

Adult body condition in September was not linked to any of the dietary components (Table 2), while there was an interactive effect of climate and the green-brown food axis (proportion of detritivorous versus phytophagous prey eaten, PC2 axis, Fig S2A) on juvenile body condition (p = 0.02, Table 2). Here, juveniles eating more detritivorous prey (i.e. higher scores on PC2) had a lower body condition in warmer climatic conditions only. Lizard gut microbiota diversity, an important trait for their fitness [START_REF] Bestion | Climate warming reduces gut microbiota diversity in a vertebrate ectotherm[END_REF], was linked to their diet. We found a significant interaction between predator specialization and climate on bacterial community diversity, measured by its Shannon index, where lizards highly specialized towards eating predators harboured less diverse communities in warmer climatic conditions, but there was no effect of predator specialization on diversity in present-day climates (p = 0.008, Table S4A, Fig 4a). (a) Gut bacterial community diversity (Shannon index) as a function of adult predator specialization (Fig. S2A). High values of the principal component denote lizards with a high level of specialization towards eating predators. There is a significant interaction between predator specialization and climatic conditions (see Table S4A). N = 135. (b) Survival probability as a function of adult predator specialization. There is no interaction between predator specialization and climatic conditions (Table 2). Blue: present-day climatic treatment, red: warm climatic treatment. N = 152.

Adult lizard subsequent Winter-Spring survival was negatively correlated to the pre-winter specialization towards predatory invertebrates (p = 0.042, Fig. 4b, Table 2) while there was no such relationship in juveniles (Table 2). There was no interaction between any of the dietary axes and climatic conditions on survival (Table 2).

Discussion

Our study highlights how climatic conditions, prey communities and predator traits interact in driving trophic interactions. Warmer climatic conditions led to higher δ 13 C values in both lizards and invertebrates. Carbon stable isotopes often signal the relative contributions of different functional groups of primary producers or changes in the environment caused by abiotic conditions like temperature and moisture [START_REF] Newsome | A niche for isotopic ecology[END_REF][START_REF] Sackett | Temperature Dependence of Carbon Isotope Composition in Marine Plankton and Sediments[END_REF], as found in skinks in response to habitat fragmentation [START_REF] Resasco | Generalist predator's niche shifts reveal ecosystem changes in an experimentally fragmented landscape[END_REF]. Further, δ 15 N values tended to be higher in warmer climatic conditions for lizards but not for invertebrates and higher for adult lizards relative to juveniles. This suggested that lizards fed on higher trophic levels in warmer conditions, as found in trout [START_REF] O'gorman | Temperature effects on fish production across a natural thermal gradient[END_REF]. Because we corrected lizard stable isotope signature by those of their prey, the differences in lizard stable isotope values result from a difference in the prey species consumed by lizards and not from a shift in invertebrate values. Warmer climatic conditions reduced the relative proportion of phytophagous versus predatory invertebrates in lizard diets. This dietary shift was mainly due to a direct effect of climatic conditions on the lizards and to a lesser extent by climate-driven changes in prey abundance.

Because climate change should impact species at higher trophic levels more [START_REF] Voigt | Trophic levels are differentially sensitive to climate[END_REF], we could have expected lizards to decrease their trophic position due to a decline in the abundance of predatory invertebrates. Warmer climatic conditions indeed decreased lizard specialization towards predators through a lower abundance in predatory invertebrates. However, this negative indirect impact of warmer climatic conditions was quite weak (-0.10), and overwhelmed by a strong (0.43) direct positive impact of climate on predator specialization. This suggests that lizards actively shifted their diet in warmer climatic conditions. Such a dietary shift has been found in brown trout (Salmo trutta) from a natural thermal gradient, where the trophic position of brown trout increased with temperature [START_REF] O'gorman | Temperature effects on fish production across a natural thermal gradient[END_REF]. Several hypotheses about elemental stoichiometry could drive diet shifts with temperature. Because temperature is linked to metabolic rates [5], higher temperatures should lead to a higher demand for carbon (respiration) than for nitrogen and phosphorus [START_REF] Cross | Interactions between temperature and nutrients across levels of ecological organization[END_REF]. This has led several species, from copepods to fish, to switch towards greater herbivory owing to the higher C content of plants [9][10][START_REF] Vejříková | Distribution of Herbivorous Fish Is Frozen by Low Temperature[END_REF].

Conversely, higher temperatures should lead to higher protein denaturation rates, thus increasing N demands [START_REF] Lemoine | Increased temperature alters feeding behavior of a generalist herbivore[END_REF] as found in grasshoppers [START_REF] Schmitz | Temperature dependence of predation stress and the nutritional ecology of a generalist herbivore[END_REF]. Finally, as growth rate is linked to phosphorus demand, increased growth rates with warming would thus lead to increased P demands [START_REF] Elser | Organism Size, Life History, and N:P Stoichiometry[END_REF][START_REF] Persson | Increased risk of phosphorus limitation at higher temperatures for Daphnia magna[END_REF]. Given that invertebrate predators display a higher N and P content than herbivores for a similar C content [START_REF] González | The Multidimensional Stoichiometric Niche[END_REF], a shift towards eating more predators should not be linked to increased C demands but instead to higher N and/or P demands. As juveniles grow faster in warm climates [START_REF] Bestion | Live Fast, Die Young: Experimental Evidence of Population Extinction Risk due to Climate Change[END_REF], they might shift towards eating predators to fulfil their phosphorus demands. On the contrary, adult growth is much slower, but they also suffer more from warmer climates, with a decreased survival [START_REF] Bestion | Live Fast, Die Young: Experimental Evidence of Population Extinction Risk due to Climate Change[END_REF]. Warmer climates might mean more maintenance costs to repair proteins [START_REF] Lemoine | Increased temperature alters feeding behavior of a generalist herbivore[END_REF], which might explain their shift towards N-and P-rich predatory invertebrates. Future work should aim at better understanding the mechanism of climateinduced lizard dietary shifts.

Lizard individual dietary breadth declined with warmer climatic conditions; i.e. both adults and juveniles became more specialized. Although this lower niche breadth at the individual level translated into narrower niche breadth at the population level in adults, juvenile diet specialization in warmer climatic conditions led to a wider population niche breadth. This result suggests that warmer climatic conditions induced a shift in juveniles from a homogeneous generalist population composed of generalist individuals to a heterogeneous generalist populations made of individuals specialized on different groups of prey [START_REF] Bolnick | The Ecology of Individuals: Incidence and Implications of Individual Specialization[END_REF]. On the contrary, the greater specialization of adult lizards at the individual level in warm climates resulted into a lower population niche breadth, suggesting that all adult individuals shifted their diet towards eating more predatory invertebrates. These results match the previously observed effects of warmer climatic conditions on juveniles' and adults' life history traits, where climate change favoured growth in juveniles but reduced survival in adults [START_REF] Bestion | Live Fast, Die Young: Experimental Evidence of Population Extinction Risk due to Climate Change[END_REF]. Here, individual dietary specialization towards predators had an overall negative impact on adult Winter-Spring survival, while there was no impact on juvenile survival. The difference between adults and juveniles could be due to differences in metabolic demands, translating into different foraging strategies and thus intraspecific competition. Metabolic rates scale with body size and temperature in ectotherms [5]. Juvenile metabolic demands likely increased in warmer climatic conditions, which might push them to consume a higher biomass of prey. Juveniles' small size limits the size of prey they can eat, including the biggest and potentially more dangerous predatory invertebrates [START_REF] Brose | Consumer-Resource Body-Size Relationships in Natural Food Webs[END_REF]. Accordingly, juveniles were here found to eat on lower trophic levels than adults. The observed increased growth rate in warmer climatic conditions [START_REF] Bestion | Live Fast, Die Young: Experimental Evidence of Population Extinction Risk due to Climate Change[END_REF] might allow juveniles to choose from a wider array of prey including bigger predatory invertebrates.

Because different juveniles focus on different prey items (as shown by the larger population niche breadth), they should avoid increased competition and thus overcome their increased energy demands in warmer climates. Adult individuals already eat more predatory invertebrates than juveniles. They might be more constrained in their metabolic response to climate and forced to specialize even more on larger, more rewarding prey. Such large prey are however rarer, thus lowering encounter rates. The resulting stronger competition may lead to lower per capita intake and decreased survival [START_REF] Bestion | Live Fast, Die Young: Experimental Evidence of Population Extinction Risk due to Climate Change[END_REF]. This negative impact may be further worsened by phenotypic changes concomitant with diet shift. The predator specialization was indeed linked to a lower gut microbiota diversity in warm climatic conditions. Such lower microbiota diversity might explain reported impacts of climate on lizard microbiota and survival. We previously showed that warmer temperatures lead to a less diverse microbiota which was correlated with a lower subsequent survival [START_REF] Bestion | Climate warming reduces gut microbiota diversity in a vertebrate ectotherm[END_REF]. Because higher gut microbiota diversity is often beneficial to their hosts [START_REF] Bolnick | Individuals' diet diversity influences gut microbial diversity in two freshwater fish (threespine stickleback and Eurasian perch)[END_REF], a reduced diversity due to climate-driven dietary changes should be detrimental, particularly if it affects essential functions such as immunity or digestion [START_REF] Gilbert | A Symbiotic View of Life: We Have Never Been Individuals[END_REF]. On the other hand, changes in gut microbiota might not be the consequence but the cause of the observed dietary shifts if it changes the relationship between digestive performance and temperature. For instance, in salamanders, the relative abundance of some bacterial taxa was correlated to energy assimilation, and both depended on temperature [START_REF] Fontaine | Environmental temperature alters the digestive performance and gut microbiota of a terrestrial amphibian[END_REF]. Thus the link we previously observed between lizard gut microbiota and survival would be the consequence of the microbiota-induced dietary shift. Future studies should disentangle whether climate-dependent diet shift induced microbiota changes or the other way around.

We further found that prey abundances were weakly affected by lizard diet, with a slightly lower density of phytophagous invertebrates when lizards tend to feed more on them (Supplementary Section S5). This weak top-down impact on prey communities may however strengthen in the long term, and interact with the observed bottom-up effects of prey abundance on lizard diet. The climate-driven changes in predator physiology could then lead to changes in the whole food web structure and functioning from bacteria to invertebrate communities through both top-down and bottom-up effects. For instance in pitcher plants, higher temperature leads to increased importance of top-down versus bottom-up effects on protozoan communities [START_REF] Hoekman | Turning up the heat: Temperature influences the relative importance of topdown and bottom-up effects[END_REF]. Together, these results show the importance of considering bottom-up and top-down drivers of trophic interactions to further understand how climate change affects species and communities [START_REF] Rosenblatt | Climate Change, Nutrition, and Bottom-Up and Top-Down Food Web Processes[END_REF]. Given the importance of trophic interaction strength on prey population dynamics, and the potential for climate change to affect trophic interaction strength [START_REF] Sentis | Predator diversity and environmental change modify the strengths of trophic and nontrophic interactions[END_REF], further work should focus on how climate-induced changes in diet will affect trophic interaction strength in a multi-species context.

Methods

Species and experimental system

The common lizard (Zootoca vivipara; Jacquin 1787) is a small (snout-vent length 50 -70 mm) lizard foraging actively on a wide variety of invertebrate species including Araneae, Coleoptera, Orthoptera, Heteroptera, Homoptera, Diptera, Hymenoptera, Gasteropods, Isopods and Lepidoptera caterpillars [START_REF] Avery | Food and feeding habits of the Common lizard (Lacerta vivipara) in the west of England[END_REF][START_REF] González-Suárez | Disentangling the effects of predator body size and prey density on prey consumption in a lizard[END_REF]. Lizards used in this study are part of a wider study on the consequences of climate change on populations [START_REF] Bestion | Dispersal response to climate change: scaling down to intraspecific variation[END_REF][START_REF] Bestion | Live Fast, Die Young: Experimental Evidence of Population Extinction Risk due to Climate Change[END_REF][START_REF] Bestion | Climate warming reduces gut microbiota diversity in a vertebrate ectotherm[END_REF] Lizards were individually marked by toe-clipping at birth and were maintained in the Metatron, an infrastructure composed of 48 semi-natural caged enclosures acting as mesocosms (Ariège, France, 43°01' N, 1°05' E). Each mesocosm is 10 x 10 m and is fully enclosed by tarpaulin and fine-meshed nets; it acts as a mini-ecosystem, with natural vegetation and invertebrate communities, and a wide variety of thermal micro-habitats (dense vegetation, rocks and logs, ponds [START_REF] Bestion | Dispersal response to climate change: scaling down to intraspecific variation[END_REF][START_REF] Bestion | Live Fast, Die Young: Experimental Evidence of Population Extinction Risk due to Climate Change[END_REF]). Diversity within these caged habitats is relatively high (30 ± 3 invertebrate families per mesocosm, see below). Climatic conditions within mesocosms are monitored continuously and can be manipulated through motor-driven shutters [START_REF] Bestion | Dispersal response to climate change: scaling down to intraspecific variation[END_REF][START_REF] Bestion | Live Fast, Die Young: Experimental Evidence of Population Extinction Risk due to Climate Change[END_REF].

Experimental procedure

In [START_REF]Climate change 2013: the physical science basis : Working Group I contribution to the fifth assessment report of the Intergovernmental Panel on Climate Change[END_REF], see [START_REF] Bestion | Live Fast, Die Young: Experimental Evidence of Population Extinction Risk due to Climate Change[END_REF] for more details about climatic treatments). There was no difference between treatments in the abundance of invertebrate prey communities at the beginning of the experiment (difference in abundance of predatory invertebrates between enclosures, PC: 31.4 ± 4.4, WC: 29 ± 6.6, p = 0.53, of phytophagous, PC: 27.6 ± 6.5, WC: 37.6 ± 7.3, p = 0.55, of detritivorous, PC: 8.2 ± 5.4, WC: 5.4 ± 1.7, p = 0.83, assessed in May 2013 following the same sampling procedure as below).

We released a total of 612 lizards, 264 adults (including two-and-more year olds (2+yo) and one-year-olds (1yo)) and 348 juveniles. Adults were previously maintained for one year inside the Metatron and recaptured in May 2013 to monitor female parturition in laboratory. Juveniles were born in terraria between June and July 2013 (see [START_REF] Bestion | Live Fast, Die Young: Experimental Evidence of Population Extinction Risk due to Climate Change[END_REF] for more details). Before being released into the Metatron, all lizards were measured, weighted and marked and a tail tip was taken from adults (but not from juveniles as they were too small to be sampled at birth) for stable isotope analyses. This procedure enables non-lethal sampling. Lizards were then released into the Metatron controlling for body size [START_REF] Bestion | Live Fast, Die Young: Experimental Evidence of Population Extinction Risk due to Climate Change[END_REF]. There were no differences in stable isotope values before the climatic treatments were applied (δ 15 N: χ 2 = 0.27, p = 0.61, δ 13 C: χ 2 = 0.78, p = 0.38). Each population included 7 ± 1 2+yo males, 12 ± 1 2+yo females, 7 ± 2 1yo, and 35 ± 3 juveniles, conforming with local densities in natural populations [START_REF] Bestion | Live Fast, Die Young: Experimental Evidence of Population Extinction Risk due to Climate Change[END_REF]. We do not expect specific differences between 2+yo and 1yo; in contrast, juveniles both have a different diet [START_REF] Avery | Food and feeding habits of the Common lizard (Lacerta vivipara) in the west of England[END_REF] and react differently to climate [START_REF] Bestion | Live Fast, Die Young: Experimental Evidence of Population Extinction Risk due to Climate Change[END_REF] from adults. Consequently, we defined two age categories, i.e. juveniles and 'adults', the latter corresponding to 2+yo and 1yo.

Lizard condition, diet and survival assessment

Mid-September 2013, we recaptured all surviving lizards during multiple capture-recapture sessions. Captured lizards were measured for snout-vent length and body mass, which allowed to assess body condition as the residuals of body mass by snout-vent length [START_REF] Skinner | Effects of Diet Restriction and Diet Complexity on Life History Strategies in Side-Blotched Lizards (Uta stansburiana)[END_REF]. We also measured lizards extended phenotype as their gut microbiota community (in adults only as juveniles were too small to be sampled). Sampling, molecular and bioinformatics methods were identical to [START_REF] Bestion | Climate warming reduces gut microbiota diversity in a vertebrate ectotherm[END_REF].

We took a tail tip for stable isotope analyses. Tail tips were clipped at the start of the experiment and they regrew the tail during the experiment, thus the stable isotope values from the regrown tissue captured diet composition during the study period [START_REF] Cucherousset | Natal departure timing from spatially varying environments is dependent of individual ontogenetic status[END_REF][START_REF] Evangelista | Ecological opportunities and intraspecific competition alter trophic niche specialization in an opportunistic stream predator[END_REF]. Lizards were then released to hibernate in the Metatron.

Finally, we measured lizard Winter-Spring survival through repeated capture sessions in May 2014 allowing to capture all individuals [START_REF] Bestion | Live Fast, Die Young: Experimental Evidence of Population Extinction Risk due to Climate Change[END_REF].

Prey invertebrate community sampling

End of September 2013, we surveyed the invertebrate community to estimate relative invertebrate diversity and abundance within each mesocosm. We set up two pitfall traps (Ø 8 x 12 cm glass jars) within each mesocosm [START_REF] Bestion | Live Fast, Die Young: Experimental Evidence of Population Extinction Risk due to Climate Change[END_REF], a sampling effort in agreement with the literature [START_REF] House | Arthropods in no-tillage soybean agroecosystems: Community composition and ecosystem interactions[END_REF]. Pitfall traps were placed at least 1.5 m from the border of the mesocosms to prevent edge effects, in areas representative of the mesocosms plant cover, and separated by at least 5 m. Traps were left for 5 sunny days to trap crawling arthropods. We also performed two net-sampling sessions on sunny days with a Ø 25 cm sweep net to recover canopy arthropods and flying insects. Sampling effort led to recover 295 ± 91 invertebrate individuals per enclosure and 30 ± 3 families (Fig S1A). Recovered invertebrates were preserved at -20°C. Invertebrate individuals were identified to the family level under a binocular microscope. We then attributed families to a functional trophic group (predatory, detritivorous and phytophagous invertebrates) and calculated abundance per group. We selected 22 invertebrate families from the most abundant families relevant to lizard diet [START_REF] Avery | Food and feeding habits of the Common lizard (Lacerta vivipara) in the west of England[END_REF] for stable isotope analyses. These families represented 72 % of the individuals sampled in the mesocosms (Table S1B). Samples from lizards (tail tip) and invertebrates (whole organisms, composed of pooled items (n=3-20) to account for interindividual variation within mesocosms) were oven-dried at 60°C for 48h, ground and sent to Cornell Stable Isotope for carbon and nitrogen stable isotope analyses (δ 13 C and δ 15 N). Within trophic group variability in stable isotope values was low compared with between-group variability (Anova, F2,253 = 91, p <0.001 for δ 13 C, and F2,253 = 116, p <0.001 for δ 15 N).

Statistical analyses

Stable isotope analyses

We first studied whether climatic conditions affected prey stable isotope values with a mixed effect model of δ 13 C (resp. δ 15 N) depending on climatic treatment plus a random mesocosm effect for each of the prey sources with lmer package in R v3.4.2 (Table S1A). We then explored the impact of climate on lizards stable isotope values. Because isotope values for food sources vary among mesocosms (Table S1A-B), and to be able to perform betweenmesocosm comparisons, we performed a baseline correction of isotopic values previous to exploring climatic effects. δ 15 N values were corrected by subtracting the mean δ 15 N values of the primary consumers (phytophagous and detritivorous invertebrates) from each mesocosm (δ 15 Ncorr). δ 13 C values were corrected (δ 13 Ccorr) following [START_REF] Quevedo | The effect of small-scale resource origin on trophic position estimates in Perca fluviatilis[END_REF] by calculating the relative contribution of carbon originating from phytophagous invertebrates to lizards using a two endmember mixing model. We then fitted a global linear mixed model on δ 13 Ccor and δ 15 Ncor with climatic treatment and its two-way interactions with age class (juvenile or adult) and sex as fixed effects and mesocosm identity as random intercept. We then compared the global model to all derived simpler models with AIC using dredge function from MuMIn package to fit all combinations of fixed variables. As several models had close AICs, we used a model averaging method [START_REF] Grueber | Multimodel inference in ecology and evolution: challenges and solutions[END_REF].

To address the consequences of climate treatment on the stable isotope niche of lizard populations, we calculated standard ellipse areas (SEAc) of juveniles and adults in each treatment using δ 13 Ccorr and δ 15 Ncorr with siar package [START_REF] Jackson | Comparing isotopic niche widths among and within communities: SIBER -Stable Isotope Bayesian Ellipses in R[END_REF]. We tested for differences in SEAc between treatments by drawing 10000 bootstrapped samples resampling individual lizards from the two treatments to generate 95% CIs following [START_REF] Resasco | Generalist predator's niche shifts reveal ecosystem changes in an experimentally fragmented landscape[END_REF]. We tested for differentiation in the stable isotope niche between climates (overlap area between ellipses) using a permutation test drawing 10000 permuted ellipses, where p is the proportion of ellipses with a smaller than observed niche overlap following [START_REF] Resasco | Generalist predator's niche shifts reveal ecosystem changes in an experimentally fragmented landscape[END_REF].

Lizard diet composition

We then used stable isotope values to calculate the dietary contribution of each prey type to each individual lizard using a Bayesian mixing model with Simmr v0.3 [START_REF] Parnell | Simmr: Stable Isotope Mixing Models in R[END_REF] with the recommended values of 10000 iterations, a burning of 1000, a thinning of 10 and default priors (no prior information). As there is no specific trophic enrichment factor (TEF) for the common lizard available in the literature, we used TEF of tree lizards (Urosaurus ornatus), a species ecologically close to the common lizard: Δ 13 C 1.2 ‰ (± 0.4 SD) and Δ 15 N: 0.7 ‰ (± 0.3 SD) [START_REF] Lattanzio | Stable carbon and nitrogen isotope discrimination and turnover in a small-bodied insectivorous lizard[END_REF][START_REF] Lattanzio | Trophic niche divergence among colour morphs that exhibit alternative mating tactics[END_REF]. However, we ran sensitivity analyses varying the TEF by ± 1 ‰ around these values to check the consistency of our results, and we also checked for potential impacts of a change in TEF with temperature on our results, showing a robustness to variation in TEF (Supplementary Section S3). To account for potential differences in prey stable isotope signatures from the different mesocosms (climate-induced or not), we estimated diet composition by mesocosm, given that lizards only had access to the prey of their own mesocosm.

We explored the impact of climate on the mean proportion of each prey category consumed by the lizards using linear mixed models with the same structure as described above. Because proportions are not independent, we focused on the two preferred prey categories only [START_REF] Avery | Food and feeding habits of the Common lizard (Lacerta vivipara) in the west of England[END_REF], the predators and the phytophagous invertebrates, to prevent issues related to non-independency of statistical models.

Lizard dietary specialization

Lizard individual dietary specialization was quantified by calculating Levins' diet breadth index 𝐵 = 1 ∑ 𝑝𝑖 2 , where pi is the mean proportion of the ith prey [START_REF] Levins | Evolution in Changing Environments: Some Theoretical Explorations[END_REF]. This metric measures whether an individual is a perfect generalist (B = 3, eating each of the 3 prey categories evenly), a perfect specialist (B = 1, eating only one category of prey), or in between. We explored the impact of climate on individual dietary specialization (exp-transformed to avoid heteroscedasticity) with the same model structure as above.

Path analyses of lizard diet

We aimed to understand whether impacts of climate on lizard diets were driven by intrinsic effects of climate on the lizards themselves, or by climate-driven changes in prey abundances. We first summarized the variables linked to lizard diet into a principal component analysis, whose two first axes explained > 85% of the variance. PC1 correlated positively with the proportion of predatory invertebrates, δ 15 Ncorr, and negatively with Levins' dietary index (Fig S1A ), and therefore denotes a dietary specialization toward predator invertebrates (hereafter called predator specialization axis). PC2 was positively linked to the proportion of detritivorous invertebrates, and negatively to the proportion of phytophagous and to δ 13 Ccorr (Fig S1A ), and denotes inputs from the green and brown food webs (hereafter called green-brown food axis). As only PC1 was linked to climate (impact of climate on PC1: t = 2.161, p = 0.031; on PC2: t = 0.07, p = 0.94), we only analysed impacts on this first axis. We used path analysis using ggm package to build several causal models corresponding to the different biological hypotheses investigated ( [START_REF] Shipley | A New Inferential Test for Path Models Based on Directed Acyclic Graphs[END_REF], see Fig. S2B). The global model included the impact of climate on the abundance of the three prey groups, an impact of prey groups abundance on each other and the impact of lizard age, climate, and abundance of the three prey categories on lizard diet, represented by PC1 axis (Fig S2B). Variables were centred and scaled. We first verified whether data was well supported according to the d-sep test in which conditional dependencies were tested through linear regressions [START_REF] Shipley | A New Inferential Test for Path Models Based on Directed Acyclic Graphs[END_REF]. We then compared the fitted models from the different sets of hypotheses (Fig S2B ) through their AIC [START_REF] Shipley | The AIC model selection method applied to path analytic models compared using a d-separation test[END_REF] with the dsep.test function from [START_REF] Fourtune | User-friendly R functions for the application of the permutation-based d-sep test, clustering-based path analysis, permutation-based path analysis and a parametric bootstrap procedure dedicated to the handling of pairwise matrices in path analysis[END_REF][START_REF] Fourtune | Inferring Causalities in Landscape Genetics: An Extension of Wright's Causal Modeling to Distance Matrices[END_REF], and kept the model with the lowest AIC (Table S2A). We then estimated path coefficients and 95% confidence intervals on the best model with linear models.

Implications of lizard diet on lizard phenotype and fitness

Finally, we studied whether lizard condition in September (body condition and gut microbiota diversity (Shannon index), through linear mixed models) and future Winter-Spring survival (through generalised mixed models with binomial family) was linked to their dietary habits for adults and juveniles respectively.

Global models included the PC1 and PC2 diet and their interaction with climate, sex, juveniles' date of birth (Julian days) and for gut microbiota, sample sequencing depth (to control for differences in bacterial load) plus random mesocosm identity. Numeric variables were centred and scaled.

Supplementary section S1: Impact of climatic conditions on invertebrate stable isotope values Figure S1A: Rarefaction curves of invertebrate species richness per mesocosm

Blue: present-day climate, red: warm climate. While the capture effort was the same among mesocosms, the total number of recovered invertebrates varied due to differences in abundances among enclosures (295 ± 91 invertebrate individuals sampled per enclosure). However, the shape of the curves show that we were close to saturation for all enclosures, suggesting a relatively good sampling effort. The global path, containing all links, represents our first biological hypothesis, that is that diet is affected by age, a direct effect of climate and an indirect effect of climate through differences in abundances of prey types, while the abundances of prey types are linked together. A first set of models, set A, removing links 1 to 3 and their combinations, tests whether the abundances of prey types are actually dependent on each other. A second set of models, set B, removing links 4 to 6 and their combinations, represents the direct impact of climate on diet, while prey abundances affect diet independently of climate as climate does not affect prey abundance. A third set of models, set C, removing link 7, represent the hypothesis of an indirect effect of climate only, through climate-driven changes in prey abundances. A fourth set of models, set D, removing links 8 to 10 and their combinations, represents the direct impact of climate on diet, while prey abundances are affected by climate but do not affect lizard diet. Finally, a fifth set of models, set E, removing link 11, represents no impact of age on diet. We compared the fitted models from each of the 5 sets of models through their AIC with the dsep.test function and kept the model with the lowest AIC. The best model was a model from the fourth set of model, removing link 10 (Table S2A). We tested whether a better

Supplementary section S3: sensitivity analysis

Best practices in stable isotope ecology recommend the use of trophic enrichment factor if possible from the same species, or failing that for a species ecologically and taxonomically close [1]. There is very few data available for trophic enrichment factors in reptiles, and the only study giving both Δ 13 C and Δ 15 N values for trophic enrichment factors in lizards is for another species, Urosaurus ornatus [2,3]. Fortunately, this species is quite ecologically similar, with a small body size (up to 59 mm snout-vent length), and feeding on a similar range of invertebrates such as Araneae, Coleoptera, Orthoptera, Heteroptera, Homoptera, Diptera and Hymenoptera [2][3][4]. However, the true TEF for common lizards might still be different from the one of tree lizards. To ensure the reliability of our results, we hence ran a sensitivity analysis around the values of Urosaurus ornatus TEF.

We varied the TEF by 0.1 ‰ steps up to +1 and -1‰ from the values found by Lattanzio & Miles (2016a, b): Δ 13 C 1.2 ‰ (± 0.4 SD) and Δ 15 N: 0.7 ‰ (± 0.3 SD). We studied how changing the TEF changed the proportion of each prey source eaten by the lizards and the Levins' dietary index; and how it impacted the dietary differences between climatic conditions (Figures S3A-S3D, Tables S3A-S3B). Because there were no significant interactions between climatic conditions and age class or sex in the original models (Table 1), our analyses did not take into account interactions to simplify the models. We fitted models with climate, age, sex and random mesocosm identity to test the climate effect. Not surprisingly, changes in the TEF lead to changes in the proportion of each invertebrate group eaten (Fig S3A -S3B), however the differences between climatic conditions are relatively robust to changes in TEF. Δ 13 C TEFs higher than the reference value of 1.2 ‰ lead to more significant differences in the proportion of predatory and phytophagous invertebrates eaten, while TEFs lower than 1.2 ‰ lead to nonsignificant differences in the proportion of predatory invertebrates and TEFs lower than 1.1 ‰ lead to non-significant differences in the proportion of phytophagous invertebrates (Table S3A, Fig S3A). Δ 15 N TEFs higher than the reference value of 0.7 ‰ lead to significant differences in the proportion of predatory invertebrates, while TEFs up to 0.9 ‰ or lower lead to significant differences in the proportion of phytophagous invertebrates (Table S3B, Fig S3B). The differences in the Levins' dietary index are the most robust to variation in TEF, with significant differences apart from very low values of Δ 13 C TEF and very high and very low values of Δ 15 N TEF (Fig S3C -S3D, Table S3A-S3B). Overall, these results suggest that the differences between climatic conditions in lizard dietary habits are robust to variation in the trophic enrichment factor, particularly for values of Δ 13 C TEF higher than 1.2 ‰ and values of Δ 15 N TEF lower than 0.7 ‰. These values are consistent with TEF values for other reptiles, with Δ 13 C TEF values as high as 2.29 ‰ for snakes' muscle [5], and 1.06 ‰ for crocodiles' muscle [6], although another study on lizards found extremely low values of -1.9 ‰ for lizards' muscle, without characterizing Δ 15 N TEF [7], and with Δ 15 N TEF values as low as -2.50 ‰ for crocodiles' muscle [6]. Other studies have used a meta-analysis on birds' Δ 15 N TEF to approximate lizards' trophic enrichment [8], which would amount to a TEF of 0.8 ‰ for birds' muscle [9], very close to the 0.7 ‰ value used in this study.

Another issue is that TEF could change with temperature. Although there is no literature on variation in TEF with temperature in reptiles, one study shows that a +5°C increase in temperature can lead to both a -0.6 ‰ decrease in Δ 15 N TEFs and a +0.4 ‰ increase in Δ 13 C TEFs in fish [10]. We thus studied how a decrease in Δ 15 N TEFs (resp. an increase in Δ 13 C TEFs) in warm climates compared to present-day climates could affect our results. We first studied a change in Δ 15 N. Δ 13 C was thus fixed at 1.2 ‰ and Δ 15 N was fixed at the reference value of 0.7 ‰ in present-day climate, but was allowed to vary between 0.7-0 and 0.7-0.6 ‰ in warm climates (Table S3C). We then repeated the analysis focusing on changes in Δ 13 C. Δ 15 N was thus fixed at 0.7 ‰ and Δ 13 C was fixed at the reference value of 1.2 ‰ in present-day climate, but was allowed to vary between 1.2+0 and 1.2+0.6 ‰ in warm climates (Table S3D).

Our results are very robust to potential variations in TEF with temperature, with impacts of climate on the proportion of predatory invertebrates eaten becoming more significant, and impacts of climate on the proportion of phytophagous invertebrates eaten being mainly robust, except for very high increases in Δ 13 C for which the impact of climate on the proportion of phytophagous invertebrates became non-significant (Table S3C-S3D). The differences in Levins' index were always significant (Table S3C-S3D). Table S3D: Impact of variation in the Δ 15 N TEF between warm and present-day climatic conditions on the statistical significance of the difference between climatic conditions in the proportion of predatory and phytophagous prey eaten, as well as the Levins' index.

Δ 13 C is fixed at 1.2 ‰ and Δ 15 N is fixed at the reference value of 0.7 ‰ in present-day climate, but is allowed to vary between 0.7-0 and 0.7-0.6 ‰ in warm climates. For each value of Δ 15

Figure 1 :

 1 Figure 1: Impact of climate on lizard corrected stable isotope values and population niche breadth (a) Bivariate plot of lizard corrected δ 13 C and δ 15 N values by age. Blue: present-day climatic treatment, red: warm climatic treatment. Lines: sample size corrected standard ellipses (SEAc). Large points and errorbars: treatment mean and 95% CI. (b) Area of the SEAc for each treatment by age with bootstrapped 95% CIs. N = 96 and 79 juveniles in present-day and warm climate respectively, and N = 77 and 75 adults.

Figure 2 :

 2 Figure 2: Impact of climate on lizard diet(a) Lizards individual dietary breadth measured by Levins' dietary index (ranging between 1: completely specialized diet to 3: completely generalized diet). (b) Dietary contribution of each putative prey (see Table1). Blue: present-day climatic treatment, red: warm climatic treatment. N = 96 and 79 juveniles in present-day and warm climate respectively, and N = 77 and 75 adults.

Figure 3 :

 3 Figure 3: Path analysis of the impact of climate on lizard diet

Figure 4 :

 4 Figure 4: Link between dietary specialization and adult gut microbial community diversity and future survival

Figure S2B :

 S2B Figure S2B: Diagram of the global path analysis model and sub-models

  model could be made by combining the paths from the best model of set D (minus link 10, AIC = 46.02) and the best model of set A (minus link 1, AIC = 56.86). The AIC difference between the best model (minus link 10) and this new model (minus links 10+1) was >10 points (AIC = 56.06).

Figure S3A :

 S3A Figure S3A: Impact of variation on the Δ13C TEF on the proportion of each of the 3 prey sources eaten by lizards from warm (in red) and present-day (blue) climates (mean values ± SEM).Δ15 N is fixed at 0.7 ‰ and Δ13 C varies by +1 and -1 from 1.2 ‰ (value from Lattanzio and Miles, dashed line). Triangles are predatory invertebrates, filled circles are phytophagous invertebrates, and diamonds are detritivorous invertebrates.

Figure S3B :

 S3B Figure S3B: Impact of variation on the Δ 15 N TEF on the proportion of each of the 3 prey sources eaten by lizards from warm (in red) and present-day (blue) climates (mean values ± SEM).

Δ 13 C

 13 is fixed at 1.2 ‰ and Δ 15 N varies by +1 and -1 from 0.7 ‰ (value from Lattanzio and Miles, dashed line). Triangles are predatory invertebrates, filled circles are phytophagous invertebrates, and diamonds are detritivorous invertebrates.

Figure S3C :

 S3C Figure S3C: Impact of variation on the Δ 13 C TEF on Levins' dietary index of lizards from warm (in red) and present-day (blue) climates (mean values ± SEM).Δ15 N is fixed at 0.7 ‰ and Δ 13 C varies by +1 and -1 from 1.2 ‰ (value from Lattanzio and Miles, dashed line).

Figure S3D :

 S3D Figure S3D: Impact of variation on the Δ 15 N TEF on Levins dietary index of lizards from warm (in red) and present-day (blue) climates (mean values ± SEM).Δ15 N is fixed at 0.7 ‰ and Δ 13 C varies by +1 and -1 from 1.2 ‰ (value from Lattanzio and Miles, dashed line).

Table

  , Fig 2b). Prey consumption varied strongly with individual age, with juveniles overall consuming more phytophagous invertebrates and fewer predatory invertebrates than adults.

Table 1 : Impact of climatic treatment on lizard corrected stable isotope values, diet and dietary specialization

 1 Model averaged values using linear mixed models. The global model included climatic treatment and its two-way interactions with age class and sex as fixed effects and random mesocosm identity. R²m are20, 21, 13, 22 and 21 % and R²c are 37, 51, 31, 29 and 34 % for global models of δ13 Ccor, δ15 Ncor, prop. predators, prop. phytophagous and diet breadth respectively. N = 327.

	Variable	Parameter	Estimate SE z-value p-value	RI
	δ 13 Ccor	Intercept	0.46	0.04 11.48	<0.001*** -
		Age	-0.13	0.02 6.62	<0.001*** 1.00
		Climate	0.12	0.06 2.24	0.025*	1.00
		Sex	0.02	0.02 0.95	0.344	0.29
		Age:Climate	0.01	0.04 0.40	0.688	0.20
	δ 15 Ncor	Intercept	2.38	0.21 11.32	<0.001*** -
		Age	0.39	0.06 6.29	<0.001*** 1.00
		Sex	0.12	0.07 1.70	0.088.	1.00
		Climate	0.48	0.27 1.80	0.072.	0.78
		Sex:Climate	0.14	0.12 1.19	0.234	0.27
		Age:Climate	0.04	0.12 0.31	0.754	0.14
	prop. predatory inv.	Intercept	0.43	0.02 19.43	<0.001*** -
		Age	0.03	0.01 2.90	0.004**	1.00
		Sex	0.01	0.01 1.27	0.203	0.83
		Climate	0.06	0.03 2.00	0.046*	0.86
		Sex:Climate	0.02	0.02 1.14	0.253	0.21
		Age:Climate	-0.01	0.02 0.81	0.420	0.15
	prop. phytophagous inv. Intercept	0.31	0.01 30.5	<0.001*** -
		Age	-0.05	0.01 6.72	<0.001*** 1.00
		Sex	-0.01	0.01 1.06	0.290	0.72
		Climate	-0.04	0.01 2.67	0.008**	1.00
		Sex:Climate	-0.01	0.01 1.07	0.283	0.22
		Age:Climate	-0.01	0.01 0.51	0.609	0.14
	Dietary breadth	Intercept	17.08	0.63 26.98	<0.001*** -
		Age	-1.89	0.38 4.93	<0.001*** 1.00
		Sex	-0.79	0.34 2.31	0.021*	1.00
		Climate	-2.47	0.87 2.83	0.005**	1.00
		Age:Climate	0.66	0.63 1.05	0.294	0.31
		Sex:Climate	-0.25	0.62 0.40	0.689	0.19
	A path analysis was used to disentangle direct effects of climate from climate-dependent
	changes in prey community on lizard diet, summarized with the first axis of a principal
	component analysis (Fig 3, Fig S2A). The best model included both a direct positive effect of

warmer climate on diet specialization (coef = 0.43, higher specialization) and, to a lower extent, indirect effects, either negative through climate-driven changes in predatory invertebrate abundance (coef = -0.46*0.22 = -0.10, lower specialization) or positive through changes in

Table

Table 2 : Implication of lizard diet on their body condition and future survival

 2

		Model averaged values with linear (body condition) and generalized (survival, binomial
		family) linear mixed models. Global models included two-way interaction between each dietary
		component and climate, and for juveniles, continuous birthdate, plus random mesocosm
		identity. Numeric variables were centred and scaled. The global models explained 24, 16, 12
		and 3 % of the marginal variance and 29, 16, 21 and 15 % of the conditional variance
		respectively for adult body condition, juvenile body condition, adult survival and juvenile
		survival. N = 152 adults, 175 juveniles.
	Variables	Age	Parameter	Estimate SE	z-value p-value	RI
	September Body condition
		Adults	Intercept	-0.21	0.07 3.22	0.001**
			Sex	0.54	0.08 6.57	<0.001*** 1.00
			PC1 diet: predator specialization -0.03	0.04 0.69	0.488	0.24
			PC2 diet: detri vs phyto	0.03	0.04 0.61	0.544	0.22
		Juveniles	Intercept	-0.06	0.03 2.21	0.027*
			PC1 diet: predator specialization 0.02	0.02 1.4	0.163	0.48
			PC2 diet: detri vs phyto	0.03	0.02 1.54	0.123	0.42
			Sex	0.14	0.03 4.67	<0.001*** 1.00
			Climate	-0.05	0.03 1.33	0.184	0.67
			Climate*PC2 diet	-0.07	0.03 2.33	0.020*	0.42
	Winter-Spring survival
		Adults	Intercept	0.11	0.33 0.32	0.748
			PC1 diet: predator specialization -0.44	0.21 2.03	0.042*	1.00
			Sex	0.88	0.38 2.3	0.021*	1.00
			Climate	0.34	0.53 0.63	0.526	0.23
			PC2 diet: detri vs phyto	0.10	0.20 0.49	0.622	0.21
		Juveniles	Intercept	-0.44	0.29 1.49	0.137
			PC1 diet: predator specialization 0.20	0.19 1.01	0.313	0.21
			Climate	-0.35	0.5	0.7	0.482	0.16
			Date of birth	0.07	0.16 0.45	0.649	0.14
			Sex	0.09	0.32 0.27	0.787	0.13

  , and descend from lizards captured in nature (capture licence nb. 2010-189-16 DREAL). The Station d'Ecologie Theorique et Experimentale has a national agreement for use of animals in the laboratory (number B09583), and our experiments are made in accordance with 2013 French ethics regulations (permits number APAFIS#15897-2018070615164391 v3 and APAFIS#19523-201902281559649 v3).

  June 2013, we allocated lizards to 10 enclosures, five attributed to a "present-day climate" treatment, and five to a "warm climate" treatment, on average 2°C warmer (weekly mean of Summer daily temperatures, PC: 26.3 ± 0.3 °C, WC: 28.3 ± 0.2 °C, mean ± SE, F1,147 = 13, p <0.001; weekly mean of Summer maximum daily temperatures: PC: 29.1 ± 0.3 °C, WC: 32.4 ± 0.4 °C, F1,147 = 35, p <0.001), coherent with climate change projections for southern Europe (

Table S1A : Impact of climatic conditions on stable isotope values per invertebrate functional group

 S1A Results from mixed effect models with climatic treatment as a fixed effect and mesocosm as a random intercept. The table presents mean ± SE for each climatic condition. Significant effects are in bold.

			Detritivorous			Phytophagous			Predatory
	parameter present warm	χ2	p-	present	warm	χ2	p-	present warm	χ2	p-
					value				value				value
	δ 13 C	-26.75	-25.84	11.8 6e-4	-29.47	-28.8 ±	7.1	0.008 -28.26	-27.96	0.93 0.33
		± 0.17	± 0.20			± 0.17	0.17			± 0.15	± 0.27
	δ 15 N	5.30 ±	4.64 ±	2.6	0.11	6.64 ±	6.20 ±	0.9	0.33	8.58 ±	8.45 ±	0.08 0.78
		0.30	0.28			0.18	0.17			0.23	0.20

Table S1B : Mean and SD stable isotope values per invertebrate functional group and mesocosm

 S1B The detritivorous group is composed of the 3 locally dominant families: Isopodae, Julidae and Lombricidae, representing 82% of the total detritivorous invertebrate abundance. The phytophagous group is composed of Cercopidae, Crysomelidae, Delphacidae, Formicidae, Tipulidae, Gryllidae, Arionidae, (69% of the phytophagous invertebrate abundance). The predator group is composed of spiders (Araeinidae, Clubionidae, Lycosidae, Salticidae, Tetragnathidae, Theridiidae, Thomisidae), Carabidae, Nabidae and Staphilinidae (86 % of the predatory invertebrate abundance).

	Group	Mesocosm Climate	Mean δ 15 N SD δ 15 N	Mean δ 13 C SD δ 13 C
	detritivorous 26	present-day	4.50	0.77	-26.82	0.79
	detritivorous 28	present-day	5.75	1.62	-26.76	0.98
	detritivorous 33	present-day	5.50	0.42	-27.04	0.46
	detritivorous 41	present-day	6.05	2.18	-26.66	0.94
	detritivorous 45	present-day	4.17	2.33	-26.36	1.71
	detritivorous 25	warm	4.82	1.13	-26.31	0.98
	detritivorous 29	warm	4.88	1.96	-26.42	0.57
	detritivorous 32	warm	4.80	1.30	-25.60	1.44
	detritivorous 38	warm	4.93	2.20	-25.43	0.56
	detritivorous 46	warm	3.86	1.77	-25.70	1.47
	phytophagous 26	present-day	5.97	1.06	-29.09	1.21
	phytophagous 28	present-day	7.20	1.04	-29.44	1.05
	phytophagous 33	present-day	7.35	2.11	-29.90	1.37
	phytophagous 41	present-day	6.64	0.61	-29.54	0.93
	phytophagous 45	present-day	6.41	0.80	-29.66	1.65
	phytophagous 25	warm	4.79	1.02	-28.60	1.18
	phytophagous 29	warm	6.03	0.83	-28.77	1.43
	phytophagous 32	warm	7.78	0.93	-28.73	2.09
	phytophagous 38	warm	6.16	0.93	-28.85	0.84
	phytophagous 46	warm	6.11	1.04	-29.02	1.10
	predatory	26	present-day	8.19	1.69	-28.12	0.96
	predatory	28	present-day	10.03	0.93	-27.86	0.85
	predatory	33	present-day	7.38	0.88	-28.60	0.76
	predatory	41	present-day	9.21	1.04	-28.55	0.73
	predatory	45	present-day	7.67	1.50	-27.93	2.15
	predatory	25	warm	7.28	0.90	-27.08	3.03
	predatory	29	warm	7.41	0.63	-28.33	0.54
	predatory	32	warm	10.19	0.82	-28.38	0.63
	predatory	38	warm	8.03	0.76	-27.78	0.51
	predatory	46	warm	8.56	0.76	-27.93	2.66

Table S2A : C-test statistic, p-value and AIC of the path sub-models

 S2A The table ranks the global model and all of the sub-models tested (see FigS1B) by their AIC. The best model includes all links but the 10 th link, that is the effect of the abundance of detritivorous invertebrates on the diet. Its p-value is > 0.05, which means that it fits well the data.

	Set	Links missing from the path Ctest	df	p-value	AIC
	D	10	10.02	10	0.439	46.02
	Global model	None	8.82	8	0.358	46.82
	D	8	13.62	10	0.191	49.62
	D+A	10+1	22.06	12	0.0368	56.06
	A	1	20.86	10	0.0221	56.86
	D	8+10	24.69	12	0.0164	58.69
	E	11	23.81	10	0.00813	59.81
	D	9	32.26	10	3.62e-4	68.26
	C	7	37.58	10	4.5e-5	73.58
	D	9+10	39.88	12	7.52e-5	73.88
	D	8+9+10	42.11	14	1.19e-4	74.11
	D	8+9	40.75	12	5.39e-5	74.75
	B	5	46.29	10	1.27e-6	82.29
	B	4	88.29	10	1.17e-14	124.29
	B	4+5	125.76	12	0	159.76
	A	3	135.81	10	0	171.81
	B	6	204.67	10	0	240.67
	A	1+3	235.94	12	0	269.94
	B	5+6	242.14	12	0	276.14
	B	4+6	284.14	12	0	318.14
	B	4+5+6	321.61	14	0	353.61
	A	2	394.49	10	0	430.49
	A	1+2	406.53	12	0	440.53
	A	2+3	521.47	12	0	555.47
	A	1+2+3	707.54	14	0	739.54

Table S3A : Impact of variation in the Δ 13 C TEF on the difference between climatic conditions in the proportion of predatory and phytophagous prey eaten, as well as the Levins' index.

 S3A 15 N is fixed at 0.7 ‰ and Δ13 C varies by +1 and -1 from the reference value of 1.2 ‰ in 0.1 ‰ steps. For each value of Δ13 C, we apply a linear mixed model of the dependent variable as a function of climatic conditions, age, sex and random mesocosm identity. We report χ 2 and pvalues for the climatic effect. Significant effects are in bold.

	Δ 13 C TEF Predatory inv.	Phytophagous inv. Levins' index
		χ2	p-value χ2	p-value χ2	p-value
	0.2	0.03	0.87	0.03	0.86	3.04	0.081
	0.3	0.01	0.92	0.07	0.78	4.23	0.04
	0.4	0	0.99	0.15	0.69	6.06	0.014
	0.5	0.01	0.92	0.26	0.61	7.44	0.0064
	0.6	0.05	0.82	0.51	0.48	8.06	0.0045
	0.7	0.15	0.70	0.81	0.37	7.14	0.0075
	0.8	0.34	0.56	1.33	0.25	6.48	0.011
	0.9	0.69	0.41	2.26	0.13	5.87	0.015
	1.0	1.31	0.25	3.58	0.058	5.83	0.016
	1.1	2.22	0.14	5.06	0.024	6.01	0.014
	1.2* ref	3.57	0.059	7.07	0.0079	6.65	0.0099
	1.3	5.35	0.021	9.23	0.0024	7.75	0.0054
	1.4	7.63	0.0057	11.27	7.9e-4	9.51	0.002
	1.5	10.41 0.0013	13.09	3e-4	11.59	6.6e-4
	1.6	13.2	2.8e-4	13.6	2.3e-4	14.39	1.5e-4
	1.7	15.86 6.8e-5	14.45	1.4e-4	16.51	4.8e-5
	1.8	18.03 2.2e-5	14	1.8e-4	19	1.3e-5
	1.9	19.94 8e-6	13.18	2.8e-4	20.72	5.3e-6
	2.0	21.13 4.3e-6	12.81	3.4e-4	21.44	3.6e-6
	2.1	21.92 2.8e-6	11.77	6e-4	21.6	3.4e-6
	2.2	22.15 2.5e-6	10.78	0.001	21.52	3.5e-6

Δ

Table S3B : Impact of variation in the Δ 15 N TEF on the statistical significance of the difference between climatic conditions in the proportion of predatory and phytophagous prey eaten, as well as the Levins' index.

 S3B 13 C is fixed at 1.2 ‰ and Δ15 N varies by +1 and -1 from the reference value of 0.7 ‰ in 0.1 ‰ steps. For each value of Δ 15 N, we apply a linear mixed model of the dependent variable as a function of climatic conditions, age, sex and random mesocosm identity. We report χ2 and p-values for the climatic effect. Significant effects are in bold.

	Δ 15 N TEF Predatory inv.	Phytophagous inv. Levins' index
		χ2	p-value χ2	p-value χ2	p-value
	-0.3	0.57	0.45	2.82	0.093	2.64	0.1
	-0.2	0.67	0.41	3.11	0.078	2.96	0.086
	-0.1	0.83	0.36	3.43	0.064	3.29	0.07
	0	0.97	0.32	3.8	0.051	3.66	0.056
	0.1	1.18	0.28	4.37	0.037	4.04	0.044
	0.2	1.43	0.23	4.94	0.026	4.37	0.036
	0.3	1.74	0.19	5.59	0.018	4.82	0.028
	0.4	2.1	0.15	6.66	0.0099	5.27	0.022
	0.5	2.55	0.11	7.21	0.0072	5.68	0.017
	0.6	3.08	0.079	7.76	0.0053	6.3	0.012
	0.7* ref	3.57	0.059	7.07	0.0079	6.65	0.0099
	0.8	4.10	0.043	5.71	0.017	7.2	0.0073
	0.9	4.68	0.031	4.13	0.042	7.85	0.0051
	1	5.01	0.025	2.55	0.11	8.12	0.0044
	1.1	5.31	0.021	1.46	0.23	8.14	0.0043
	1.2	5.45	0.02	0.73	0.39	7.41	0.0065
	1.3	5.55	0.018	0.35	0.55	6	0.014
	1.4	5.43	0.02	0.14	0.7	3.5	0.061
	1.5	5.24	0.022	0.03	0.86	0.72	0.40
	1.6	4.91	0.027	0	1	0	0.97
	1.7	4.44	0.035	0.02	0.88	0.4	0.53

Δ

Table S3C : Impact of variation in the Δ 13 C TEF between warm and present-day climatic conditions on the statistical significance of the difference between climatic conditions in the proportion of predatory and phytophagous prey eaten, as well as the Levins' index.

 S3C 15 N is fixed at 0.7 ‰ and Δ13 C is fixed at the reference value of 1.2 ‰ in present-day climate, but is allowed to vary between 1.2 + 0 and 1.2 + 0.6 ‰ in warm climates. For each value of Δ15 N, we apply a linear mixed model of the dependent variable as a function of climatic conditions, age, sex and random mesocosm identity. We report χ2 and p-values for the climatic effect. Significant effects are in bold.

		Predatory inv.	Phytophagous inv. Levins' index
	Δ 13 C TEF χ2	p-value χ2	p-value	χ2	p-value
	+0* ref	3.57	0.059	7.07	0.0079	6.65	0.0099
	+0.1	5.22	0.022	6.13	0.013	7.69	0.0056
	+0.2	7.17	0.0074 4.74	0.03	9.57	0.002
	+0.3	9.24	0.0024 3.67	0.055	12.03	5.2e-4
	+0.4	11.25 7.9e-4	2.4	0.12	15.37	8.8e-5
	+0.5	12.86 3.4e-4	1.55	0.21	18.47	1.7e-5
	+0.6	14.2	1.6e-4	0.79	0.37	22.28	2.4e-6

Δ

  N, we apply a linear mixed model of the dependent variable as a function of climatic conditions, age, sex and random mesocosm identity. We report χ2 and p-values for the climatic effect. Significant effects are in bold.

		Predatory inv. Phytophagous inv. Levins' index
	Δ 15 N TEF χ2	p-value χ2	p-value	χ2	p-value
	-0* ref	3.57 0.059	7.07	0.0079	6.65	0.0099
	-0.1	4.50 0.034	11.24 8e-4	8.89	0.0029
	-0.2	5.21 0.022	16.61 4.6e-5	11.02	9e-4
	-0.3	5.61 0.018	23.44 1.3e-6	13.16	2.9e-4
	-0.4	5.87 0.015	32.1	1.5e-8	15.09	1e-4
	-0.5	5.97 0.015	42.77 6.2e-11	16.97	3.8e-5
	-0.6	5.88 0.015	54.84 1.3e-13	18.84	1.4e-5

Acknowledgements:

We thank Olivier Calvez, Olivier Guillaume, Antoine Cave, Bastien Rémurier, Laure Geidel and Alice Fournier for fieldwork assistance and Richard Inger for insightful statistical comments.

Ethics:

The lizards used in this study are part of a wider study on the consequences of climate change on populations, and descend from lizards captured in the field (capture licence nb. 2010-189-16 DREAL). The Station d'Ecologie Theorique et Experimentale has a national agreement for use of animals in the laboratory (number B09583), and our experiments are made in accordance with 2013 French ethics regulations (permits number APAFIS#15897-2018070615164391 v3 and APAFIS#19523-201902281559649 v3).

Data accessibility: data is available on zenodo at dx.doi.org/10.5281/zenodo.3475402. Data should be cited as: Bestion, E, Soriano-Redondo, A, Cucherousset, J, Jacob, S, White, J, Zinger, L, Fourtune, L, Di Gesu, L, Teyssier, A, Cote, J (2019). Raw data for: "Altered trophic interactions in warming climates: consequences for predator diet breadth and fitness", Bestion et al 2019 Proceedings B. (Version 1). http://doi.org/10.5281/zenodo.3475402.

Author contributions: EB, JCo and JCu conceived the study and designed the experiment. EB, LDG, AT, and JCo ran the experiment and collected the data. SJ, JW, LDG and LZ extracted and analysed the bacterial data. EB analysed the data with the help of ASR, LF, JCu and JCo. EB led the writing of the manuscript and JC, ASR, JCu, JW, LZ and SJ contributed substantially to the writing of the manuscript.

Competing interests:

We declare we have no competing interests. The first axis of the PCA represents 57 % of the variance, and is mainly linked to the proportion of predatory invertebrates in the diet (+0.52 loading), the Levins' dietary index (-0.49 loading), and the corrected δ 15 N values (+0.49), while the proportion of phytophagous (-0.27), detritivorous invertebrates (-0.39) and the δ 13 C values (0.17) have less importance. This first principal component is hereafter named predatory specialization. The second axis of the PCA represents 28 % of the variance and is mainly linked to the proportion of phytophagous invertebrates (-0.63), of detritivorous invertebrates (+0.46) and the δ 13 C values (-0.62), while the proportion of predatory invertebrate (0.05) and the δ 15 N values (0.09) are less represented. This axis will be referred to as the green-brown diet axis.

Supplementary material for

Altered trophic interactions in warming climates: consequences for predator diet breadth and fitness

Supplementary section S4: Link between lizards' diet and their gut microbial communities Table S4A: Link between lizard diet and their gut microbial community diversity

Analyses of the effect of diet on adult lizard microbial community diversity (measured by Shannon index) using a linear mixed model with a model averaging approach. The global model included the interaction between each of the two dietary axes and climatic conditions, sex, sample sequencing depth plus mesocosm identity as a random effect. All numeric variables were centred and scaled.


domain: chim phys

text:
A Gibaud

J Villanova

O Cherkas

A Bulou

L Kamtcheu Ouanssi

A Mcheik

S Cassaignon

P J Lopez

S Berthier

Analysis of diatoms by holotomography

3D X-ray tomography was used to unravel the inner and outer morphology of a centric diatom namely the Coscinodiscus sp. We show how holotomography carried out with a 40 nm voxel size can provide detailed information about the sizes of the different parts of the diatom frustule. We have in particular analyzed quantitatively the pore size in the cribrum and cribellum parts of the diatom together with an estimation of the wall size. We evidence that in center of the diatom, walls are forming a hexagonal arrangement that is containing some pentagons to promote paving the space in 3D. Fig. 5. Distribution of the diameters of holes in the cribellum.

Introduction

Diatoms are among the most fascinating organisms found in nature [START_REF] Round | Diatoms : Biology and Morphology of the Genera[END_REF]. These unicellular photosynthetic protists that belong to the stramenopiles are found in a large number of freshwater or marine environments and live inside an intricately silica shell. A rough estimate suggests from 50,000 to 200,000 species, making them among the most species-rich lineages of eukaryotes. They have several important ecological roles, contributing to various biogeochemical cycles with estimates between a fifth and a quarter of all photosynthesis on our planet [START_REF] Sims | Evolution of the diatoms: insights from fossil, biological and molecular data[END_REF]. By fixing carbon or converting it from carbon dioxide into sugar, diatoms also reduce the amount of carbon dioxide in the atmosphere just as terrestrial plants [START_REF] Sims | Evolution of the diatoms: insights from fossil, biological and molecular data[END_REF][START_REF] Finkel | Silica use through time: Macroevolutionary change in the morphology of the diatom fustule[END_REF]. Diatoms are also a key source of food and energy for other organisms in many ecosystems so that many animals depend on diatoms either directly or indirectly for their growth. Diatoms are the principal marine organisms involved in the cycle of silicon, which constitutes about one-quarter of the Earth's crust.

As mention above, diatoms are capable of synthetizing a transparent cell walls made of silicon dioxide hydrated with a small amount of water (SiO 2 + H 2 O). As silica is the main component of glass, they are often called "algae in glass houses". The cell wall or thecae which is named frustule consists of two overlapping parts known as valves. Since silica is impervious, diatoms have evolved elaborate patterns of perforations in their valves to allow nutrient exchange with the environment, and motility in some species. The proposed evolutionary functions for these intricate shell designs include nutrient acquisition, control of diatom sinking rate, control of turbulent flow around the cell, and protection from grazing and viral attack [START_REF] Bailleul | Energetic coupling between plastids and mitochondria drives CO 2 assimilation in diatoms[END_REF]. These patterns have also an unprecedentedly high specific strength, exceeding that of all other reported natural biomaterials, which we attribute to the combination of the honeycomb sandwich plate architecture and extremely low flaw density in the constituent biosilica [START_REF] Aitken | Microstructure provides insights into evolutionary design and resilience of Coscinodiscus sp. Frustule[END_REF]. The ornamentation pattern of the valve, which are very aesthetic, are use for classifying diatoms. Three different classes were proposed by Round et al. [START_REF] Round | Diatoms : Biology and Morphology of the Genera[END_REF]: the Coscinodiscophyceae, are centric diatoms with frustule that present a radial symmetry, Fragilariophyceae are pennate diatoms with bilateral symmetry but lacking a raphe, and Bacillariophyceae, pennate diatoms with a raphe [10,[START_REF] Medlin | The evolution of the diatoms (Bacillariophyta). I. Origin of the group and assessment of themonophyly of its major divisions[END_REF].

Here we have focused our attention to a specific centric gender, the Coscinodiscus. Our major interest was to image in 3D this diatom in order to get a full description of its 3D architecture. This was achieved by using 3D-Holotomography at the ID16-B beamline of ESRF. With this technique we have investigated the frustule topography of Coscinodiscus sp. With the 3D array of this object we have determined many morphologic properties of the diatom such as the pores size, the domain walls and the shape of the outer and inner frustule membranes. With a better understanding of the diatom frustule structure from the nanometer scale up to whole cell we can foresee that we will have a powerful tool to unravel some key physical properties of porous biosilica membranes and thus anticipate potential technological https://doi.org/10.1016/j.surfin. E-mail address: gibaud@univ-lemans.fr (A. Gibaud). applications. Comparison with other imaging technique is provided.

Experimental

Coscinodiscus sp. (referenced CCMP 584) come from the National Center of Marine Algae and Microbiota located in Maine-USA. Coscinodiscus sp. is maintained in laboratory seawater environment as described in Vartanian et al. [START_REF] Vartanian | Plasticity and robustness of pattern formation in the model diatom[END_REF]. The medium is sterilized by autoclave (120 °C, 25 min) and then completed at cold by the addition of orthosilicic acid (C final = 175 μmol L -1 ), hydrogen phosphate dipotassium (C final = 0.3 mmol L -1 ) as well as a mixture of vitamins (biotin at 50 μg L -1 , vitamin B12 at 50 μg L -1 and thiamine at 0.1 μg L -1 ). Coscinodiscus sp. culture is maintained for two weeks at 18 °C in polycarbonate flasks in an incubator with a constant day-night cycle (12-12 h) and a luminous intensity equivalent to 80 μEm -2 s -1 during the day. The frustules of Coscinodiscus sp. are purified in order to remove organic matter to finally obtain the isolated inorganic frustules. The chemical purification protocol is based on 10 mL of Coscinodiscus sp. solution. Cells are washed 3 times with distilled water, filtered and are then dispersed in a mixture of 5 mL of sulfuric acid (96%) and 1 mL of nitric acid (80%). After 30 min of treatment, the pellet with silica is washed 5 times with filtered distilled water. The acid treatment separates the different parts of the frustule, the two valves and their girdle bands. Coscinodiscus sp. frustules are then suspended in a mix solution of ethanol:water with a ratio [1:4]. By a micropipette, 200 µL of solution are then spread on a microscope slide. Coscinodiscus sp. valves are mounted on a cylindrical micrometer silica tip for X-ray tomography analysis. This step was performed using a micromanipulator consisting of an optical microscope, a camera and a micromanipulator plate (xyz).

The 3D volumes have been acquired using X-ray nano-tomography [START_REF] Cloetens | Holotomography: quantitative phase tomography with micrometer resolution using hard synchrotron radiation X rays[END_REF] at the nano-analysis endstation ID16B at the ESRF having a focused beam of 50 × 50 nm 2 [START_REF] Martinez-Criado | ID16B: a hard X-ray nanoprobe beamline at the ESRF for nano-analysis[END_REF]. Phase contrast imaging was performed using this focused beam as secondary source producing a conic and monochromatic beam with an energy of 17.5 keV and a high flux of 6.10 11 ph s -1 . Thanks to the geometry, the magnification i.e. pixel size and field of view depends of the sample position between the secondary source and the detector, in this experiment, pixel size varied from 10 nm to 120 nm. For each tomography, about 2560 projections, were recorded on a PCO edge camera (2560 × 2160 pixels) along a 360°r otation with an exposure time of 100 or 200 ms per step, depending of the sample. 3D reconstructions were achieved in two steps: (i) phase retrieval calculation using an inhouse developed octave script and (ii) filtered backprojection reconstruction using ESRF software PyHST2 [START_REF] Mirone | The PyHST2 hybrid distributed code for high speed tomographic reconstruction with iterative reconstruction and a priori knowledge capabilities[END_REF].

Results and discussion

A typical 3D Holotomography image of the frustule is shown in Fig. 1. With the 3D image of the diatom one can immediately appreciate the magnificence of this centric diatom. The inner layer exhibits a honeycomb-like structure called areolae in which large holes known as foramen are observed. The full size of the diatom is 75 µm and its thickness varies in the range 1.35-1.5 µm. The size of each foramen varies from one to one another. As a result, the foramen pattern does not exhibit a perfect honeycomb structure.

An evaluation of the foramen radius was made after thresholding the axial section of the diatom (see Fig. 2a andb). All the analysis of the pore size distribution was made with the FIJI software [START_REF] Schindelin | Fiji: an open-source platform for biological-image analysis[END_REF]. It was found that the distribution of foramen radii was mainly bimodal with a main mode located at R 1 = 0.68 ± 0.06 µm and a minor one located at R 2 = 0.57 ± 0.12 µm (see Fig. 2c). The analysis was carried out over 871 holes thus providing a reasonable statistic.

When moving from the inside of the diatom to the outside, one then find the cribrum which is the central part of the diatom. As shown in Fig. 3 the cribrum is made of an array of ill formed hexagons. It can be seen that the organization of hexagons can vary significantly from one place to one another. For instance, in the left part of Fig. 3 one can see that the array forms a well ordered 2D hexagonal structure with a nice pentagonal defect located in the top part. The presence of such a defect is not fortuitous as such defects are necessary to pave the space in 3D. On the right part of the figure, a neighboring area exhibits a much more disordered structure in which hexagons are irregular and with a bigger number of pentagons. Every hexagon is made of biosilica walls separating the cavities located between the inner part of the frustule and the cribellum.

In order to understand the shape of the cribellum it is necessary to zoom at high resolution the 3D image of the diatom. This is shown in Fig. 4.

The top part of Fig. 4 shows a small part of the inner frustule on the left panel and the cribellum on the right panel. Below we have selected a few images taken as top views at different altitudes in the frustule. One can clearly see on these images the richness of the structure with big foramens followed by biosilica walls and finishing with very small pores located in the cribellum. The analysis of the 20 foramens in the image (without taking in account the ones at the edges gives an average radius of 0.63 µm. This value is in reasonable agreement with the one (0.68 µm) found on a much larger series of Fig. 2. The biosilica walls have a width of about 200 nm in the middle of each segment. Their width slightly increases when one moves towards a node. The small holes seen in the cribellum do not really exhibit a 2D hexagonal ordering except locally. Their diameter is of the order of about 125 ± 20 nm (see Fig. 5).

With a voxel size of 40 nm, it is clear that it was nevertheless impossible to identify any features below this value. This is why we could not resolve the hierarchical structure contained in the cribellum. In particular very small pores (45 ± 9 nm) as evidenced by Losic et al [START_REF] Losic | Atomic force microscopy (AFM°characterization of the silica nanostructure of two centric diatoms[END_REF] by Atomic force microscopy in high resolution mode were not identified. Our results are on the other hand perfectly in line with ones found by FIB-SEM analysis of the same specie [START_REF] Xing | Characterization and analysis of Coscinodiscus genus frustule based on FIB-SEM[END_REF] with the great advantage that X-ray tomography is non destructive compared to FIB-SEM.

So far the main limitation of the X-ray holotomography compared to TEM or AFM is a coarser resolution. Indeed it is difficult to image materials with a resolution better than 30 nm with X-ray holotomography while SEM (1-20 nm), TEM (0.1 nm) and AFM (1 nm) lateral) can go down to much higher resolution [START_REF] Giessibl | AFM's path to atomic resolution[END_REF]. Yet with the advance of Extremely Bright Sources (as what will be available after the E.S.R.F. upgrade) one should achieve a better resolution (<10 nm) in the near future. The main advantages of holotomography over these techniques is that it does not require the sample to be under vacuum as is the case for SEM. and TEM and it allows the collection of a 3D image. The 3D image is of crucial interest for having an overview of the inner and outer part of a material. Note that a 3D image is also the only way to observe the inner morphology of a material which is not feasible using SEM or TEM. This also provides the possibility to extract the mechanical properties of such tiny materials as the 3D array can be processed using finite elements analysis.

Conclusion

In this paper we have shown that 3D holotomography is a useful technique to image in 3D the magnificent structure of diatoms. In particular, one can determine by this technique the pore size distribution of the areola and cribellum and evidence the arrangement of the silica walls (cribrum) inside the frustule. As the typical voxel size that we could achieve was 40 nm, it was impossible to probe the very fine structure that was previously observed in the cribellum by high resolution AFM [START_REF] Losic | Atomic force microscopy (AFM°characterization of the silica nanostructure of two centric diatoms[END_REF]. In this respect holotomography provides similar information as the one obtained by FIB-SEM [START_REF] Xing | Characterization and analysis of Coscinodiscus genus frustule based on FIB-SEM[END_REF]. This first study of diatoms by this technique is of great interest to foster further studies of these materials by finite elements thus providing useful information about their mechanical properties.

  2019.100358 Received 1 April 2019; Received in revised form 12 July 2019; Accepted 21 July 2019 ⁎ Corresponding author at: IMMM, UMR 6283 CNRS, Avenue Oliver Messiaen, 72085 Le Mans, Cedex 9, France.

Fig. 1 .

 1 Fig. 1. A representation of the diatom frustule showing the nice architecture made of a large number of foramens. Scale bar = 10 µm. The size of this image was corresponding to a pixel size of 160 nm after reduction of the initial 3D matrix by a 3D factor of 64.

Fig. 2 .

 2 Fig. 2. Cross section of the diatom before and after binarisation of the image. The bottom panel shows the distribution of the foramens radii found in the frustule. Scale bar=10 µm and voxel size 160 nm.

Fig. 3 .

 3 Fig. 3. Magnified view of the areolae of the frustule showing the presence of biosilica walls with either a nearly perfect 2D hexagonal structure or with a disordered one.

Fig. 4 .

 4 Fig. 4. Top part 3D representation of the areola and of the cribellum showing the large difference in size between the pores contained in both areas. All images are obtained with the original voxel size of 40 nm. The very small holes present in the cribellum can be very well identified. Scale bar 1.4 µm.

Acknowledgments

We are indebted to ESRF for providing access to the ID16B beamline. AM, PJL, SC and SB would like to thank for its financial support the French state funds managed by the ANR within the Investissements d'Avenir Programme (ANR-11-IDEX-0004-02), and more specifically within the framework of the Cluster of Excellence MATISSE led by Sorbonne Université. The work of PJL was cofunded by the Labex DRIIHM, French programme "Investissements d'Avenir" (ANR-11-LABX-0010) which is managed by the ANR.

Conflict of interest

None.