Tamara Gómez-Moracho

Tristan Durand

Cristian Pasquaretta

Philipp Heeb

Mathieu Lihoreau
email: mathieu.lihoreau@univ-tlse3.fr

Artificial diets modulate infection rates by Nosema ceranae in bumblebees

Keywords: Bombus terrestris, Nosema ceranae, nutrition, experimental infection, survival analyses, PCR

Parasites alter the physiology and behaviour of their hosts. In domestic honey bees, the microsporidia Nosema ceranae induces an energetic stress and impairs the behaviour of foragers, potentially leading to colony collapse. Whether this emerging parasite similarly affects wild pollinators is little understood because of the low success rates of experimental infection protocols. Here we established a new apporach for infecting bumblebees (Bombus terrestris) with controlled amounts of N. ceranae, by briefly exposing individual bumblebees to a sucrose solution containing parasite spores, before feeding them with artificial diets. We validated our protocol by testing the effect of two spore dosages and two diets varying in their protein to carbohydrate ratio, on the prevalence of the parasite (proportion of infected bees), the intensity of infection (spore count in the gut), and the survival of bumblebees.

Insects fed a low-protein high-carbohydrate diet showed highest parasite prevalence (up to 70%) but lived longest, suggesting that immunity and survival of bumblebees are maximised at different protein to carbohydrate ratios. Spore dosage had no effect on parasite infection rate and host survival. The identification of experimental conditions for successfully infecting bumblebees with N. ceranae in the lab will facilitate investigations of the sub-lethal effects of this parasite on the behaviour and cognition of wild pollinators.

Introduction

Bees face a high diversity of parasites and pathogens that negatively affect their metabolism [START_REF] Li | Chronic Nosema ceranae infection inflicts comprehensive and persistent immunosuppression and accelerated lipid loss in host Apis mellifera honey bees[END_REF][START_REF] Mayack | Energetic stress in the honeybee Apis mellifera from Nosema ceranae infection[END_REF], immune system [START_REF] Antúnez | Immune suppression in the honey bee (Apis mellifera) following infection by Nosema ceranae (Microsporidia)[END_REF][START_REF] Li | Spore load and immune response of honey bees naturally infected by Nosema ceranae[END_REF], behaviour and cognition [START_REF] Gómez-Moracho | Effects of parasites and pathogens on bee cognition[END_REF], altogether compromising the fitness of individuals and colonies (Goulson et al. 2015;[START_REF] Klein | Why bees are so vulnerable to environmental stressors[END_REF].

The microsporidia Nosema ceranae is one of the most prevalent parasites of honey bees worldwide and is thought to be a major cause of colony declines [START_REF] Martín-Hernández | Nosema ceranae in Apis mellifera : a 12 years postdetection perspective[END_REF]. N. ceranae invades the epithelial cells of the honey bee midgut where it replicates [START_REF] García-Palencia | Natural infection by Nosema ceranae causes similar lesions as in experimentally infected caged-workers honey bees (Apis mellifera)[END_REF][START_REF] Higes | Experimental infection of Apis mellifera honeybees with Nosema ceranae (Microsporidia)[END_REF]. At the physiological level, this parasite disrupts the carbohydrate [START_REF] Aliferis | Gas chromatography-mass spectrometry metabolite profiling of worker honey bee (Apis mellifera L.) hemolymph for the study of Nosema ceranae infection[END_REF][START_REF] Mayack | Energetic stress in the honeybee Apis mellifera from Nosema ceranae infection[END_REF] and lipid [START_REF] Li | Chronic Nosema ceranae infection inflicts comprehensive and persistent immunosuppression and accelerated lipid loss in host Apis mellifera honey bees[END_REF]) metabolism of the host, which ensures the availability of nutrients for its own replication. This causes an energetic stress on infected honey bees that consume more sucrose solution than non-infected conspecifics [START_REF] Alaux | Interactions between Nosema microspores and a neonicotinoid weaken honeybees (Apis mellifera)[END_REF][START_REF] Martín-Hernández | Comparison of the energetic stress associated with experimental Nosema ceranae and Nosema apis infection of honeybees (Apis mellifera)[END_REF]; but see [START_REF] Aufauvre | Parasite-insecticide interactions: a case study of Nosema ceranae and fipronil synergy on honeybee[END_REF]. N. ceranae also alters gene expression in the brain [START_REF] Holt | Chronic parasitization by Nosema microsporidia causes global expression changes in core nutritional, metabolic and behavioral pathways in honey bee workers (Apis mellifera)[END_REF], inhibits the apoptosis of epithelial cells [START_REF] Martín-Hernández | Microsporidia infection impacts the host cell's cycle and reduces host cell apoptosis[END_REF] and deregulates immune responses (Martín-Hernandez et al., 2018). At the behavioural level, infected honey bees start foraging earlier in life [START_REF] Goblirsch | Physiological and behavioral changes in honey bees (Apis mellifera) induced by Nosema ceranae infection[END_REF]Higes et al., 2009;[START_REF] Perry | Rapid behavioral maturation accelerates failure of stressed honey bee colonies[END_REF], exhibit more frequent but shorter foraging flights (Dosselli et al., 2016;Dussaubat et al., 2013;[START_REF] Kralj | Nosema sp. influences flight behavior of infected honey bee (Apis mellifera) foragers[END_REF], show reduced homing abilities [START_REF] Wolf | So near and yet so far: harmonic radar reveals reduced homing ability of Nosema infected honeybees[END_REF] and lower olfactory learning performances (Piiroinen and Goulson, 2016;[START_REF] Gage | Nosema ceranae parasitism impacts olfactory learning and memory and neurochemistry in honey bees (Apis mellifera)[END_REF]but see Charbonneau et al., 2016).

Over the past ten years, N. ceranae has been identified in an increasing number of wild bee species (bumblebees: [START_REF] Graystock | Emerging dangers: deadly effects of an emergent parasite in a new pollinator host[END_REF][START_REF] Li | Diversity of Nosema associated with bumblebees (Bombus spp.) from China[END_REF][START_REF] Plischuk | South American native bumblebees (Hymenoptera: Apidae) infected by Nosema ceranae (Microsporidia), an emerging pathogen of honeybees (Apis mellifera)[END_REF], stingless bees: [START_REF] Porrini | Nosema ceranae in south american native stingless bees and social wasp[END_REF])) as well as in some wasps [START_REF] Porrini | Nosema ceranae in south american native stingless bees and social wasp[END_REF] and butterflies [START_REF] Malysh | Natural infection of the beet webworm Loxostege sticticalis L. (Lepidoptera: Crambidae) with three Microsporidia and host switching in Nosema ceranae[END_REF]. In the field, horizontal transmission to wild pollinators may occur through contamination of flower pollen by infected honey bees. This possibility is particularly concerning since many of these wild pollinators are solitary or present simple social organisations [START_REF] Michener | The bees of the world[END_REF], and therefore lack complex social immunity behaviours that allow honey bees to collectively limit infection risks and combat parasites (Cremer et al., 2007).

The effects of N. ceranae on wild pollinators have been best investigated in bumblebees. Recent studies suggest that N. ceranae impairs the cognitive abilities of bumblebees, potentially reducing the foraging performances of entire colonies (Piiroinen et al., 2016;Piiroinen and Goulson, 2016). However, the diversity of experimental infections protocols used in these studies, and their relatively low success rates (i.e. from 0% in (Piiroinen et al., 2016) to 62% in [START_REF] Graystock | Emerging dangers: deadly effects of an emergent parasite in a new pollinator host[END_REF]), make it difficult to draw definitive conclusions and call for more robust standardised approaches. By contrast, 100% of infections are routinely reached in honey bee studies (Doublet et al., 2015;[START_REF] Roberts | Horizontal transmission of a parasite is influenced by infected host phenotype and density[END_REF].

The age of bumblebees, their level of starvation prior to exposure, and the amount of parasite spores to which they are exposed to, are all potentially important parameters that vary across current infection protocols. Highest infections levels were obtained by starving bumblebees of uncontrolled age for 8h before feeding them with 6500 spores (an empirically measured infection intensity in wild colonies) in 40% sucrose solution individually administered with a pipette [START_REF] Graystock | Emerging dangers: deadly effects of an emergent parasite in a new pollinator host[END_REF]. Bumblebees were then maintained in smalls groups of 10 individuals with ad libitum access to 40% sucrose solution. Under these conditions, 62% of the bumblebees showed spores in their gut, which considerably reduced their lifespan.

Exposure to higher spore dosages caused different results. [START_REF] Fürst | Disease associations between honeybees and bumblebees as a threat to wild pollinators[END_REF] starved 2-days old bumblebees for 1h before feeding them with 100K spores administered in a 10 μL drop of sucrose and maintained them individually with 50% sucrose and artificial pollen ad libitum. Here, 34% of the bumblebees developed an infection but no effect was observed on survival [START_REF] Fürst | Disease associations between honeybees and bumblebees as a threat to wild pollinators[END_REF]. Piiroinen and Goulson (2016) and Piiroinen et al., (2016) administered bumblebees of uncontrolled age 180K and 130K N. ceranae spores respectively with a pipette and maintained them in small groups of 10 with ad libitum access to 50% sucrose and pollen. In these experiments, where the bumblebees were provided high numbers of spores but starved for only 2h, 3% (Piiroinen and Goulson, 2016) or none (Piiroinen et al., 2016) of the individuals developed an infection.

Another potentially important parameter, so far unexplored, is the nutritional composition of diets provided to bumblebees after parasite exposure. Nutrition is as a key mediator of host-parasite interactions [START_REF] Ponton | Nutritional immunology: a multi-dimensional approach[END_REF] and should therefore be carefully controlled when developing standard infection procedures. Many insects increase their consumption of dietary protein in order to develop stronger immunological responses and combat parasites [START_REF] Ponton | Nutritional immunology: a multi-dimensional approach[END_REF][START_REF] Lee | Flexible diet choice offsets protein costs of pathogen resistance in a caterpillar[END_REF][START_REF] Povey | Dynamics of macronutrient self-medication and illness-induced anorexia in virally infected insects[END_REF]. Increasing evidence indicate that bees given a choice of foods can carefully adjust their intake of nutrients to reach target levels maximizing fitness traits (e.g. [START_REF] Vaudo | Macronutrient ratios in pollen shape bumble bee (Bombus impatiens) foraging strategies and floral preferences[END_REF][START_REF] Kraus | Bumblebees adjust protein and lipid collection rules to the presence of brood[END_REF][START_REF] Addin Ruedenauer | Best be(e) on low fat: linking nutrient perception, regulation and fitness[END_REF]. Although there is no direct demonstration that diet modifies the ability of bees to fight infections, bumblebees fed a low-protein diet have a reduced immune response [START_REF] Brunner | Protein-poor diet reduces host-specific immune gene expression in Bombus terrestris[END_REF]. Honey bees infected by Nosema apis [START_REF] Rinderer | Worker honey bee response to infection with Nosema apis: Influence of diet[END_REF] and N. ceranae [START_REF] Jack | Effects of pollen dilution on infection of Nosema ceranae in honey bees[END_REF][START_REF] Porrini | Nosema ceranae development in Apis mellifera : influence of diet and infective inoculum[END_REF][START_REF] Tritschler | Protein nutrition governs within host race of honey bee pathogens[END_REF] survive longer when provided protein rich pollen. Since protein consumption is needed for synthesising peptides in immune pathways [START_REF] Lee | Flexible diet choice offsets protein costs of pathogen resistance in a caterpillar[END_REF][START_REF] Mason | Reduced consumption of proteinrich foods follows immune challenge in a polyphagous caterpillar[END_REF][START_REF] Povey | Dynamics of macronutrient self-medication and illness-induced anorexia in virally infected insects[END_REF], these results suggest that bees can adjust their nutrient intake for self-medication [START_REF] Poissonnier | A theoretical exploration of dietary collective medication in social insects[END_REF].

Here we developed an experimental protocol to efficiently infect bumblebees with N. ceranae by briefly exposing individuals to controlled amounts of parasite spores and feeding them with artificial diets varying in their protein to carbohydrate ratios.

We calibrated our approach by testing two spore dosages and two diets. We analysed parasite prevalence (proportion of infected bumblebees based on polymerase chain reactions, PCR), parasite intensity (spore counts in the gut) and host survival to identify best conditions for infecting bumblebees at sub-lethal doses.

Materials and Methods

Bees

Experiments were conducted in December 2017. Bumblebee workers (Bombus terrestris) of unknown age were obtained from two commercial colonies (Biobest, Belgium). Prior to the experiments, 15 workers from each colony were sampled for parasite screening [START_REF] Graystock | Emerging dangers: deadly effects of an emergent parasite in a new pollinator host[END_REF]. The absence of N. ceranae and other common parasites of bumblebees (N. bombi and Crithidia bombi) in these samples was confirmed in a monoplex PCR with the primers 218MITOC (N. ceranae: [START_REF] Martín-Hernández | Outcome of colonization of Apis mellifera by Nosema ceranae[END_REF], Nbombi-SSU-J (N. bombi: [START_REF] Klee | Specific and sensitive detection of Nosema bombi (Microsporidia: Nosematidae) in bumble bees (Bombus spp.; Hymenoptera: Apidae) by PCR of partial rRNA gene sequences[END_REF] and CB-ITS1 (C. bombi: Schmid-Hempel and Tognazzo, 2010).

To validate our approach on bumblebees, Honey bees (Apis mellifera) were used as positive controls for parasite infection. Honey bee workers of unknown age were obtained from a Nosema-free (N. ceranae and N. apis) colony maintained at our experimental apiary (University Paul Sabatier, Toulouse). The absence of parasite in the colony was confirmed in a duplex PCR with the primers 218MITOC and 321APIS on a sample of 15 workers [START_REF] Martín-Hernández | Outcome of colonization of Apis mellifera by Nosema ceranae[END_REF].

Parasites

N. ceranae spores were obtained from a naturally infected honey bee colony. The abdomens of 15 honey bee foragers were crushed into dH 2 O, and the homogenate was examined using light microscopy (x400). Samples showing spores were checked in a duplex PCR [START_REF] Martín-Hernández | Outcome of colonization of Apis mellifera by Nosema ceranae[END_REF] to verify for the presence of N. ceranae and the absence of N. apis (spores of both parasites have similar morphologies; [START_REF] Fries | Natural infections of Nosema ceranae in European honey bees[END_REF]). Positive honey bee gut homogenates were used to prepare the spore solutions for the experimental infections, following a standard purification protocol [START_REF] Fries | Standard methods for Nosema research[END_REF]. Spore solutions were prepared no more than one week before the infections. Briefly, 1 mL of the honey bee gut homogenate was centrifuged at 5000 rpm for 5 min. The supernatant containing tissue debris was discarded and the pellet containing the spores was re-suspended in 0.5 mL of dH 2 O by vortexing. The sample was centrifuged and washed into dH 2 O two times more to obtain a spore solution of 85% purity [START_REF] Fries | Standard methods for Nosema research[END_REF]. N. ceranae spores were counted using an improved Neubauer haemocytometer (Cantwell, 1970) in a light microscope (x400). Counts were made in five squares of 0.2 x 0.2 mm 2 area in both chambers of the haemocytometer and the total number of spores was averaged. The final inoculum concentration was adjusted to either 7500 spores/μL or 15000 spores/μL in 20% (v/v) of sucrose solution. All the inocula were prepared the day of the experimental infections.

Infections

Bumblebees and honey bees were exposed to solutions of N. ceranae spores on the same day. Based on preliminary observations showing that different starvation durations are needed to elicit feeding in bumblebees and honey bees, bumblebees and honey bees were manipulated separately. At 9.00 am (GMT+1), 300 bumblebees were isolated in empty Petri Dishes (20 mm Ø) and starved for 5h. At 12.00 pm, 300 honey bees were isolated in the same conditions but for 2h only. At 2.00 pm, bumblebees were individually exposed to a drop of 20 μL of sucrose solution (20% v/v) containing either 0 spore (control), 150K spores or 300K spores.

Honey bees were exposed to a drop of sucrose solution containing either 0 spore (control) or 150K spores. The sucrose was delivered with a micropipette in the Petri dish of each bee. Only the bees that consumed the entire drop within 2 two hours were kept for the experiments (272 out of the 300 bumblebees, 258 out of 300 honey bees, see details in supplementary Table 1).

Artificial diets

Immediately after parasite exposure, bees were allocated to one of two artificial diets, which generated 10 experimental groups. The number of individuals in each group varied between 44 and 50 for bumblebees, and 47 and 77 for honey bees (supplementary Table 1). Diets were liquid solutions containing either a low protein to carbohydrate ratio (P:C 1:150, hereafter "low-protein diet") or a high protein to carbohydrate ratio (P:C 1:5, hereafter "high-protein diet"). The two diets were prepared with a fixed total amount of nutrients (P + C content of 170 g/L).

Carbohydrates were supplied as sucrose (Euromedex, France). Proteins consisted in a mixture of casein and whey (4:1) (Nutrimuscle, Belgium). Both diets contained 0.5% of vitamin mixture for insects (Sigma, Germany).

Survival

Bumblebees and honey bees were individually kept in a Petri dish with a hole (1 cm Ø) on the top lid, in which was placed a gravity feeder containing one of the two diets. The feeder consisted in a 1.5 mL Eppendorf tube with a hole at its basis through which the bees could insert their proboscis and ingest liquid food. All bees were kept in two identical incubators (Pol-Eko, Poland) at 26ºC, with a photoperiod of 12h light: 12h dark, for 21 days. Each incubator contained the same proportion of bees from the 10 experimental groups (supplementary Table 1). Every day, diets were renewed and dead bees were stored at -20 ºC for molecular analyses. Bees that survived the entire experiment were freeze-killed on day 21.

Prevalence and intensity of N. ceranae

Parasite prevalence (presence in the gut of bees) was assessed in bumblebees and honey using PCR (see example Figure 1A). The gut of each bee was extracted and homogenised in dH 2 O and vortexed with 2 mm glass beads (Labbox Labware, Spain). Genomic DNA was extracted using Proteinase K (20 mg/mL; Euromedex, France) and 1 mM of Tris-EDTA Buffer (pH = 8). PCR conditions were adapted from [START_REF] Martín-Hernández | Outcome of colonization of Apis mellifera by Nosema ceranae[END_REF] for a monoplex PCR with the 218MITOC primers specific for N. ceranae. PCR reactions were carried out in 48-well microtitre plates in a S1000™ Thermal Cycler (Biorad, CA). Each reaction contained 1.5 U of Taq Polymerase (5 U/μL; MP Biomedicals, CA), 1x PCR Direct Loading Buffer (MP Biomedicals, CA), 0.4 μM of each pair of primers [START_REF] Martín-Hernández | Outcome of colonization of Apis mellifera by Nosema ceranae[END_REF], 200 μM of dNTPs (Jena Biosciences, Germany), 0.48 μg/μL of BSA (Sigma, Germany) and 2.5 μL of DNA sample in a final volume of 25 μL. Thermal conditions consisted in an initial denaturing step of 94 °C for 2 min, followed by 35 cycles of 94 °C for 30 s, 61.8ºC for 45 s and 72 °C for 2 min, with a final elongation step of 72 °C for 7 min. The length of PCR products (i.e. 218 pb) was checked in a 1.2% agarose gel electrophoresis stained with SYBR Safe DNA Stain (Edvotek, Washington DC).

Parasite intensity (spore load in the gut) was estimated in positive PCR bumblebee samples under a light microscope (x400). The number of spores was counted as described above (see Section 1.2 and example Figure 2A). Random samples of Nosema-negative PCR bumblebees were also screened to confirm the absence of parasite spores.

Statistical analyses

Bumblebees were analysed for parasite prevalence, parasite intensity and survival.

Honey bees were used as positive control for parasite infection, and were therefore only analysed for parasite prevalence. All analyses were performed in R v. 1.0.143 (R Development Core Team). All means are shown with standard errors (mean ±

S.E).

The effects of diet, spore dosage and their interaction on parasite prevalence (proportion of individuals infected after parasite exposure) were tested using Generalized Linear Models with a binomial error structure (binomial GLMs). The effect of diet, spore dosage and their interaction on the proportion of bees showing N. ceranae spores in their gut were tested using a binomial GLM. The effect of diet, spore dosage and their interaction on parasite intensity (number of spores per bee) were tested using a negative binomial GLM (because of the large over-dispersion of the data). The parasite loads of individuals bees that survived until the end of the experiment (day 21) and those that died before were compared using a negative binomial GLM with a binary predictor (e.g. dead or alive at day 21) as fixed effect.

GLMs with binomial distribution errors were fitted using the glm function in the R package "stats". GLMs with a negative binomial error distribution were fitted using the glm.nb function in the R package "MASS" [START_REF] Venables | Modern applied statistics with S[END_REF]. All the models were tested for interactions among predictors (e.g. diet, dosage and PCR results). Interactions that did not improve the fitting were removed from the models using the Akaike information criterion (AIC) for model comparison [START_REF] Akaike | Prediction and Entropy[END_REF].

The survival of bumblebees was analysed using a Kaplan-Meier test curve with the function survfit in the R package "Survival" [START_REF] Therneau | Modeling survival data: extending the cox model, statistics for biology and health[END_REF].

The effects of spore dosage, diet, infectious status and their interactions were analysed using Cox proportional-hazards regression models (function coxph in the R package "Survival"), followed by a Tukey post-hoc test to account for pairwise comparisons. In all models, colony origin and incubator identity were included as random factors.

Results

Parasite prevalence

To assess infection rates, bumblebees and honey bees were analysed with PCR for the presence of parasites after the 21 days of the experiment. In total, 46.15% of the bumblebees (84 out of 182, Figure 1B and Table 1) and 83.8% of the honey bees (119 out of 142, Figure 1C) exposed to N. ceranae were PCR positive, which validates our protocol. Note however that a proportion of control (non-exposed) individuals (5.5% of bumblebees, 19.8% honey bees) were found PCR positive (Figures 1B and1C). This suggests that our colonies were not entirely free of parasites prior to the experiments or that horizontal cross-contamination occurred during the experiments. All these infected control bees were excluded from further analyses.

Diets significantly influenced the proportion of bees that became infected after exposure to the parasite (Figures 1B and1C; Table 1). A significantly larger number of bumblebees became infected when fed the low-protein diet than when fed the high-protein diet (GLM binomial : Estimate = 1.186 (± 0.313), z = 3.79, p < 0.001), irrespective of spore dosage (GLM binomial : Estimate = 0.4870 (± 0.313), z = 1.503, p = 0.133). Likewise, a larger number of honey bees were infected when fed the lowprotein than when fed the high protein-diet (GLM binomial : Estimate = 1.298 (± 0.538), z = 2.41, p = 0.016). Therefore, feeding a low-protein diet induced highest infection rates in both species. Interestingly all the bumblebees that were fed the low-protein diet and that survived until day 21 were PCR positive to N. ceranae (6 bumblebees for 150K, 9 bumblebees for 300K). By contrast, the only bumblebee that was fed the high-protein diet and that survived until day 21 (300K) was not infected.

Parasite loads

To assess the intensity of the infection, the gut homogenates of dead PCR positive bumblebees were screened under microscope for the presence of N. ceranae spores.

Spores were observed in bumblebee guts for both diets (Figures 2B-E; see supplementary Table 1 for details). Comparing the presence of spores in bumblebees that did not die on the same day yield some information about the dynamics of spore production. For the low-protein diet, spores were seen from day 3 to day 20 post exposure with 150K spores (Figure 2B) and from day 4 to day 20 post exposure with 300K spores (Figure 2C). Spores were never observed between day 8 and day 15. This may be due to the low mortality rate of bumblebees on these days.

For the high-protein diet, spores were seen from day 2 to 8 post exposure with 150K spores (Figure 2D), and from day 3 to day 9 post exposure with 300K spores (Figure 2E).

Overall 30.9% (26 out of 84) of the infected bumblebees showed N. ceranae spores in their gut (Table 1). This estimation of prevalence based on spore loads is lower than that based on PCR screening (Figure 1B and Table 1) because, here, the intracellular stages of the parasite (e.g. meronts, sporonts) cannot be detected. The proportion of bumblebees with spores in their gut was similar irrespective of the diet (GLM binomial _ diet : Estimate = 0.176 (± 0.489), z = 0.36, p = 0.718) and the spore dosage (GLM binomial _ spore dosage : Estimate = 0.109 (± 0.477), z = 0.23, p = 0.819). Spore loads were highly variable across individuals, with an average of 367.31 (± 72.03) spores per bumblebee. The spore dosage the bees were exposed to had no effect on the spore loads found in their gut (GLM negative-binomial : Estimate = -0.002 (± 0.002), z = -0.73, p = 0.464). On the contrary, the diet had a significant effect on spore load (GLM negative-binomial : Estimate = 1.294 (± 0.347), z = 3.73, p < 0.001), leading to higher amounts of spores in bumblebees fed the high-protein diet (662.50 ± 222.71 spores per bee) than in bumblebees fed the low-protein diet (182.81 ± 40.99 spores per bee).

Considering bumblebees that were fed the low-protein diet and that survived until day 20 post exposure, only 4 out of 6 individuals exposed to 150K spores (175 ± 87.5 spores per bee; Figure 2B) and 4 out 9 individuals exposed to 300K spores (125 ± 62.5 spores per bee; Figure 2C) showed spores in their gut. These bumblebees showed similar spore loads than those fed the same diet but that died before day 20 post exposure (GLM negative-binomial: Estimate = -0.363 (± 0.389), z = -0.93, p = 0.350).

Survival

To test the effect of spore dosage and diet on the physiology of bumblebees, survival was analysed during the 20 days after parasite exposure. Here the infection status of each bumblebee was based on the PCR results.

Overall, bumblebees fed the high-protein diet had lower survival than bumblebees fed the low-protein diet (Figure 3; Cox: estimate = -0.75 (± 0.14), z = -5.17, p < 0.001). Bumblebees fed the high-protein diet (Figure 3A) showed similar mortality rate irrespective of spore dosage (Table 2) and infectious status (supplementary Table 2). By contrast, bumblebees fed the low-protein diet (Figure 3B) had a significantly reduced survival when exposed to spores than when nonexposed (Table 2). For this diet, 50% of exposed bumblebees died between days 6 and 7 post exposure. This lethal time 50 (LT 50 ) was not reached for the non-exposed (control) bumblebees. Interestingly, in the low-protein diet, infected bumblebees tended to die faster than control bumblebees, but survived significantly longer than bumblebees exposed and non-infected (Figure 3B; supplementary Table 2).

Therefore, both parasite exposure and infection had negative effects on the survival of bumblebees maintained on the low-protein diet.

Discussion

Several recent studies suggest that N. ceranae negatively affect bee behaviour and cognition, which may have dramatic consequences for colony growth and survival [START_REF] Gage | Nosema ceranae parasitism impacts olfactory learning and memory and neurochemistry in honey bees (Apis mellifera)[END_REF]Piiroinen and Goulson, 2016). In bumblebees, these results remain difficult to interpret due to the low efficiency of experimental infection protocols. Here we exploited recent insight into the nutritional ecology of bees (e.g. [START_REF] Vaudo | Macronutrient ratios in pollen shape bumble bee (Bombus impatiens) foraging strategies and floral preferences[END_REF][START_REF] Kraus | Bumblebees adjust protein and lipid collection rules to the presence of brood[END_REF][START_REF] Addin Ruedenauer | Best be(e) on low fat: linking nutrient perception, regulation and fitness[END_REF] to develop a reliable method to infect bumblebees with N. ceranae. We identified key effects of diet composition on bumblebee infection rates and survival, indicating a complex interaction between diet, parasite development and host health.

Overall 46% of the bumblebees exposed to N. ceranae spores were infected, a percentage that increased up to 70% when only considering bumblebees that were exposed to 300K spores and maintained on a low-protein high-carbohydrate diet.

These levels of prevalence are similar to those obtained by [START_REF] Graystock | Emerging dangers: deadly effects of an emergent parasite in a new pollinator host[END_REF] (62% infection rate) who used a 20 to 45 times lower infection dose (measured in naturally infected colonies: 6500 spores/bee) administered with a micropipette directly into the bee mouth parts. These rates of successful infections are higher than all previous studies where bumblebees were exposed to an order of 10 5 spores/bee either delivered as a drop of solution in a Petri Dish (39%; [START_REF] Fürst | Disease associations between honeybees and bumblebees as a threat to wild pollinators[END_REF] or with a micropipette directly into the bee mouth (0-3%; Piiroinen and Goulson, 2016;Piiroinen et al., 2016).

We did not find any clear effect of parasite dosage (150K or 300K spores per bee) on prevalence and survival. Comparing our results to that of previous studies does not indicate such effect neither, which suggests that above a certain concentration of parasite spores (e.g. 6500 spores/bee in [START_REF] Graystock | Emerging dangers: deadly effects of an emergent parasite in a new pollinator host[END_REF]), parasite dosage is not an important factor determining the success of an infection. By contrast, we found a strong effect of diet on parasite prevalence and spore loads.

Previous studies indicate that pollen intake affects honey bee physiology and tolerance to N. ceranae [START_REF] Basualdo | Bee bread increases honeybee haemolymph protein and promote better survival despite of causing higher Nosema ceranae abundance in honeybees[END_REF]Di Pasquale et al., 2013). Using artificial diets with controlled amounts of protein and carbohydrates, we demonstrate that food macronutrient balance substantially influences both the infection rate and the survival of bumblebees. A higher number of bumblebees were infected when fed the low-protein high-carbohydrate diet, suggesting that different blends of nutrients differently affect the germination of the parasite (but see [START_REF] Jack | Effects of pollen dilution on infection of Nosema ceranae in honey bees[END_REF]. The digestion of the different macronutrients in the bumblebee gut, whose microbiota is mostly composed by sugar-fermentative bacteria [START_REF] Mohr | Diversity and phylotype consistency of bacteria in the guts of three bee species (Apoidea) at an oilseed rape field[END_REF], may lead to changes in the gut environment that could favour the parasite germination, such as shifts in pH [START_REF] Wittner | The Microsporidia and microsporidiosis[END_REF]. Furthermore, because N. ceranae exploits the metabolism of carbohydrates to obtain energy from its host [START_REF] Mayack | Energetic stress in the honeybee Apis mellifera from Nosema ceranae infection[END_REF]) a higher carbohydrate consumption by infected bumblebees may benefit the establishment of N. ceranae. Alike previous studies on honey bees that showed that the supplement of pollen in diet increase the parasite intensity [START_REF] Basualdo | Bee bread increases honeybee haemolymph protein and promote better survival despite of causing higher Nosema ceranae abundance in honeybees[END_REF][START_REF] Bunning | Characterizing the impact of commercial pollen substitute diets on the level of Nosema spp. in honey bees (Apis mellifera L.)[END_REF][START_REF] Jack | Effects of pollen dilution on infection of Nosema ceranae in honey bees[END_REF], we found that bumblebees with access to higher amounts of protein show higher spore loads in their gut, suggesting that proteins benefit the replication of the parasite.

The effect of diet was also evident on bumblebee survival. N. ceranae reduced the survival of bumblebees, specifically in the low-protein high-carbohydrate diet, where mortality rate increased by day 3 post exposure. This result is consistent with the time described for N. ceranae to produce new spores in the honey bee gut [START_REF] Higes | Experimental infection of Apis mellifera honeybees with Nosema ceranae (Microsporidia)[END_REF]. Similarly to [START_REF] Graystock | Emerging dangers: deadly effects of an emergent parasite in a new pollinator host[END_REF], we found that most of the infected bumblebees (67.5%) died without showing spores in their gut, suggesting that the parasite was not able to complete its cycle at a detectable level (i.e. produce new spores). The lack of spores in the bumblebee guts could be due to a migration of the parasite to the fat body of their host where it cannot reproduce [START_REF] Graystock | Emerging dangers: deadly effects of an emergent parasite in a new pollinator host[END_REF]. Alternately, this could be a consequence of a high virulence of the parasite.

Emergent parasites can be very virulent for a novel host causing its death before reproducing and releasing their offspring [START_REF] Schmid-Hempel | Parasites in social insects[END_REF]. Although it is not clear when N. ceranae started to colonise bumblebee hosts (including B. terrestris), the parasite was first identified in bumblebees in 2005 [START_REF] Plischuk | South American native bumblebees (Hymenoptera: Apidae) infected by Nosema ceranae (Microsporidia), an emerging pathogen of honeybees (Apis mellifera)[END_REF], implying a short coevolution time in which the parasite may not have had time to fully adapt its virulence to its diverse host species. Interestingly, the absence of parasite spores in the gut of bumblebees that died at different times could reflect the ability of bumblebees to clear the parasite. The fact that infected bumblebees fed the lowprotein high-carbohydrate diet survived longer than exposed non-infected bumblebees fed the same diet suggests that the mechanisms allowing parasite clearance incur a higher metabolic cost, here manifested as a reduction of bumblebee lifespan, than parasite tolerance. Nonetheless, given that only dead bumblebees were checked for spores and that spore loads are generally higher in live bees than in dead ones [START_REF] Zheng | Spore loads may not be used alone as a direct indicator of the severity of Nosema ceranae infection in honey bees Apis mellifera (Hymenoptera:Apidae)[END_REF], studying the dynamics of N. ceranae spore production in live bumblebees (for instance by analysing faeces) will be necessary to determine whether these insects are able to get rid of the parasite.

The fact that bumblebees showed low parasite prevalence but died faster when fed a high-protein low-carbohydrate diet suggests that immunity and lifespan are maximized at different nutritional balances. Several studies show how an animals' diet can differently influence the expression of key life-history traits, forcing animals to trade-off between optimizing multiple traits simultaneously (e.g. Bunning et al., 2016[START_REF] Bunning | Characterizing the impact of commercial pollen substitute diets on the level of Nosema spp. in honey bees (Apis mellifera L.)[END_REF][START_REF] Rapkin | The geometry of nutrient space-based life-history trade-offs: sex-specific effects of macronutrient intake on the trade-off between encapsulation ability and reproductive effort in decorated crickets[END_REF]. In insects, lifespan is typically enhanced on high-carbohydrate diets whereas reproduction is maximized on high-protein diets (fruit flies: [START_REF] Lee | Lifespan and reproduction in Drosophila: new insights from nutritional geometry[END_REF]Fanson et al., 2009;[START_REF] Reddiex | Sex-Specific Fitness consequences of nutrient intake and the evolvability of diet preferences[END_REF][START_REF] Jensen | Sex-specific effects of protein and carbohydrate intake on reproduction but not lifespan in Drosophila melanogaster[END_REF][START_REF] Semaniuk | Within-diet variation in rates of macronutrient consumption and reproduction does not accompany changes in lifespan in Drosophila melanogaster[END_REF], crickets: Maklakov et al., 2008). Immunity and reproduction also display differences in nutritional requirements (fruit flies: [START_REF] Ponton | Nutritional immunology: a multi-dimensional approach[END_REF][START_REF] Ponton | Macronutrients mediate the functional relationship between Drosophila and Wolbachia[END_REF]decorated crickets: Rapkin et al., 2018;leafworm: Cotter et al., 2011). Honey bees survive longer on high-carbohydrate diets [START_REF] Altaye | Convergence of carbohydrate-biased intake targets in caged worker honeybees fed different protein sources[END_REF] and pollen (the main source of protein) favours the survival of individuals infected with N. ceranae [START_REF] Basualdo | Bee bread increases honeybee haemolymph protein and promote better survival despite of causing higher Nosema ceranae abundance in honeybees[END_REF][START_REF] Bunning | Characterizing the impact of commercial pollen substitute diets on the level of Nosema spp. in honey bees (Apis mellifera L.)[END_REF][START_REF] Jack | Effects of pollen dilution on infection of Nosema ceranae in honey bees[END_REF][START_REF] Zheng | Spore loads may not be used alone as a direct indicator of the severity of Nosema ceranae infection in honey bees Apis mellifera (Hymenoptera:Apidae)[END_REF]. Whether sterile bumblebee workers trade-off between over-ingesting protein and under-ingestion of carbohydrates in order to reduce parasite establishment at the expense of a shorter lifespan is an open question. In these social insects, such individual strategy may considerably reduce the risks of contamination of other workers within the colony [START_REF] Poissonnier | A theoretical exploration of dietary collective medication in social insects[END_REF].

Developing standard protocols to characterize the sublethal effects of parasites and pathogens on bees has become a major challenge for understanding bee population declines [START_REF] Gómez-Moracho | Effects of parasites and pathogens on bee cognition[END_REF]. Here we demonstrated that diet is key in determining infection rates of bumblebees exposed to N. ceranae. Highest infection rates and longest survivals were obtained with a high-carbohydrate lowprotein diet, thereby providing ideal conditions for investigating potential effects of N. ceranae on bee behaviour and cognition. Other parameters, not tested here, may also be of importance and investigated in future studies. For instance, both our study and that of [START_REF] Graystock | Emerging dangers: deadly effects of an emergent parasite in a new pollinator host[END_REF] starved bumblebees for at least 5 h prior to parasite exposure, which may have increased the probability of parasite establishment. Variations in the age of the bumblebee tested may also explain some of these differences. In the only study that controlled for age, [START_REF] Fürst | Disease associations between honeybees and bumblebees as a threat to wild pollinators[END_REF] infected 2-days old bumblebees (post eclosion from the pupa) and obtained a lower infection rate than that presented here and no effect on bumblebee mortality, suggesting that young bumblebees are less susceptible to the parasite. Finally, we cannot exclude differences in the virulence of the N. ceranae strains used for experimental infection across studies (but see [START_REF] Van Der Zee | Virulence and polar tube protein genetic diversity of Nosema ceranae (Microsporidia) field isolates from Northern and Southern Europe in honeybees (Apis mellifera iberiensis)[END_REF]. We hope that our infection protocol will facilitate further studies on the interactions between N. ceranae and bumblebees in order to better assess the risks this emergent parasite represents for wild pollinators. and ML were funded by a grant from the Agence Nationale de la Recherche to ML (ANR-16-CE02-0002-01). C.R., Hunt, J., 2016. Dietary choice for a balanced nutrient intake increases the mean and reduces the variance in the reproductive performance of male and female cockroaches. Ecol. Evol. 6, 4711-4730. doi:10.1002/ece3.2243Bunning, H., Rapkin, J., Belcher, L., Archer, C.R., Jensen, K., Hunt, J., 2015 Funct. Ecol. 25, 186-198. doi:10.1111/j.1365-2435.2010.01766.x Cremer, S., Armitage, S.A.O., Schmid-Hempel, P., 2007. Social Immunity. Curr. Biol. 17, R693-R702. doi:10.1016/j.cub.2007.06.008 Di Pasquale, G., Salignon, M., Le Conte, Y., Belzunces, L.P., Decourtye, A., Kretzschmar, A., Suchail, S., Brunet, J.-L., Alaux, C., 2013. Influence of pollen nutrition on honey bee health: do pollen quality and diversity matter? PLoS One ceranae (PCR positive) for all diets and spore dosages. Bumblebee groups contained between 44 and 50 individuals. Honey bee groups contained between 47 and 77 individuals (see details in supplementary Table 1). (see details in supplementary Table 1). 3). Each group contained between 44 and 50 individuals (see details in supplementary Table 1).

  8, e72016. doi:10.1371/journal.pone.0072016 Dosselli, R., Grassl, J., Carson, A., Simmons, L.W., Baer, B., 2016. Flight behaviour of honey bee (Apis mellifera) workers is altered by initial infections of the fungal parasite Nosema apis. Sci. Rep. 6, 36649. doi:10.1038/srep36649 Doublet, V., Natsopoulou, M.E., Zschiesche, L., Paxton, R.J., 2015. Within-host competition among the honey bees pathogens Nosema ceranae and Deformed wing virus is asymmetric and to the disadvantage of the virus. J. Invertebr. Pathol. 124, 31-34. doi:10.1016/j.jip.2014.10.007 Dussaubat, C., Maisonnasse, A., Crauser, D., Beslay, D., Costagliola, G., Soubeyrand, S., Kretzchmar, A., Le Conte, Y., 2013. Flight behavior and pheromone changes associated to Nosema ceranae infection of honey bee workers (Apis mellifera) in field conditions. J. Invertebr. Pathol. 113, 42-51. doi:10.1016/j.jip.2013.01.002 Fanson, B.G., Weldon, C.W., Pérez-Staples, D., Simpson, S.J., Taylor, P.W., 2009. Nutrients, not caloric restriction, extend lifespan in Queensland fruit flies (Bactrocera tryoni). Aging Cell 8, 514-523. doi:10.1111/j.1474-9726.2009.00497.xTablesand Table legends

Figures and figure legends

  Figures and figure legends

Figure 1 .

 1 Figure 1. Parasite prevalence. (A) Agarose electrophoresis gel with negative (lanes 1, 2, 5 and 6) and positive (lanes 3, 4, 7-9) bumblebees to N. ceranae determined by PCR. N: negative control of PCR; P: positive control of PCR; Ld: molecular size marker (100 pb). Percentage of (B) bumblebees and (C) honey bees infected by N.ceranae (PCR positive) for all diets and spore dosages. Bumblebee groups contained between 44 and 50 individuals. Honey bee groups contained between 47 and 77 individuals (see details in supplementary Table1).

Figure 2 .

 2 Figure 2. Parasite loads. (A) N. ceranae spores observed in an infected bumblebee (optical microscope, x 400). (B-E) Proportion of dead bumblebees at different days post exposure that were positive to N. ceranae in a PCR (grey bars) and showed spores in their gut (black bars), for both diets (high-and low-protein diets) and spore dosages (150K and 300K). Each group contained between 44 and 50 individuals

Figure 3 .

 3 Figure 3. Survival analyses. Survival probability of bumblebees fed the high-protein diet (A) and the low-protein diet (B), for the different spore dosages (control, 150K and 300K) across time. Infected (dashed lines) and non-infected (solid lines) bumblebees are differentiated. Different letters associated to curves indicate statistical differences in survival (p<0.05; post-hoc Tukey test after Cox-regression model in a Kaplan Meier test curve, see supplementary Table3). Each group

  . Protein and carbohydrate intake influence sperm number and fertility in male cockroaches, but not sperm viability. Proc. R. Soc. B Biol. Sci. 282. Cotter, S.C., Simpson, S.J., Raubenheimer, D., Wilson, K., 2011. Macronutrient balance mediates trade-offs between immune function and life history traits.

	doi:10.1098/rspb.2014.2144
	Cantwell G.E. 1970. Standard methods for counting Nosema spores, Am. Bee J.
	110, 222-223.

Table 1 . Number of bumblebees exposed to N. ceranae, infected with parasite (PCR positive), and showing spores in their gut.

 1 The percentage of bumblebees infected relative to those exposed, and the percentage of bumblebees showing spores in their gut relative to the number of PCR positive individuals are given into brackets.

	Diet	Spore dosage	Exposed	Infected	Showing spores
	Low-protein	150K	44	23 (52.27%)	7 (30.4%)
		300K	45	31 (68.88%)	9 (29.03%)
	High-protein	150K	47	14 (29.78%)	4 (28.5%)
		300K	46	16 (34.78%)	6 (37.5%)
	Total		182	84 (46.15%)	26 (30.9%)

Table 2 . Cox Regression Model testing the effect of spore dosage on the survival of bumblebees for each diet.

 2

	Diet	Spore dosage	Estimate	S.E.	z	p
	High-protein	150K	0.2766	0.2115	1.308	0.191
		300K	0.1440	0.2151	0.669	0.503
	Low-protein	150K	1.2595	0.2792	4.511	< 0.001
		300K	1.1021	0.2808	3.925	< 0.001

Acknowledgements

We thank Pascale Belenguer, Lucie Hotier, Audrey Dussutour and Enikö Csata for their help and advice.

Funding TGM was funded by a postdoctoral fellowship from the Fyssen Foundation. PH was funded by the 'Laboratoire d'Excellence (LABEX)' TULIP (ANR-10-LABX-41). TD, CP author/funder. All rights reserved. No reuse allowed without permission.


Philippe Keckhut
email: philippe.keckhut@aerov.jussieu.fr

Stephane Marchand

Alain Hauchecorne

Sophie Godin-Beekmann

Françoise Pinsard

Stuart Mcdermid

Thierry Leblanc

Georg Hansen

Jean-Luc Baray

Hassan Bencherif

Dan Swart

Yasjka Meijer

Shiv Pal

Marielle Guirlet

Claude Vialle

Françoise Posny

Florence Goutail

VALIDATION OF GOMOS OZONE PROFILES USING NDSC LIDAR: STATISTICAL COMPARISONS

The lidars deployed in the NDSC framework have been used for the validation of GOMOS onboard ENVISAT. During the commissioning phase around ten coincidences per site have been investigated. No significant bias, larger than ±5%, has been reported except around 50 km and 20 km where both techniques are known to present some limitations. The estimated errors of both GOMOS and lidar are in good agreement with the standard deviation of the differences between coincidences. At higher latitude, comparisons are not so good because of the measurement conditions of bright limb during this period.

DATA DESCRIPTION

The network for the Detection of Stratospheric Change (NDSC) is a set of high-quality, remote-sounding research stations, designed for observing the physical and chemical state of the stratosphere and mesosphere [START_REF] Kurylo | Network for the Detection of Stratospheric Change[END_REF]. Vertical profiles of temperature and ozone are measured using lidars and radiosondes. Stations consist of at least five primary stations (fully equipped) and of some other complementary sites (providing a more limited number of instruments), are located from poles to tropics providing a well-adapted spatial coverage for an independent calibration of satellite sensors of the middle atmosphere. The instruments included in this project were selected on the basis of insuring the largest latitudinal coverage from strategic stations located from mid-latitudes, to high-latitudes and tropics (where bias may be larger) and from northern to southern hemisphere. They were also selected on the basis of being operational high quality measurements managed by scientists interested in satellite sensor validation. Quality control is continuously achieved through rigorous calibration procedures and inter-comparison campaigns. A review of those comparisons involving lidars has been performed and presented in table Similarly with the comparison shown in figure 1, the agreements were quite good both qualitatively and quantitatively. Most of the structures have been seen similarly with the both instruments except in the lower stratosphere where the noise increase rapidly and for some stars having a lower intensity radiation. When large ozone structures were present in the vertical profiles, no significant altitude shift has been observed.

VERTICAL BIAS

While a still too small number of coincidences were available, first statistical comparisons were conduced with the lidar data specifically associated with the AO 360 VETO. Mean differences are usually associated with systematic differences or bias. These preliminary comparisons reveal between 20 and 45 km no bias larger than ±10% except for Andoya site where larger differences can be noted below 25 km and above 40 km with bias of 20%. However during the early fall period sun is still high, for the latitude of Andoya, and the background noise for both lidar and GOMOS is larger. To appreciate, how significant were those mean differences, standard errors (SE) have been calculated. This quantity is estimated as the mean standard deviation of the difference divided by the square root of the number (n) of available coincidences in assuming that they are independent (see Eq. 1). From those estimates none of the differences appear systematically at the same altitude levels. While for OHP, the largest bias appears between 25 and 35 km, for Andoya and TMF a bias is noted below 25 km. For Hawaii, a significant bias appears above 45 km where the lidar signals from the other sites are already under the noise. In addition to altitude and latitude, other parameters may impact on the accuracy of GOMOS ozone retrieval, such as the star radiance and the temperature, that have not yet be investigated. The standard deviation of the differences between GOMOS and lidar data can be explained by the contribution of the instrumental noise of both instruments that can be estimated from the expected errors of the both instruments. Differences can also come from the geometry and characteristic of the both instruments. Lidar measurements are integrated over several hours while the horizontal resolution of GOMOS is larger due to the horizontal view path. The uncertainty of GOMOS measurements is larger at the low altitudes because UV wavelength is quickly absorbed and signals became smaller. In opposite, lidar uncertainties increase with altitude because of the photon noise related to the air-density decrease. The quadratic addition of GOMOS and lidar instrumental uncertainties are minimum (5%) around 25-30 km except for Andoya (20%). The quadratic addition of the both instrument is around 20% at 45 km depending of the lidar site and 15% at 20 km depending of the measurement conditions of GOMOS. The standard deviation of the differences between the both instruments is in good agreement with the estimated error for all the sites and mainly for Hawaii. At mid-latitude, the both sites reveal larger differences between GOMOS and lidar at 25-35 km probably due to the instrument geometries and the presence of small scale structures such as laminae.

variance n SE ◊ = 1 (1)

NOISE ESTIMATED

For Andoya surprisingly exhibits a standard deviation between the both sources smaller than the quadratic sum of the estimated errors below 25 km. The variability of the data series is calculated for each datasets in using the coincident measurements. The comparisons of GOMOS variability with the one estimated with the lidar located at Hawaii, reveal both some fluctuations between 5 and 10 % according to altitudes and show a very good agreement except above 45 km and below 25 km where the instrumental noises increase considerably respectively for lidar and GOMOS as expected. Temporal errors are in good agreement with both the quadratic sum of the estimated errors and the standard deviation of the differences. At mid latitude, GOMOS provides a larger variability increasing up to 15-20 % while lidars remain smaller than 10% and often even smaller than 5%. This can be mainly due, to the short-term variability, better reproduced with GOMOS. However, we can note some temporal fluctuations with GOMOS larger than with lidars around 25-35 km where the variance increase from 5 to 15%. This result is again in agreement with the quadratic sum of the estimated errors and the standard deviation of the difference. This result reveals that GOMOS records a larger atmospheric variability than lidar. This is not yet clear if it is due to the instantaneous nature of the GOMOS measurements compared to the integrated lidar soundings or if it is due to some additional GOMOS retrieval uncertainties. At higher latitude (Andoya) the GOMOS temporal variability is similar to the standard deviation of the difference between GOMOS and lidar.

FILERING EFFECTS AND THE GEOPHYSICAL CONTRIBUTIONS

CONCLUSIONS

During the first few months of the commissioning phase where GOMOS data were available a large number of data were obtained and good coincidences (around 10 per site). This number of coincidences allow to estimates first statistical comparisons. They have revealed no bias systematically at all lidar sites, and an agreement with lidar of ±10% have been obtained which is close to the expected accuracy of these instruments. Estimated errors are in agreement with the standard deviation of the daily differences. At higher latitude, a larger bias of 20 % can be noted. However the GOMOS measurement conditions are not the best due to the bright limb conditions. Those conditions do not induced a larger noise but also some bias. This study shows that GOMOS is observing a larger variability than lidar.

  While coincidences with GOMOS operations were planned in advance to optimise time and spatial coincidences, the comparison configuration with lidars was very good. GOMOS measurements were performed between 22:00 and 23:00 hour solar local time, while lidars operate at night mainly during the first half of the night depending of weather conditions. In this configuration most of the GOMOS profiles were obtained in dark limb that is the conditions giving the best accuracy. First individual comparisons were obtained on April 2002.

Figure 1 .

 1 Figure1. A comparison between, a GOMOS profile and a lidar profile at OHP. The mean tangent altitude and OHP were separated by 250 km and the time difference was 2 hours. In this case the star occulted has a magnitude of 2.4 and a spectrum associated with a equivalent black body temperature of 28000 Kelvin.

Figure 2 .

 2 Figure 2. Statistical mean differences with ± one standard error (right) and the both mean profiles (left) for Andoya (top), OHP (second line), Table Mountain (third line) and Hawaii (bottom).

Figure 3 .

 3 Figure 3. Mean standard deviations of the difference between GOMOS and Lidars compared to the expected standard deviation estimated by the square root of the sum of both variances of the estimated errors of GOMOS and the given lidar. These results are provided for Andoya (top left), Hawaii (top right), Table Mountain (bottom left) and OHP (bottom right).

Figure 4 .

 4 Figure 4. Temporal variability deduced from both lidar and GOMOS series. These results are provided for Andoya (top left), Hawaii (top right), Table Mountain (bottom left) and OHP (bottom right).

Table 1 .

 1 [START_REF] Kurylo | Network for the Detection of Stratospheric Change[END_REF]. Further information about lidar can be found on the NDSC server (see http://www.ndsc.ncep.noaa.gov). Errors (systematic and random) expected within ozone and temperature lidar within the NDSC The initial objective of this project was to provide numerous coincident measurements from the ground to insure the best validation. Most of the data obtained during the commissioning phase have been archived in the NILU database. The validation of ozone and temperature profiles using NDSC measurements have been investigated through statistical comparisons to take the advantages of the large number of coincidences expected mainly with lidar that operate at night Two lidars, belonging to two other specific AO have not yet been investigated with a similar protocol. Another objective was to take into account as far as possible the atmospheric variability including the use of assimilation tools. This work has not yet been conducted.

	Parameter	Altitude	Bias	variance
	Ozone	< 20 km < 20 km 20-35 km > 40 km	5-10 % without Raman channels 5 % with Raman channels 2% 5-10 %	5% 5 % 2% 5-10 %
	Temperature	30 km 30 km 35-65 km 75 km	5-10 K without a Raman channel expected 1 K with a Raman channel 1 K 5-10 K	2 K 4 K 2 K 5-10 K
	__________________________________________________________________________________________________________
	Proc. of Envisat Validation Workshop, Frascati, Italy, 9 -13 December 2002 (ESA SP-531, August 2003)

Table 2 .

 2 List of stations involved in ENVISAT validation through the VETO proposal

ACKNOWLEDGEMENTS

The coordination of the validation activities was supported by the French Space Agency CNES. A lot of efforts have been done, by all the technicians located on the different lidar sites, to insure numerous coincident measurements. Lidar teams involved in Hawaii, in California, in south of France and in Andoya are specially acknowledged for providing in nearly real time the lidar measurements. The data used in this publication were obtained as part of the Network for the Detection of Stratospheric Change (NDSC) and are publicly available (see http://www.ndsc.ncep.noaa.gov).

ANNEXE

Here is presented all the files used in the comparisons. The GOM_NL__2P files were produced by the software version GOPR_LV2_5.3 and retrieved from the ACRI-ST server. The HDF files were downloaded from the NILU database server.

For Table Mountain Facilities station groundbased_lidar.dial_cnrs.sa003_table.mountain_d2_20021001t052915z_001.hdf GOM_NL__2PNACR20021001_050053_000000572010_00004_03064_0001.N1 groundbased_lidar.dial_cnrs.sa003_table.mountain_d2_20021001t052915z_001.hdf GOM_NL__2PNACR20021001_081642_000000612010_00006_03066_0001.N1 groundbased_lidar.dial_cnrs.sa003_table.mountain_d2_20021002t063737z_001.hdf GOM_NL__2PNACR20021002_060614_000000582010_00020_03080_0001.N1 groundbased_lidar.dial_cnrs.sa003_table.mountain_d2_20021002t063737z_001.hdf GOM_NL__2PNACR20021002_074651_000000592010_00020_03080_0001.N1 groundbased_lidar.dial_cnrs.sa003_table.mountain_d2_20021003t061414z_001.hdf GOM_NL__2PNACR20021003_053304_000000572010_00033_03093_0001.N1 groundbased_lidar.dial_cnrs.sa003_table.mountain_d2_20021004t054338z_001.hdf GOM_NL__2PNACR20021004_064357_000000592010_00049_03109_0001.N1 groundbased_lidar.dial_cnrs.sa003_table.mountain_d2_20021021t063946z_001.hdf GOM_NL__2PNACR20021021_061141_000000532010_00291_03351_0001.N1 groundbased_lidar.dial_cnrs.sa003_table.mountain_d2_20021028t045411z_001.hdf GOM_NL__2PNACR20021028_054745_000000452010_00392_03452_0001.N1 groundbased_lidar.dial_cnrs.sa003_table.mountain_d2_20021028t045411z_001.hdf GOM_NL__2PNACR20021028_054909_000000562010_00392_03452_0001.N1 For Mauna Loa station groundbased_lidar.dial_cnrs.sa004_mauna.loa_d2_20020907t060504z_001.hdf GOM_NL__2PNACR20020907_072801_000000472009_00163_02722_0001.N1 groundbased_lidar.dial_cnrs.sa004_mauna.loa_d2_20020917t073320z_001.hdf GOM_NL__2PNACR20020917_085526_000000632009_00307_02866_0001.N1 groundbased_lidar.dial_cnrs.sa004_mauna.loa_d2_20020923t080609z_001.hdf GOM_NL__2PNACR20020923_090609_000000492009_00393_02952_0001.N1 groundbased_lidar.dial_cnrs.sa004_mauna.loa_d2_20020924t073618z_001.hdf GOM_NL__2PNACR20020924_083438_000000482009_00407_02966_0001.N1 groundbased_lidar.dial_cnrs.sa004_mauna.loa_d2_20020924t073618z_001.hdf GOM_NL__2PNACR20020924_083604_000000622009_00407_02966_0001.N1 groundbased_lidar.dial_cnrs.sa004_mauna.loa_d2_20021001t072409z_001.hdf GOM_NL__2PNACR20021001_081306_000000462010_00006_03066_0001.N1 groundbased_lidar.dial_cnrs.sa004_mauna.loa_d2_20021001t072409z_001.hdf GOM_NL__2PNACR20021001_081514_000000472010_00006_03066_0001.N1 groundbased_lidar.dial_cnrs.sa004_mauna.loa_d2_20021001t072409z_001.hdf GOM_NL__2PNACR20021001_081642_000000612010_00006_03066_0001.N1 groundbased_lidar.dial_cnrs.sa004_mauna.loa_d2_20021001t072409z_001.hdf GOM_NL__2PNACR20021001_094844_000000732010_00007_03067_0001.N1 For Observatoire de Haute Provence station groundbased_lidar.dial_cnrs.sa001_ohp_d2_20020916t195817z_001.hdf GOM_NL__2PNACR20020916_194004_000000442009_00300_02859_0001.N1 groundbased_lidar.dial_cnrs.sa001_ohp_d2_20020916t195817z_001.hdf GOM_NL__2PNACR20020916_211753_000000492009_00301_02860_0001.N1 groundbased_lidar.dial_cnrs.sa001_ohp_d2_20020916t195817z_001.hdf GOM_NL__2PNACR20020916_212040_000000452009_00301_02860_0001.N1 groundbased_lidar.dial_cnrs.sa001_ohp_d2_20020917t194729z_001.hdf GOM_NL__2PNACR20020917_204618_000000492009_00315_02874_0001.N1 groundbased_lidar.dial_cnrs.sa001_ohp_d2_20020917t194729z_001.hdf GOM_NL__2PNACR20020917_204906_000000452009_00315_02874_0001.N1 groundbased_lidar.dial_cnrs.sa001_ohp_d2_20020918t191842z_001.hdf GOM_NL__2PNACR20020918_201731_000000462009_00329_02888_0001.N1 groundbased_lidar.dial_cnrs.sa001_ohp_d2_20020918t191842z_001.hdf GOM_NL__2PNACR20020918_215459_000000512009_00330_02889_0001.N1 groundbased_lidar.dial_cnrs.sa001_ohp_d2_20020920t192006z_001.hdf GOM_NL__2PNACR20020920_205123_000000562009_00358_02917_0001.N1 groundbased_lidar.dial_cnrs.sa001_ohp_d2_20020920t192006z_001.hdf


domain: sde.mcg sde chim

text:
Michel Vert
email: michel.vert@umontpellier.fr

Anthropogenic Heat Estimate from World Energy Production: Effects on Ice Loss, Global Warming and Humanity

Keywords: global energy production, anthropogenic heat release, AHR, ice loss, ice imbalance, global warming, water-interphase equilibria

encore faibles par rapport à la perte considérable de glaces désormais évidente. Quelques années devraient suffire pour confirmer ou infirmer le contrôle climatique attribué à l'énergie thermique anthropique et aux équilibres interphases de l'eau, surtout si la perte de glaces et le dégagement de chaleur anthropique continuent d'augmenter tandis que la production anthropique de CO2 diminue. En cas de confirmation, c'est la maîtrise de la population et la boulimie d'énergies qu'il faudra promouvoir.

ABSTRACT:

The information provided by greenhouse gas experts is worrying. Dramatic ncreases in ocean level and atmospheric temperature are predicted due to an increase in the "greenhouse effect" caused by anthropogenic carbon dioxide. Considered negligible in the past, the release of anthropogenic heat resulting from the production and the exploitation of the different sources of energy around the world is increasingly seen as a factor that can affect global ices and climate. To go further, the main problem is the estimation of the global anthropogenic heat release. As a new approach, an estimation of the anthropogenic release heat was made from the main sources of energy exploited in the world for the 1994-2017 period after conversion to oil equivalents. The 6.7 Zj estimate was compared to the 9.34 Zj that were necessary to melt the ices lost recently reported as about 28 trillion tonnes for the same period,. The two energies being of the same order of magnitude, it was concluded that the anthropogenic heat released into the environment had been sufficient to melt the ices lost during the selected 23-year period. In addition, it was shown that lost ices and equilibria between the different physical forms of water acted as thermal buffers thus explaining why the overall variations in atmospheric temperature and sea level are still small compared to the considerable loss of ices now evident. A few years should be enough to confirm or invalidate the climate control attributed to anthropogenic thermal energy and water interphase equilibria, especially if the loss of ices and the anthropogenic heat release continue to increase while the anthropogenic production of CO2 decreases. In case of confirmation, it is control of the population and of the energy bulimia that will have to be promoted.

RESUME:

Les informations fournies par les experts en gaz à effet de serre sont préoccupantes. Des augmentations spectaculaires du niveau des océans et de la température atmosphérique sont prévues en raison d'une augmentation de «l'effet de serre» causé par le dioxyde de carbone anthropique. Considéré comme négligeable dans le passé, le dégagement de chaleur anthropique résultant de la production et de l'exploitation des différentes sources d'énergie à travers le monde est de plus en plus considéré comme un facteur pouvant affecter les glaces et le climat mondiaux. Pour aller plus loin, le principal problème est l'estimation du dégagement global de chaleur anthropique. Dans le cadre d'une nouvelle approche, une estimation de la chaleur dégagée anthropique a été réalisée à partir des principales sources d'énergie exploitées dans le monde pour la période 1994-2017 après conversion en équivalents pétrole. L'estimation de 6.7 Zj a été comparée aux 9.34 Zj nécessaires pour faire fondre les glaces perdues récemment déclarées à environ 28 billions de tonnes pour la même période. Les deux énergies étant du même ordre de grandeur, il a été conclu que la chaleur anthropique libérée dans l'environnement avait été suffisante pour faire fondre les glaces perdues au cours de la période de 23 ans choisie. De plus, il a été montré que les glaces perdues et les équilibres entre les différentes formes physiques d'eau agissaient comme des tampons thermiques expliquant ainsi pourquoi les variations globales de la température atmosphérique et du niveau de la mer sont

INTRODUCTION

As a neophyte in climate change prediction, the chemist I am is puzzled by the information that is disseminated by greenhouse gas experts and revived at every turn by media, politicians, environmentalists and various associations. What do we hear? "Climate changes are caused by an increase in the natural "greenhouse effect" due to the release of anthropogenic carbon dioxide and other atmospheric greenhouse gases (methane from herbivorous animals and from natural gas, and even nitrous oxide N 2 O of whipped cream) [1]. These increases are said causing planet heating via infrared radiations and are all related to human activity. Decreasing the sources of anthropogenic CO 2 is the systematical and universally recommended solution today [2].

However, there seem to be arguments against the surplus of greenhouse effect [3-5]. Some opponents (climate-sceptic) contest predictions based on hypotheses and calculations. Others emphasize the absence of correlation between the present small atmosphere and ocean temperature increases and the relatively important loss of the different forms of ice, or oppose fundamentals of interactions between infrared electromagnetic waves and molecules [START_REF] Richard | CO 2 is not driving the global-warming, 2018, Tower of Reason[END_REF]. From what I know about the absorption of visible and ultraviolet electromagnetic waves by the atoms and electrons of chemical functional groups present in organic molecules, I was unable to find flaws in [START_REF] Richard | CO 2 is not driving the global-warming, 2018, Tower of Reason[END_REF] relative to the questioning of CO 2 -related radiative heating. In general, alternatives to the "greenhouse effect" dogma and consideration to conductive effects related to heat exchanges by inter-matter conduction were missing until recently, something which is changing [5].

Let us forget polemics and religious-like arguments to retain the following indisputable facts: -"Earth is losing more and more ice from glaciers, permafrost, floating ice and polar ice caps" [START_REF] Rignot | Four decades of Antarctic Ice Sheet mass balance from 1979-2017[END_REF][START_REF]Ramp-Up in Antarctic Ice Loss Speeds Sea Level Rise[END_REF][START_REF] Shepherd | Mass balance of the Antarctic Ice Sheet from 1992 to 2017[END_REF], and -"Humanity is using more and more energy from different sources with anthropogenic heat release (AHR) as consequence". Until recently, AHR was considered negligible relative to global warming. This is no longer the case. Some scientists are now paying attention to local AHR relative to climate changes although the challenge is at the global level [START_REF] Chen | Exploring the possible effect of anthropogenic heat release due to global energy consumption upon global climate: a climate model study[END_REF][START_REF] He | Impact of the anthropogenic heat release on the energy balance of land-atmosphere system[END_REF].

The aim of this work was to compare ice loss and anthropogenic heat release in the light of some fundamental facts and annual global energy production; this with the perspective of showing some effects on the present climate perturbations and on the future of humanity.

ICE LOSS OR ICE IMBALANCE

On Earth, the balance of the annual ice formation-disaggregation cycle, the socalled ice loss or ice imbalance, is not constant. Therefore, to investigate whether there is a correlation between AHR and ice loss, comparison must be made over a long period of time to minimize the effects of annual fluctuations. In a recent review, authors combined satellite observations and numerical models to estimate the global ice loss between 1994 and 2017. This approach led to a global loss of c.a. 28 ± 2 trillion tonnes of ice over these 23 years [START_REF] Slater | Modern Records from Scripps Institution of Oceanography, CDIAC, Review Article: Earth's ice imbalance[END_REF]. The thermal energy necessary to melt this huge amount of ice was c.a. 9.34 ± 0.6 x 10 21 joules or c.a. 9.34 Zj, according to the enthalpy of fusion of ice: 333.55 x 10 3 J/kg.

PHYSICAL AND CHEMICAL FUNDAMENTAL FACTS

1) When ice is in the presence of heat, it melts and form water which turns to vapour if heating persists. In contrast, vapour in contact with a cold environment condenses back to liquid water and ice if cooling persists.

2) The annual temperature variations of the oceans and the atmosphere in the hemispheres are mainly dependent on the Sun radiative energy, and on its irregular cyclic emissions.

3) When two media are brought into contact with each other, the hottest transfers heat to the coldest. The temperature of two media changes in opposite directions, except in the case of an interphase equilibrium during which the temperature is fixed [12]. 4) Anthropogenic sources of heat include losses at the production stage, animal and human metabolisms, combustions of oil-based products, natural gas, and biomass (including forest wildfire), as well as nuclear and thermal power plants and machines producing work, all difficult to quantify at the globe level.

5) The different sources of energy are not equivalent relative to CO 2 production. When burned in the presence of atmospheric oxygen (O 2 ), charcoal (C) generates hot carbon oxides (CO and CO 2 ) but no primary hot water vapor. In contrast, the combustion of hydrocarbons composed of carbon and hydrogen (oil, peat, lignin, natural gas, wood, and even animal and human metabolisms) generates CO 2 plus hot vapor, both hotter than the atmosphere. In all cases, atmospheric oxygen is consumed. There has been indeed a slight decrease in its proportion in the air and in the oceans over the years [START_REF] Ipcc ; Sukla | Climate change and land: an IPCC special report on climate change, land degradation, sustainable and management, food security, and greenhouse gas fluxes in terrestrial ecosystems[END_REF]. As for the production of electrical energy by nuclear power plants and by renewable resources, it does not generate CO 2 but it generates heat immediately during the production and later on during the exploitation of electricity (electric radiators, TVs, lightings, smartphones, etc., all heat). Even electric trains and cars give off heat. So, all sources of heat and not just fossil fuels disperse heat into the atmosphere and more generally into the environment [START_REF] Manowska | The Importance of Heat Emission Caused by Global Energy Production in Terms of Climate Impact[END_REF]. 6) Once cooled, the hot gas and vapor produced by the combustion of carboncontaining sources of energy integrate the corresponding atmospheric pools. CO 2 is captured by seas, by some alkaline minerals and by plants with regeneration of oxygen (inverted lung) while condensed water is managed by terrestrial absorption, by ice formation, by evaporation ↔ condensation equilibria involved in the formation of clouds and rains, or by reintegration into natural living matter via biochemistry; 7) Chemistry teaches three important fundamentals: 1) in a closed world like Earth "nothing is created, nothing is lost, everything is transformed" (this holds for electromagnetic radiations through absorption, transmission and refraction phenomena); 2) solid ↔ liquid (ice ↔ liquid water) and liquid ↔ vapor (clouds and rains) interphase equilibria consume or generate thermal energy according to the direction they move, and 3) an interphase equilibrium always evolves at constant temperature, that is to say without temperature change during the energy transfer (ice melting or boiling water). For instance, on a sunny day ice in a glass of water melts to bring and maintain the temperature of the water at 0°C until the ice disappears. Then, the temperature of the water increases. In humans and animals, perspiration and evaporation are used to maintain the temperature of the organism fixed (37 °C for man) despite internal or external heating by metabolism and Sun, respectively. When sick, a mammalian organism gets inflammation and fever, i.e. faces extra heat, a situation quite comparable with anthropogenic and wildfire heats in the case of the planet. 8) In the past, huge quantities of fossil energy sources (actually solar energy stored in the distant past) have already been consumed and transformed in parts as heat, water, CO 2 and biomass. Large quantities of heat are still stored (oil, coal, gas, radioactive minerals) or are going to be produced (electricity) in the future. This new thermal energy will supplement the anthropogenic heat already released in the environment. 9) Based on the energy preservation principle, the AHR generated by the combustion of fossil charcoal, oil, gas and biomass, by electricity-producing plants and alternatives, and by machines and devices using this electricity is transferred to the components of the environment, in particular to atmosphere and ocean water. In general, nothing is seen but, for instance, the hot vapor becomes visible if it is cooled rapidly. In winter, it can be seen from lung exhalation, from car exhausts at the start or in the upper atmosphere behind planes. It is the same from the evaporators of nuclear plants topped with large clouds.

What can be said from these facts in relation to ice loss and climate perturbations? Nothing if the anthropogenic heat energy is negligible except calling on the effect of anthropogenic greenhouse gas. This is what has been done universally, so far, to the chagrin of climate-sceptic people. However, AHR is less and less regarded as negligible. Today some scientists are more and more interested to the role that Anthropogenic Heat Release (AHR) may play relative to climate changes and global warming, as emphasized before.

ANTHROPOGENIC HEAT RELEASE ESTIMATE

A recent article recalled the historical evolution and proposed a novel method based on a new algorithm to provide an estimate of global AHR from data on urban zones with emphasis on the limits of the approach [START_REF] Yang | Data Descriptor: A new global anthropogenic heat estimation based on high-resolution nighttime light data[END_REF]. AHR can hardly be consistently quantified because each source of energy is particular, and each application has its own characteristics in terms of work and heat. So far, local thermal data and calculations have been used mostly in relation to the climate change and sea level rise [START_REF] Chen | Exploring the possible effect of anthropogenic heat release due to global energy consumption upon global climate: a climate model study[END_REF][START_REF] He | Impact of the anthropogenic heat release on the energy balance of land-atmosphere system[END_REF][START_REF] Yang | Data Descriptor: A new global anthropogenic heat estimation based on high-resolution nighttime light data[END_REF]. Another means to estimate AHR is consideration of AHR as a fraction of the global energy produced annually from the different sources homogenized by conversion in Tonnes of Oil Equivalent (Toe). Table 1 shows data on the global energy produced over the 1900 -2018 period of time obtained from different sources [START_REF]Consommation mondiale d'énergie 1800-2000 : les résultats[END_REF][17][18][19][20].

According to Table 1, the increase in converted global energy was c.a. 100% between 1900 and 1950, 500% between 1950 and 2000, and c.a. 150 % in 18 years from 2000 to 2018-2019. The problem is now the evaluation of AHR from such global data that includes energies exploited as work and as heat (direct production) to which residual heat from work is to be added. For instance, cars or trains are using energy to move (work) but part of it is released as heat depending on the yield in work. In addition, these machines also release part of the kinetic (work) energy when they brake (brakes heats up) [START_REF] Manowska | The Importance of Heat Emission Caused by Global Energy Production in Terms of Climate Impact[END_REF]. Therefore, only estimation of AHR as part of the global produced energy can be done reasonably.

Whereas the scientific literature is silent relative to global data on energy production and consumption, estimations were found in official reports providing information on global energy consumption [18] that is smaller but very close to the global primary energy production [19]. To estimate the global anthropogenic heat released over the 1994 -2017 period selected for comparison with ice loss, global energy data from [19] were selected because they were converted in MToe according to conversion factor specific of each fossil source and, in the particular case of electricity, using the respective yields of production plants. The converted total energy consumed during the 1994 -2017 reference period was 268,400 MToe, an estimate corresponding to c.a. 11.2 ZJ heat energy on the basis of oil combustion that produces 333.55 kJ/kg heat energy. This rough estimate gives an idea of the maximum value of AHR which is rather close to the 9.34 Zj estimated to melt lost ice over the same period. Taking into account the energy used to produce work estimated as 40% of the total energy [START_REF] Manowska | The Importance of Heat Emission Caused by Global Energy Production in Terms of Climate Impact[END_REF], the minimum of AHR is c.a. 6.7 ZJ. It is important to note that the heat from more frequent and intense forest combustion (from humans or from wildfire) is not included. Therefore, one can conclude that AHR was large enough to have caused the melting of all or at least of a large part of the ice lost over the selected period of time. a) Converted in Zj from data in Mtoe from [START_REF]Consommation mondiale d'énergie 1800-2000 : les résultats[END_REF] using the 1 Mtoe = 4.18 x 10 10 j equivalence b) In Z j From [19] Whereas the scientific literature is silent relative to global data on energy production and consumption, estimations were found in official reports providing information on global energy consumption [18] that is smaller but very close to the global primary energy production [19]. To estimate the global anthropogenic heat released over the 1994 -2017 period selected for comparison with ice loss, global energy data from [19] were selected because they were converted in MToe according to conversion factor specific of each fossil source and, in the particular case of electricity, using the respective yields of production plants. The converted total energy consumed during the 1994 -2017 reference period was 268,400 MToe, an estimate corresponding to c.a. 11.2 ZJ heat energy on the basis of oil combustion that produces 333.55 kJ/kg heat energy. Taking into account the energy used to produce work as 40% of the total energy [START_REF] Manowska | The Importance of Heat Emission Caused by Global Energy Production in Terms of Climate Impact[END_REF], the minimum of AHR is thus 60% of the global exploited energy c.a. 6.7 ZJ. It is important to note that the heat generated by the more frequent and intense forest combustion and by volcanos is not included. Therefore, one can conclude that AHR was large enough to have caused the melting of all or at least of a large part of the ice lost over the selected period of time.

WHAT ABOUT CLIMATE PERTURBATIONS?

In the past, the number of humans on Earth was small and AHR was negligible. Only the Sun heated the planet with ice melting and reformation, atmosphere and ocean heating over summers and winters alternately in the northern and southern hemispheres, this including effects of greenhouse gas. Today, the anthropogenic heat diffused in the environment comes in addition. It increases rapidly and complements the Sun heating even if its contribution estimated as 0.0163 % of the contribution due to the huge solar energy supply is very small [START_REF] Manowska | The Importance of Heat Emission Caused by Global Energy Production in Terms of Climate Impact[END_REF]. From a thermodynamic viewpoint, anthropogenic heat affects ice ↔ liquid water, liquid water ↔ vapor (cloudiness, rainfall) equilibria that are theoretical sources of temperature constancy, the latter depending on the presence of solutes like salt in sea water [START_REF] Salhotra | Effect of Salinity and Ionic Composition on Evaporation: Analysis of Dead Sea Evaporation Pans[END_REF] These interdependent phase equilibria shift in one direction or the other depending on the amount of cold or heat to be managed. Theoretically, the global temperature should remain balanced. However, the Earth is very large and complex, and it is submitted to chaos. What are observed locally are temperature wells and peaks, formations and disappearances of clouds, floods and droughts, etc. Basically, the corresponding opposite thermal effects should be balanced through water evaporation from warm oceans and condensation in the cold upper atmosphere in association with ice melting and reformation. This is not the case because these fluctuations are far from those scientists are used to play with in a laboratory. Global averaging is impossible because of the relative slowness's of some equilibria evolutions and of turbulences in air and water (atmospheric pressure, high winds, heavy rainfalls, hurricanes, oceanic streams Labrador and Gulf stream, Niño and Niña, summer and winter, etc.). In contrast, solid ices are not dramatically perturbed by turbulences though their melting depends on them. It is therefore preferable to monitor the annual ice imbalance (in mass and not in surface) to try predicting the evolution of the planet climatic environment on the basis of thermodynamic phenomena. Whether the thermal energy to be absorbed comes from an excess of greenhouse effect or from the anthropogenic thermal energy, or from both, the trend is clear: on continuous heating the buffering effect of ice melting will be progressively transferred to the buffering effect of evaporation-condensation transitions involving water.

In summary, the preceding analysis leads to consider that AHR is absorbed by water interphase exchanges, an absorption that may explain the far-fromequilibrium slight increases in air and ocean temperatures detected so far. According to this logic, anthropogenic thermal energies transferred via atmosphere and oceanic water turbulences are sooner or later going to cause ice melting, something which is predominantly observed today. With more thermal energy to transfer turbulences that normally handle solar heat (hurricanes, thunderstorms, tornadoes, oceanic movements) should increase in strength and frequency locally without affecting importantly and permanently the global oceanic and atmospheric temperatures. There are already climatic signs in this direction [START_REF] Buis | How Climate Change May Be Impacting Storms Over Earth's Tropical Oceans, NASA Global climate Signs, Vital sign of the planet, Blog[END_REF]. Furthermore, ice loss is predominant in the northern hemisphere relative to the southern one in agreement with greater production and consumption of energy in the northern hemisphere [20]. Therefore, the few tenth of a degree Celsius and the few mm raises of atmospheric temperature and ocean level reported respectively so far may be another version of the half-full or halfempty bottle ambiguity, meaning that small increases may be viewed or not as beginning of dramatic deviations. This ambiguity fuels the polemics relative to climate evolution. It is important to note that anthropogenic CO 2, is indirectly related to thermal energy production via combustion and thus to AHR.

In the far future, when all global ice is melted, the absorption of anthropogenic heat will be supported by the sole back and forth evolution of water evaporationcondensation equilibria which will evolve towards the formation of more and thicker clouds. The resulting screen will reflect more and more the solar energy and thus will cause surface cooling of the Earth with, at the end of the process, reformation of the ice on the planet as it was in the distant past [23]. Cumulated anthropogenic energy diffusion will result in shortening the time scale of the evolution that, fortunately, remains of the order of thousands of years presently.

IF THIS IS THE FUTURE, WHAT SHOULD BE DONE?

If the global anthropogenic heat energy is source of ice loss and climate perturbations as suggested before, replacing the fossil sources by other sources of energy to keep the global energy consumption growing without CO 2 production may appear like a plaster cast on a wooden leg. As a matter of fact, the Earth suffers of a kind of cancer and the tumor is humanity because of a quasiexponential growth of population and a bulimia of energy whose negative effects on the planet go get worse if nothing is done. The treatment may be a reduction of the anthropogenic CO 2 that is connected to the demand in energies but, according to the present approach, it is the origin of the harm (the total anthropogenic heat energy dissipated in the environment) and the excessive demand of energy that have to be treated. To repel such evolution, the economy will have to be curbed in order to reduce the production of goods and of energy-consuming means needed today to provide remunerative work and to satisfy the lure of profit. Consequences are well discussed in a recent newspaper article [START_REF] Bardeen | On transient climate change at the Cretaceous-Paleogene boundary due to atmospheric soot injections[END_REF]. Greenhouse effect or not, it appears necessary to act without waiting for Nature to limit the human population and its worship of consumption otherwise increasing anthropogenic heat might lead to humanity disappearance as it may have been for dinosaurs in the distant past [START_REF] Chiarenza | Asteroid impact, not volcanism, caused the end-Cretaceous dinosaur extinction[END_REF]. After the anterior historical pandemics, the newly appeared SARS-CoV-2 corona virus may be a good example how Nature herself can proceed. In a close future, the buffering effects of ice melting, and of the evaporation-condensation of ocean and atmospheric water should continue to keep ocean and atmosphere temperatures globally stable even if enhanced local fluctuations are observed. It is probably a matter of millennia but it is better to anticipate fighting AHR. Despite the lack of consistent data at the global level, all partial data available on Arctic, sea ice, Antarctic and land ice losses [START_REF] Slater | Modern Records from Scripps Institution of Oceanography, CDIAC, Review Article: Earth's ice imbalance[END_REF] and on global energy production [19], have all increased between 2000 and 2014 whereas the atmospheric temperature remained rather stable with no more than a slight increase during the last years [START_REF]Global Temperature Report for 2018[END_REF].

CONCLUSIONS

Taking into account chemistry and thermodynamics fundamentals combined with global data published in reports led to the conclusion that annual AHR was large enough to justify ice losses observed so far. Complementary or alternative to the greenhouse effect of the anthropogenic surplus of CO 2 in the atmosphere, the heat balancing role assigned to thermodynamic exchanges and to equilibria of water phase transitions led to propose maintenance rather than increase of global oceanic level and atmospheric temperatures in the future. It also suggested that turbulences should be increased with local consequences worsened in frequency and intensity. The Sun governed the climate for billions of years. The novelty is that during the last hundred and fifty years, humanity has been freeing increasing parts of the huge heat energy stored as fossil or radioactive matters. Coming in addition to the action of the Sun energy on the climate, AHR might alter the climate ups and downs evolutions in force for billions of years if it continues to grow over the next years. The emphasized trends are not proofs but a few years should be enough to confirm or refute the roles assigned to thermodynamics and physical phase-transfer equilibria, especially if annual ice imbalance progresses while the sources of anthropogenic CO 2 are driven down.

Table 1 :

 1 Evolution of the estimated from the global annual primary energy deduced from main sources of energy converted in zeta Joules (10 21 J) when available in millions of equivalent of oil (MToe).

	Year Coal	Oil	Natural	Biomass Electricity Renewable Total
			gas
	1900 480	25	5	580		1,100
						0.046
						a)
	1950 955	505	153	545		2,158
						0.090
						a)
	2000 2,116 3,542	2,206	465	1,096	9,242
						0.394
						b)
	2018 0.158 0.191	0.139		0.061	0.026	0.576
						b)
	2019 0.158 0.193	0.141		0.073	0.029	0.584
						b)