Alexandre Carpentier
email: alexandre.carpentier@univ-rennes1.fr

Serena Como

Christine Dupuy

Christel Lefrançois

Carpentier A 1♯

Feeding ecology of Liza spp. in a tidal flat: Evidence of the importance of primary production (biofilm) and associated meiofauna

Keywords: Grey mullets, Feeding ecology, Mudflat, Microphytobenthos, Meiofauna

Introduction

Tidal flats represent a key system in the network of ecosystems at the continent-ocean interface. Biofilm, formed by microphytobenthos and bacteria, confers a high productivity to tidal flats (see [START_REF] Heip | Production and consumption of biological particles in temperate tidal estuaries[END_REF] for a review). The functioning of tidal flats is now well described, especially food web organization using carbon flow models (e.g., [START_REF] Degré | Comparative analysis of the food webs of two intertidal mudflats during two seasons using inverse modelling: Aiguillon Cove and Brouage Mudflat, France[END_REF][START_REF] Leguerrier | Numerical analysis of the food web of an intertidal mudflat ecosystem on the Atlantic coast of France[END_REF][START_REF] Leguerrier | Modelling the impact of oyster culture on a mudflat food web in Marennes-Oléron Bay (France)[END_REF][START_REF] Van Oevelen | Carbon flows through a benthic food web: Integrating biomass, isotope and tracer data[END_REF]. In contrast, the role of biofilm production and associated primary consumers in the ecosystem remains less well known. To integrate the ecological functioning of tidal flat systems into a global flux scheme, it is indeed necessary to describe if and how primary production and associated primary consumers are integrated into the ecosystem and potentially exported to adjacent areas (e.g., subtidal waters) [START_REF] Degré | Comparative analysis of the food webs of two intertidal mudflats during two seasons using inverse modelling: Aiguillon Cove and Brouage Mudflat, France[END_REF]. If biofilm consumption by benthic suspension-and deposit-feeders (see Pascal et al., 2008aPascal et al., , 2008bPascal et al., , 2008c[START_REF] Pascal | Seasonal variation in consumption of benthic bacteria by meio-and macrofauna in an intertidal mudflat[END_REF] has been greatly described, less is known about the role of vertebrates such as fishes or birds (see Bocher et al., this issue for birds).

The present study aimed to better understand how fish exploit biofilm in tidal flats and, conversely, what functions fish could have in such an ecosystem. Probably due to sampling difficulties, studies dealing with biofilm consumption by fish have focused on salt marshes (e.g., [START_REF] Laffaille | Can thin-lipped mullet directly exploit the primary and detritic production of European macrotidal salt marshes?[END_REF][START_REF] Lebreton | Trophic ecology of mullets during their spring migration in a European saltmarsh: A stable isotope study[END_REF] whereas tidal flats are rarely investigated (but see [START_REF] Almeida | Feeding ecology of Liza ramada (Risso, 1810) (Pisces, Mugilidae) in a south-western estuary of Portugal[END_REF]. We focused on mugilids, unique fish species in temperate regions able to consume biofilm. Mugilids are very abundant in coastal areas and occupy a large variety of habitats (e.g., [START_REF] Almeida | Feeding ecology of Liza ramada (Risso, 1810) (Pisces, Mugilidae) in a south-western estuary of Portugal[END_REF]Bruslé, 1981a;[START_REF] Laffaille | Composition du peuplement piscicole d'un petit estuaire anthropisé (le Couesnon, France)[END_REF][START_REF] Laffaille | Can thin-lipped mullet directly exploit the primary and detritic production of European macrotidal salt marshes?[END_REF][START_REF] Odum | Utilization of the direct grazing and plant detritus food chains by the striped mullet Mugil cephalus[END_REF]. This success may be due to unusual feeding behavior and diet [START_REF] Almeida | Feeding ecology of Liza ramada (Risso, 1810) (Pisces, Mugilidae) in a south-western estuary of Portugal[END_REF], combined with high salt tolerance in numerous species, including Liza aurata and Liza ramada (hereafter called grey mullets) [START_REF] Cardona | Juvenile bottlenecks and salinity shape grey mullet assemblages in Mediterranean estuaries[END_REF][START_REF] Daverat | Colonisation tactics of three temperate catadromous species, eel Anguilla anguilla, mullet Liza ramada and flounder Platichthys flesus, revealed by Bayesian multielemenal otolith microchemistry approach[END_REF]. Because they have a highly adapted digestive tract (e.g., a protractile and thin mouth with developed lips, specialized gill rakers, and a gizzard [START_REF] Thomson | The grey mullets[END_REF]), grey mullets are among the rare fish species able to graze biofilms on a variety of supports such as rocks and artificial items (pontoons, buoys, bridge pillars, reefs), but mainly tidal flats and salt marshes. Grazing by mullets could consequently represent an important role for primary production in intertidal mudflats [START_REF] Almeida | Feeding ecology of Liza ramada (Risso, 1810) (Pisces, Mugilidae) in a south-western estuary of Portugal[END_REF], and also a way of exchange between intertidal and subtidal areas [START_REF] Laffaille | Role of fish communities in particulate organic matter fluxes between salt marshes and coastal marine waters in the Mont Saint-Michel Bay[END_REF]. Because they appear very opportunistic and until recently most studies used only visual examination of stomach content, various terms have been used to describe grey mullets' diets. They can be based on the size of particles, such as "microbenthos and meiobenthos feeder" [START_REF] Hickling | A contribution to the natural history of the English grey mullets (Pisces, Mugilidae)[END_REF] or "benthic microphagous omnivore" [START_REF] Blaber | The feeding ecology of juvenile mullet (Mugilidae) in south-east African estuaries[END_REF], or based on the location of exploited resources, such as "interface feeder" [START_REF] Odum | Utilization of the direct grazing and plant detritus food chains by the striped mullet Mugil cephalus[END_REF] or "limno-benthophagous" [START_REF] Laffaille | Can thin-lipped mullet directly exploit the primary and detritic production of European macrotidal salt marshes?[END_REF][START_REF] Lebreton | Trophic ecology of mullets during their spring migration in a European saltmarsh: A stable isotope study[END_REF]. For the same reasons, grey mullets have also been classified in a wide variety of trophic positions including herbivorous, omnivorous, plankton feeders, or micro-crustacean predators (Bruslé, 1981a). Indeed, it has been proven that many species of grey mullets ingest a great proportion of microphytobenthos (e.g., [START_REF] Laffaille | Role of fish communities in particulate organic matter fluxes between salt marshes and coastal marine waters in the Mont Saint-Michel Bay[END_REF], and also small benthic grazers such as copepods, foraminifers, nematodes, and polychaetes [START_REF] Cardona | Non-competitive coexistence between Mediterranean grey mullet (Osteichthyes, Mugilidae): evidences from seasonal changes in food availability, niche breadth and trophic overlap[END_REF][START_REF] Ferrari | Feeding habits of juvenile stages of Sparus auratus L., Dicentrarchus labrax L. and Mugilidae in a brackish embayment of the Po River Delta[END_REF][START_REF] Laffaille | Role of fish communities in particulate organic matter fluxes between salt marshes and coastal marine waters in the Mont Saint-Michel Bay[END_REF]. Nevertheless, to our knowledge, no studies occur on the prevalence of the whole diversity of biofilm components in mullet diets, especially for the main taxa of meiofauna. Except for younger pelagic zooplanktonophagous stages [START_REF] Ferrari | Feeding habits of juvenile stages of Sparus auratus L., Dicentrarchus labrax L. and Mugilidae in a brackish embayment of the Po River Delta[END_REF]Chieregato, 1981, Lebreton et al., 2011), it also remains unknown what exactly grey mullets assimilate from ingested prey. A recent investigation of stable isotopic ratios from salt marsh food webs placed grey mullets at a higher trophic position than previously described [START_REF] Lebreton | Trophic ecology of mullets during their spring migration in a European saltmarsh: A stable isotope study[END_REF][START_REF] Vinagre | Isotopes reveal fluctuation in trophic levels of estuarine organisms, in space and time[END_REF], with grey mullets being able to assimilate significant amounts of secondary consumers from the biofilm, in particular nematodes [START_REF] Lebreton | Trophic ecology of mullets during their spring migration in a European saltmarsh: A stable isotope study[END_REF].

In light of these considerations and in the context of the tidal flat functioning in terms of the role of primary production, we investigated the feeding ecology and in particular the diet of adult mullets feeding in a natural tidal flat. We first explored, through the vacuity of their digestive tracts, the potential for material transport by mullet between subtidal and intertidal areas according to their tidal migrations. We then compared diet diversity in stomach contents and indices of what remains in feces with available food items in the biofilm. This instantaneous view was coupled with analyses of the natural isotopic ratios of the main components of the tidal flat food web, including mullets. From these investigations, we discuss a global perspective on the role of biofilm and associated meiofauna, and by extension tidal flats, for grey mullets and, conversely, the potential role of mullets in the global functioning of tidal flats.

Material and methods

Study site

Sampling was carried out in 2008 in a tidal flat called Brouage, the site of the VASIREMI ANR French program, in the eastern part of Marennes-Oléron Bay, located in the middle of the Atlantic coast of France. The surface of Marennes-Oléron Bay is 150 km 2 [START_REF] Pouliquen | Etude minéralogique et géochimique des sédiments du littoral vendéocharentais de la vasière Ouest-Gironde (France) : application à la connaissance de l'origine et à la dynamique des vases dans la baie de Marennes-Oléron[END_REF], of which about 60% is exposed during spring low tide. This is a macrotidal bay in which well-mixed waters are often highly turbid because of Charente River inputs and the resuspension of sediment by currents and waves. A large mudflat about 3-4 km in width extends for more than 10 km from north to south, constituting a large silty-muddy flat of about 40 km 2 mainly bordered by a sand beach. Meteorological conditions exhibit a strong seasonality typical of a temperate climate. Details of numerous benthic organisms and processes are available in [START_REF] Leguerrier | Numerical analysis of the food web of an intertidal mudflat ecosystem on the Atlantic coast of France[END_REF][START_REF] Leguerrier | Modelling the impact of oyster culture on a mudflat food web in Marennes-Oléron Bay (France)[END_REF] and [START_REF] Degré | Comparative analysis of the food webs of two intertidal mudflats during two seasons using inverse modelling: Aiguillon Cove and Brouage Mudflat, France[END_REF].

Fish sampling

Fish were sampled in May, July, and September 2008 using 4 50-m gill nets (40-mm and 25mm mesh size) to catch fish from 20 to 60 cm in length. One combination of 2 nets was set at ebb tide and a second set later from a boat at the high water slack. Nets were anchored in the mud to avoid being swept away by the flood tide. The first combination of nets was hauled in just before the high water slack to avoid capturing fish leaving the tidal flat. The second combination of nets was hauled in about 3 h after the high water slack in order to catch fish as they left the flat. Just after capture, feces, when available, were sampled by squeezing the belly of each individual and then conserved individually for further laboratory analyses in filtered seawater to prevent any contamination by other organisms. Fish were deep-frozen (-20°C) at the laboratory within 4 h after capture until analysis.

Laboratory

Stomach vacuity (percentage of individuals with an empty stomach) was compared between flood and ebb tide for all sampling months (n = 52 fish caught). Stomach content and feces analyses (meiofaunal taxa densities, viability of foraminifers after digestion process, chlorophyll a concentration, and %POM estimates, see below for details) were conducted over only 1 season because of strong variability in captures according to month and tide.

Because of the small number of fish caught with a full stomach and feces in May (n = 4) and July (n = 11), we opted to focus on fish caught in September (n = 21 fish, with n = 21 for stomach contents and n = 10 feces). Feces and samples of stomach contents were analyzed under a stereomicroscope (×20) to check for occurrences and densities of common meiofaunal taxa, expressed in numbers of individuals per g of fresh stomach content or feces weight, accordingly. Both feces and stomach content were weighted before analyzing the content.

Densities of meiofaunal taxa in the biofilm (n = 42 samples) from Brouage mudflat in July 2008 were also included in analyses. 70% alcohol fixed sediment cores (above 1 st cm depth of a 15-cm diameter corer) were sieved through a 50-μm mesh and meiofauna taxa were then counted under a stereomicroscope (Orvain et al., unpublished data). Note that what is called "biofilm" for prey density comparison corresponded to the first cm of the upper layer of sediment and was in fact a mix of mud, biofilm, and associated fauna. Densities were compared according to origin (biofilm, stomach content, or feces) by a set of one-way analyses of variance (ANOVA). To check for the viability of foraminifers after the digestion process, shells found in feces (n = 10) were placed for 24 h in a seawater solution and regularly examined under a stereomicroscope (×20). If no pseudopodia emission occurred within 24 h, foraminifers were considered dead. To test for the ingestion and digestion of microphytobenthos, chlorophyll a concentration, a proxy of microphytobenthos, was estimated both in stomach contents (n = 21) and feces (n = 10) from fish caught in September and compared using a t-test. To explore the efficiency of mullets in concentrating particulate organic matter (POM), the percentage of POM (%POM) was also assessed in the stomach contents of mullets caught in September (n = 21) by comparing stomach content weight after cremation (SWC) (at 480°C for 48 h) and stomach content weight after desiccation (SWD) (at 50°C for 48 h): %POM = [1 -(SWC/SWD)] × 100.

It is well known that carbon and nitrogen turnover is much faster in the liver than in muscles [START_REF] Guelinckx | Changes in δ 13 C and δ 15 N in different tissues of juvenile sand goby Pomatoschistus minutus: a laboratory diet-switch experiment[END_REF][START_REF] Macavoy | Isotopic turnover in aquatic predators: quantifying the exploitation of migratory prey[END_REF]. For example, in fish livers nitrogen and carbon isotopic compositions are characteristic of the food consumed within a few weeks before capture [START_REF] Logan | Turnover rates of nitrogen stable isotopes in the salt marsh mummichog, Fundulus heteroclitus, following a laboratory diet switch[END_REF][START_REF] Macneil | Variable uptake and elimination of stable nitrogen isotopes between tissues in fish[END_REF] while those of muscles indicate the average diets of adult fish within a few months before capture. Therefore, samples of liver and muscle tissues were collected (n = 52; all months) to unravel the recent individual feeding histories of mullets dwelling in the tidal mudflats. All samples were freeze-dried and ground using a ball mill. No delipidation was performed on samples since no significant effect on isotope values was found during preliminary tests (cyclohexane treatment according to De [START_REF] De Niro | Mechanism of carbon fractionation associated with lipid synthesis[END_REF]. The nitrogen and carbon isotopic compositions in liver and muscle tissues of mullet were determined using EA-IRMS (Isoprime, Micromass, UK). The carbon and nitrogen isotope ratios are expressed in the delta notation δ 13 C and δ 15 N, where: δX = [(R Sample /R Reference ) -1] × 1000, where X = δ 13 C or δ 15 N and R is the ratio 13 C: 12 C or 15 N: 14 N in the sample and in the reference material. Results are referred to Vienna Pee Dee Belemnite (VPDB) for C and to atmospheric nitrogen for N and expressed in units of ‰ ± standard deviation (sd). Fish isotopic signatures were compared according to month and tissue (twoway ANOVAs) and also with signatures of food sources and main primary sources of C from freshly sampled materials. Most source data were reported by Bocher et al. (this issue, and unpublished data) and were sampled in 2008 in Marennes-Oléron Bay including seasonal variability (4 seasons, except for microphytobenthos that was not sampled in the autumn). It

Results

A total of 52 grey mullets were captured between May and September 2008 (Table 1).

Their sizes ranged from 265 to 410 mm (mean and standard error of 340.17 ± 4.94 mm) and their sex ratio was constant (50/50) throughout the sampling period. In all sampling periods, the stomachs of fish caught during flood tide contained significantly less material (mud and biofilm, expressed as percentage of fish biomass without stomach content) than those leaving the mudflat during ebb tide (4.74 ± 0.88% and 11.03 ± 0.58% for fish caught during flood and ebb tide, respectively, t = -4.63, p < 0.001). The proportion of fish with a totally empty stomach was high (62%) during flood tide and 0% during ebb tide.

Except for foraminifers, there was a significant variability in the density of the main taxa of meiofauna between biofilm (n = 42), stomach contents (n = 21), and feces (n = 10) (F 2, 69 varied from 3.64 to 49.95, p < 0.05 for nematodes, copepods, ostracods, and platyhelminthes and F 2, 69 = 1.67, NS for foraminifers) (Fig. 1). Density significantly increased from biofilm to stomach contents for nematodes, copepods, and ostracods (Tukey pairwise mean differences varied from 1.12 to 100.93, p < 0.05) but decreased for platyhelminthes (pairwise mean difference = -0.715, p < 0.001). Prey concentrations increased from biofilm to stomach content by 20% for nematodes, with mean densities of 218.4 ± 6.4 and 263.0 ± 69.6 ind.g -1 (densities expressed in numbers of individuals per g of fresh biofilm or fresh total stomach content) in biofilm and stomach content, respectively; 4146% for copepods, with mean densities of 2.4 ± 0.1 and 101.9 ± 82.0 ind.•g -1 in biofilm and stomach content, respectively and 367% for ostracods, with mean densities of 0.3 ± 0.2 and 1.4 ± 1.0 ind.•g -1 in biofilm and stomach content, respectively. Conversely, there was a 60-fold decrease in platyhelminthes concentration, with mean densities of 1.2 ± 0.1 and 0.02 ± 0.02 ind.•g -1 in biofilm and stomach content, respectively. A significant density decrease occurred between stomach content and feces only for nematodes (pairwise mean difference = 251.370, p < 0.001) (Fig. 1). Compared to stomach contents, all individuals found in feces were observed partly digested (e.g., nematode remains, copepod carapaces), nematode remains being more difficult to detect compared to indigestible foraminifer shells or copepod and ostracod carapaces. Even if the proportion of dead foraminifers in the sediment is not known, there was no doubt that mullet ingest living individuals since foraminifer's are well known to be active species in mudflat's biofilm (Pascal et al., 2008a). Nevertheless, as no activity was detected for foraminifers found in feces and examined under a stereomicroscope (×20) in a seawater solution, we concluded that even if their carapace remained intact, they died during the transit and their content was probably digested. Another interesting result was the absence in stomachs of H. ulvae, a common species homogeneously distributed (pers. obs.) on the mudflat of Brouage in large densities (17,191 ± 547 ind.•m -2 , n = 168) in July 2008 (Orvain et al., unpublished data). Knowing the feeding behavior of grey mullet (grazing traces of 2 to 4 cm wide over variable length), it is obvious that they ingest some of these molluscs. This suggests that they were able to reject them before they reached the stomach. Chlorophyll a concentration was strongly different between feces and stomach content with a depletion of 74% (134,537 ± 16,181 µg.•g -1 in stomachs and 35,413 ± 8,252 µg.•g -1 in feces respectively, t = -7.121, df = 20, p < 0.001). This clearly confirms the ingestion and digestion of microphytobenthos by mullets. %POM was calculated for 21 stomach content samples from September and reached 6.79 ± 0.43%.

Although there was a significant temporal variability of δ 13 C and δ 15 N signatures, no clear seasonal pattern occurred (Fig. 2). Indeed, the δ 13 C signature was constant among the months of study but not among tissues (F 1, 86 = 26.55, p < 0.001 for tissue; F 2, 86 = 0.80, NS for month; F 2, 86 = 0.68, NS for intercept) (Fig. 2), while a significant variation was detected both among tissues and months for δ 15 N (F 1, 86 = 68.31, p < 0.001 for tissue; F 2, 86 = 4.58, p < 0.001 for month; F 2, 86 = 8.55, p < 0.001 for intercept). Interpretation of food web potential relationships are based on mean values of δ 13 C of animals being typically enriched by 1.1‰

or less per trophic level within oceanic systems (e.g., [START_REF] France | Ecosystem differences in the trophic enrichment of δ13C in aquatic food webs[END_REF][START_REF] Michener | Stable Isotopes in Ecology and Environmental Science[END_REF] and on the δ 15 N of animals being enriched on average by 3‰ compared with their diet [START_REF] Minagawa | Stepwise enrichment of δ15N along food chains: further evidence and the relation between δ15N and animal age[END_REF][START_REF] Vander Zanden | Variation in d15N and d13C trophic fractionation: implications for aquatic food web studies[END_REF][START_REF] Post | Using stable isotopes to estimate trophic position: models, methods, and assumptions[END_REF][START_REF] Maccutchan | Variation in trophic shift for stable isotope ratios of carbon, nitrogen, and sulfur[END_REF][START_REF] Caut | Caution on isotopic model use for analyses of consumer diet[END_REF]. According to those values, the signatures from mullets appeared mainly linked to nematodes and potentially H. ulvae. Those taxa probably exploit microphytobenthos as a primary source rather than SOM or POM, which exhibited too depleted δ 13 C values to be significantly consumed (δ 13 C was -15.4 ± 0.6‰, -19.4 ± 0.9‰, and -22.2 ± 1.8‰, for microphytobenthos, SOM, and POM, respectively). Since δ 13 C signature of foraminifers could suffer bias due to the absence of acidification, it remained difficult to determine the importance of that prey for mullets. Nevertheless, as for copepods, foraminifers appeared in the same range of mullet δ 15 N values, suggesting a secondary role as prey for mullets (differences between the δ 15 N of mullet liver or muscle and the δ 15 N of copepods or foraminifers ranged from -1.46 to 1.27‰).

Discussion

Functional interactions of grey mullets with tidal flat biofilm and associated meiofauna were examined using various approaches.

Quantitatively, 62% of captured fish had empty stomachs at flood tide and 100% had full stomachs during ebb tide. Moreover, nets were set at a middle distance from the tidal zone and fishes were caught within 1h after the beginning of the flood tide, so some of them had probably already begun to feed, explaining why some fish had stomach contents during flood tide. [START_REF] Laffaille | Role of fish communities in particulate organic matter fluxes between salt marshes and coastal marine waters in the Mont Saint-Michel Bay[END_REF][START_REF] Laffaille | Can thin-lipped mullet directly exploit the primary and detritic production of European macrotidal salt marshes?[END_REF] had previously checked for the vacuity of adult grey mullet stomachs (grey mullets >100 mm) in a salt marsh (Mont St Michel Bay in France).

Unlike our results, they never found fish with an empty stomach as they entered the salt marshes. Nonetheless, a higher instantaneous ration (Ir = gut content weight/body weight) indicated that mullets came to feed actively on the salt marshes. This is likely due to the higher elevation of salt marshes that are flooded for 1 or 2 hours at the end of the flood tide and the beginning of the ebb tide, when mullets have started to feed before their capture.

Similar results have been found by [START_REF] Lebreton | Trophic ecology of mullets during their spring migration in a European saltmarsh: A stable isotope study[END_REF] in Aiguillon Bay (France), where fishes were also caught in salt marshes lining the mudflat. Our results suggest that most grey mullets stay during the low tide without feeding in the subtidal area and wait for the next flood tide to reach the mudflats to forage. By extension, this proved that fish do not import anything from subtidal areas into tidal flats, which to our knowledge has never been shown before. Conversely, according to the mean biomass of stomach content (11.03 ± 0.58% of body weight), the export of materials from tidal flats to subtidal areas appeared concordant with those of [START_REF] Laffaille | Can thin-lipped mullet directly exploit the primary and detritic production of European macrotidal salt marshes?[END_REF] (8% of body weight) but with a different %POM (31.3 ± 7.6% for [START_REF] Laffaille | Can thin-lipped mullet directly exploit the primary and detritic production of European macrotidal salt marshes?[END_REF] compared to 6.79 ± 0.43% in our study). That difference in %POM most likely reflects different amounts of detritus (litter) mainly present in salt marshes compared to tidal flats where no macrophytes occur (e.g., [START_REF] Valéry | Impact of the invasive species Elymus athericus on carbon pools in a salt marsh[END_REF]. The absence of salt marshes in Brouage Bay also permitted us to confirm the major role played by tidal flat biofilms for mullets. Indeed, studies dealing with mullets feeding on biofilm mainly concerned fish caught in salt marshes lining tidal flats [START_REF] Laffaille | Role of fish communities in particulate organic matter fluxes between salt marshes and coastal marine waters in the Mont Saint-Michel Bay[END_REF][START_REF] Laffaille | Can thin-lipped mullet directly exploit the primary and detritic production of European macrotidal salt marshes?[END_REF][START_REF] Lebreton | Trophic ecology of mullets during their spring migration in a European saltmarsh: A stable isotope study[END_REF]but see Almeida, 2003) where fish concentrate in canals, making them easier to sample. It was therefore impossible to distinguish where and when fish feed during their tidal migration.

Biofilm and associated meiofauna seem consequently to act as a unique resource for those species, at least during their presence on coastal mudflats, which is probably temporary. Indeed, during their life cycle, grey mullets exhibit a set of migration strategies, including amphidromous ones [START_REF] Almeida | Estuarine movement patterns of adult thin-lipped grey mullet, Liza ramada (Risso) (Pisces, Mugilidae), observed by ultrasonic tracking[END_REF][START_REF] Almeida | Feeding ecology of Liza ramada (Risso, 1810) (Pisces, Mugilidae) in a south-western estuary of Portugal[END_REF]. If most juveniles colonize estuarine or freshwaters [START_REF] Trancart | Swimming activity responses to water current reversal support selective tidal-stream transport hypothesis in juvenile thinlip mullet Liza ramada[END_REF], adults exhibit various migration strategies notably between marine and freshwaters [START_REF] Daverat | Colonisation tactics of three temperate catadromous species, eel Anguilla anguilla, mullet Liza ramada and flounder Platichthys flesus, revealed by Bayesian multielemenal otolith microchemistry approach[END_REF]. Therefore, more studies will be necessary to conclude about the relative contribution of biofilms to the overall diet throughout the entire life cycle of mullets. Qualitatively, biofilm is a complex assemblage of primary producers associated with meiofauna and microfauna grazers. What exactly grey mullets ingest, select, and assimilate from biofilm and meiofauna grazers continues to be debated with sometimes contradictory results. Indeed, while [START_REF] Almeida | Feeding ecology of Liza ramada (Risso, 1810) (Pisces, Mugilidae) in a south-western estuary of Portugal[END_REF] suggested that mullets selectively reject particles <55 µm, a more recent study conversely observed retention of particles ranging between 20 and 55 µm [START_REF] Pedro | Granulometric selectivity in Liza ramado and potential contamination resulting from heavy metal load in feeding areas[END_REF]. It has also been proven that prey such as benthic diatoms or nematodes can be selectively ingested from sediment by the fish [START_REF] Odum | Utilization of the direct grazing and plant detritus food chains by the striped mullet Mugil cephalus[END_REF][START_REF] Guinea | Morphological and biometrical study of the gillrakers in four species of mullet[END_REF][START_REF] Pedro | Granulometric selectivity in Liza ramado and potential contamination resulting from heavy metal load in feeding areas[END_REF]. This ability to select small-sized particles is in accordance with diatom sizes reported in Brouage Bay, where the assemblage structure of benthic diatoms is characterized by the dominance of a small species, Navicula phyllepta (around 20-30 µm in length), throughout the year with a seasonal succession of secondary species, including only 1 large diatom (Gyrosigma peisonis, around 50-60 µm in length) (Dupuy et al., this issue;[START_REF] Haubois | Spatiotemporal structure of the epipelic diatom assemblage from an intertidal mudflat in Marennes-Oléron Bay, France[END_REF]. Concerning animal prey, our results appear consistent with recent evidence for the importance of meiofauna, especially nematodes, in grey mullet diets (organisms > 63 µm) [START_REF] Lebreton | Trophic ecology of mullets during their spring migration in a European saltmarsh: A stable isotope study[END_REF], which mullets seem able to concentrate. Other preys are also more or less greatly concentrated by mullets, but appear more variable in diet as suggested by their relative isotopic signatures. It was nevertheless clear that, unlike foraminifers and platyhelminthes, mullets significantly concentrate copepods and ostracods. The observed variability of abundances of those preys in stomach contents could be due to their reduced availability (compared to nematodes) in sediments, relative abundance being consistent with other studies in the same site (e.g., [START_REF] Rzeznik-Orignac | Spatio-temporal structure of the nematode assemblages of the Brouage mudflat (Marennes Oléron, France)[END_REF] found that 95% of meiofauna taxa in numbers were nematodes while copepods and ostracods counted for only 2 and 1%, respectively). One can finally hypothesize that the extreme copepod density variability in stomach contents can be due to an aggregative distribution of that prey. Note that if foraminifer shells remained intact in feces, they were probably killed during the digestion process, even if their contribution to mullet diet appeared low or non-existent both in number and based on isotopic signatures. The hypothesis of potential dispersion of foraminifers by mullets seems consequently unlikely even if such observations were still revealed for molluscs surviving fish gut passage (see [START_REF] Brown | Freshwater mollusks survive fish gut passage[END_REF].

Finally, we also found that mullets are able to reject larger preys such as H. ulvae, probably by filtration through their gill rakers, since this species was absent from mullet diets, a result that would not be obvious based on isotopic signature methods.

It appears that the mullet diet in mudflats is a mix of meiofauna and primary sources.

The balance between those different components of the diet remains relatively stable over seasons but could also explain inter-individual variability. It also depends on the ability of mullets to concentrate and, thus, filtrate what they ingest. It is likely that meiofauna contribute to the high trophic level found for mullets by [START_REF] Lebreton | Trophic ecology of mullets during their spring migration in a European saltmarsh: A stable isotope study[END_REF] and [START_REF] Vinagre | Isotopes reveal fluctuation in trophic levels of estuarine organisms, in space and time[END_REF].

Note that [START_REF] Pasquaud | Determination of fish trophic levels in an estuarine system[END_REF] found that mullets in a temperate estuarine food web remained at the lowest trophic level among all fish species. This confirms the very special feeding niche that mullets occupy and probably their success in terms of occurrence and abundance, at least in temperate waters. Finally, those results also suggested that mullet diets in tidal flats remain consistent with those of salt marshes.

One can wonder why we found such a high mineral fraction in stomach contents (up to 90%), which tends to prove that the selection efficiency for biofilm by grey mullets remains low. The size of mud particles may be too low to be rejected or too similar to those of items mullets keep (microphytobenthos). Nevertheless, this could also be due to the reduced time mullets have for feeding (mudflats are immersed for only a few hours per day depending on the tide coefficient); mullets optimize the quantity of food ingested rather than the quality. This hypothesis is partially sustained by the observed frenzy of fish during the flood (obs. pers.), some individuals feeding with half of their body out of the water and most hurrying to reach immersed mudflat parts as quickly as possible. This behavior may also be linked to the microphytobenthos behavior at flood tide. Indeed, it has been observed that microphytobenthos migrate from 3 to 5 mm down to the sediment as immersion occurs [START_REF] Herlory | Microstructure of microphytobenthic biofilm and its spatio-temporal dynamics in an intertidal mudflat (Aiguillon Bay, France)[END_REF] leading to a dilution of their concentration for mullet that feed by dragging the surface of the mud with their mouth.

Finally, if this study helped to clarify the diet and feeding behavior of grey mullets on tidal mudflats, the next question is then the role of the habitat and their resources for mullets and, conversely, the role of grey mullets in the global functioning of tidal flats. The great productivity of biofilm and the lack of competition, since grey mullets are the only fish species able to exploit it, could make temperate tidal mudflats an important habitat, especially for adult grey mullets. Indeed, sampling studies including mullets in salt marshes have found an absence of sub-adult G2 age fish (150 to 195 mm according to [START_REF] Lebreton | Trophic ecology of mullets during their spring migration in a European saltmarsh: A stable isotope study[END_REF]) (e.g., [START_REF] Laffaille | Composition du peuplement piscicole d'un petit estuaire anthropisé (le Couesnon, France)[END_REF][START_REF] Lebreton | Trophic ecology of mullets during their spring migration in a European saltmarsh: A stable isotope study[END_REF]. The mesh sizes of the nets we have used were too large to catch fish smaller than 200 mm, but the smallest fish captured was 265 mm, in accordance with the results of the previous studies. One can hypothesize that tidal flats are transitional habitats for adult individuals waiting for gonad maturation before reaching the high sea to reproduce in autumn and winter at a minimum age of 3 years old (G3) (Bruslé, 1981b). Consequently, biofilm and associated meiofauna could be considered to be a main resource for grey mullets during gonad maturation. Nevertheless, it appears necessary to study grey mullets in other habitats where adults occur (e.g., harbors and coastal areas) to explore their strategy and life history when they use different feeding resources.

In conclusion, the comprehension of the functional interaction between mullets and tidal flats is improved notably by a better understanding of material exchange between tidal flats and adjacent subtidal ecosystems. As previously suggested by modeling [START_REF] Degré | Comparative analysis of the food webs of two intertidal mudflats during two seasons using inverse modelling: Aiguillon Cove and Brouage Mudflat, France[END_REF], our results also confirmed the privileged export pathway for locally produced biofilm by grey mullets through ingestion during their tidal migration and their ability to select and concentrate some prey.

H. ulvae

Cop.

Nem.

Sept.

Sept.

July

July

Foram.

May

May POM SOM

  included microphytobenthos (n = 3), suspended organic matter (n = 20), particulate organic matter (n = 22), Hydrobia ulvae (n = 14), and nematodes (n = 17). Copepods (n = 5) and foraminifers (n = 2) isotopic values come from Pascal et al. (unpublished data) and were sampled in the spring and autumn of 2007. Note that foraminifers had not been acidified and included potential biased values in δ 13 C (reaching potentially 100%, Pascal et al., 2008a).

Figure 1 .

 1 Figure 1. Comparisons of mean densities of main meiofauna taxa (expressed in numbers of individuals per g of fresh biofilm (the first cm of the upper layer of sediment and in fact a mix of mud, biofilm, and associated fauna), stomach content, or feces weight, accordingly) between the Brouage tidal flat biofilm, grey mullet stomach contents (n = 21) and feces (n = 10). Densities were log-transformed to improve graphical representations of scarcer prey. *P < 0.05; **P < 0.01; ***P < 0.001; NS = not significant.

Figure 2 .

 2 Figure 2. Mean ± sd δ 15 N and δ 13 C of grey mullet liver and muscle according to month. Prey and primary source signatures are also reported: particulate organic matter (POM), suspended organic matter (SOM), microphytobenthos (Mpb.), foraminifers (Foram.), copepods (Cop.), Hydrobia ulvae (H. ulvae), and nematodes (Nem.). Copepod and foraminifer isotopic values come from Pascal et al. (unpublished data); all sources and other preys come from Bocher et al., this issue and unpublished data.

Fig

  Fig. 1.

Table 1 .

 1 Details of fish sampling in 2008 at Brouage mudflat according to months and tides, in numbers, mean sizes, and stomach contents (SC, expressed in standardized % of individual biomass) with standard errors (se).

	Tables
		May			July			September		TOTAL
		flood	ebb	total	flood	ebb	total	flood	ebb	total	flood	ebb
	n	2	11	13	11	4	15	3	21	24	16	36
	mean size (mm)	373.50 363.73 365.23 350.73 357.50 352.53 348.00 314.71 318.88 353.06	334.44
	se	9.50	10.20 8.69	6.62	5.58	5.04	8.00	7.39	6.89	5.15	6.58
	SC (%)	9.99	12.98 12.52 3.40	6.16	4.14	6.11	10.94 10.34 4.74	11.03
	se	6.16	0.87	1.06	0.26	1.79	0.57	1.98	0.63	0.67	0.88	0.58

Acknowledgments

We sincerely thank P. Richard for advice and help in the field, isotopic, and experimental studies, C. Fontaine and J. Lamoureux for their support of the laboratory work, P. Bocher and P.-Y. Pascal for additional data on isotopic signatures, B. Walters and anonymous reviewer for English improvement. We also thank anonymous reviewers for suggested improvements. This study was supported by the French ANR (National Research Agency) through the VASIREMI project "Trophic significance of microbial biofilms in tidal flats" (contract ANR-420 06-BLAN-0393-01).

Figure captions


Pierre-Jean Lapray

Barthélémy Heyrman

Dominique A Ginhac

Smart

A smart camera for High Dynamic Range imaging

de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

A smart camera for High Dynamic Range imaging P.J Lapray and B. Heyrman and D. Ginhac plapray@gmail.com, heybar@u-bourgogne.fr, dginhac@u-bourgogne.fr Laboratoire Le2i UMR 6306 -Université de Bourgogne Aile des Sciences de l'ingénieur 9 avenue A. Savary -BP 47870 21078 DIJON CEDEX Abstract: This paper describes the HDR-ARtiSt hardware platform, a FPGA-based architecture that can produce a real-time high dynamic range video from successive image acquisition. The hardware platform is built around a standard low dynamic range (LDR) CMOS sensor and a Virtex 5 FPGA board. Our video camera system is able to achieve a real-time video rate of 30 frames per second for a full sensor resolution.

Standard cameras capture only a fraction of the information that is visible to the human eye. This is specifically true for natural scenes including areas of low and high illumination due to transitions between sunlit and shaded areas. When capturing such a scene, many cameras are unable to store the full Dynamic Range (DR) resulting in low quality video where details are concealed in shadows or washed out by sunlight. High Dynamic Range (HDR) imaging techniques appear as a solution to overcome this issue by encoding digital video with higher than standard 24-bit RGB format, and then increasing the range of luminance that can be stored. By limiting the exposure time, the image loses lowlight detail in exchange for improved detail in bright areas. By increasing the exposure time, the image is only detailed in the dark areas because of the pixel saturation in bright areas.

A complete FPGA-based smart camera architecture is described, which produces a realtime High Dynamic Range (HDR) live video stream from multiple captures. A specific memory management unit has been defined to adjust the number of acquisitions to improve HDR quality.

This smart camera is built around a standard CMOS image sensor and a Xilinx FPGA. It embeds multiple captures, HDR processing, data display and transfer, which is an original contribution compared to the state of the art. The proposed architecture enables a real-time HDR video flow for a full sensor resolution (1.3 Mega pixels) at 60 frames per second."

Index Terms -High dynamic range, smart camera, pipeline processing, real-time systems, specific memory management core, video signal processing.


Pierre-Jean Lapray
email: plapray@gmail.com

Barthélémy Heyrman

Matthieu Rossé
email: mrosse@u-bourgogne.fr

Dominique Ginhac
email: dginhac@u-bourgogne.fr

A 1.3 megapixel FPGA-based smart camera for high dynamic range real time video

A camera is able to capture only a part of a high dynamic range scene information. The same scene can be fully perceived by the human visual system. This is true especially for real scenes where the difference in light intensity between the dark areas and bright areas is high. The imaging technique which can overcome this problem is called HDR (High Dynamic Range). It produces images from a set of multiple LDR images (Low Dynamic Range), captured with different exposure times. This technique appears as one of the most appropriate and a cheap solution to enhance the dynamic range of captured environments. We developed an FPGA-based smart camera that produces a HDR live video colour stream from three successive acquisitions. Our hardware platform is build around a standard LDR CMOS sensor and a Virtex 6 FPGA board. The hardware architecture embeds a multiple exposure control, a memory management unit, the HDR creating, and the tone mapping. Our video camera enables a real-time video at 60 frames per second for a full sensor resolution of 1, 280 × 1, 024 pixels.

I. INTRODUCTION

Conventional cameras have a limited dynamic range, much less than the human vision system. In many imaging systems, saturated zones in the dark and illuminated areas of the captured image still a problem. These limitations are due to large variations of real scene radiances, with over and under-exposed areas appeared in the single image. The sequential capture of several images with different exposure times can deal with the lack of information in extreme lightning conditions. This way is called the HDRi (High Dynamic Range imaging) system.

A. HDR imaging system

Creating an HDR image is done in three steps:

• Recover the response curve of the system,

• Blend pixels into radiance values,

• Perform Tone Mapping to display the resulting HDR images onto a standard monitor.

In an ideal configuration, create an HDR image is done by simply reducing low dynamic images in the same configuration by dividing each image by their exposure time (normalization), then by summing the pixels of the images. However, due to the presence of complex electronic circuits, most of the cameras have a non-linear processing about the transformation of the incident light. This non-linear transformation is transposed by the inverse of the response curve of the camera, noted g. This feature must be known before the estimation of the real radiance values, because it determines the relationship between the light striking the sensor and the corresponding pixel values. For most devices, the function f is specific to each system (lens + opening + sensor), and must be estimated as best accurate as possible to reconstruct the HDR image. Since 1995, several algorithms [START_REF] Mann | On being 'undigital' with digital cameras: Extending dynamic range by combining differently exposed pictures[END_REF], [START_REF] Debevec | Recovering high dynamic range radiance maps from photographs[END_REF], [START_REF] Mitsunaga | Radiometric Self Calibration[END_REF], [START_REF] Reinhard | High Dynamic Range Imaging: Acquisition, Display, and Image-Based Lighting (The Morgan Kaufmann Series in Computer Graphics)[END_REF] have emerged, to evaluate as precisely as possible the function g.

The estimation of the real radiance values can be followed by a dynamic range mapping, in order to visualize the result on an LDR display. This method is called the tone mapping and it is used to render the HDR data to match dynamic of conventional hardware display. For example, it can convert 32-bit wide pixels to 8-bit wide pixels ([0,255]). There are two types of tone mapping operators (TMO): spatially uniform TMO (i.e. global TMO) and spatially non-uniform TMO (i.e. local TMO). In our case, several algorithms seem to be implementable in real time due to fast computation capabilities, whether global or local. Following is a list of software methods (from the fastest to the slowest algorithm) whose efficiency and simplicity of the calculations are shown in the literature:

• Drago et al. [START_REF] Drago | Adaptive logarithmic mapping for displaying high contrast scenes[END_REF] (Adaptive Logarithmic Mapping For Displaying High Contrast Scenes)

• Duan et al. [START_REF] Duan | Tone-mapping high dynamic range images by novel histogram adjustment[END_REF] (Tone-mapping high dynamic range images by histogram novel Adjustment)

• Reinhard et al. [START_REF] Reinhard | Photographic tone reproduction for digital images[END_REF] (Photographic Tone Reproduction for Digital Images (global algorithm))

• Durand et al. [START_REF] Durand | Fast bilateral filtering for the display of high-dynamic-range images[END_REF] (Fast Bilateral Filtering for the Display of High-Dynamic-Range Images)

• Fattal et al. [START_REF] Raanan Fattal | Gradient domain high dynamic range compression[END_REF] (Gradient Domain High Dynamic Range Compression)

• Tumblin et al. [START_REF] Pattanaik | Timedependent visual adaptation for fast realistic image display[END_REF] (Time-dependent visual adaptation for fast realistic image display)

In this paper, we propose a HDR smart camera based on a parallel architecture dedicated to real-time HDR video content. What is new in this paper is shown through four steps. First, we capture images from the sensor with alternating three exposure times, selected by our Multiple Exposure Control (MEC). Then, we manage reading and writing operations in memory in order to have several video streams in parallel, corresponding to the different exposure times. Under a highly parallel context, we blend the three video streams together with a modified version of a HDR technique. Finally, an hardware implementation of a global tone mapping technique is performed. We will begin by describing existing works about HDR video technique in Section II. Then, in Section III, we will describe our system in detail. Finally, some experiments and results will follow this discussion in Section IV. Concluding remarks are then presented.

II. RELATED WORK

We detail here the existing hardware architecures. We limit ourselves to recent systems which can operate in real time, whether they are focused exclusively on capture, HDR creating or tone mapping. Table I summarizes these methods.

In 2012, Akyuz et al. [START_REF] Genc | Evaluation of radiometric camera response recovery methods[END_REF] developed a complete system on a GPU platform. The tasks are performed in parallel with a pipelined structure. Generating HDR and the tone mapping are done without knowing the response curve of the camera. They use the algorithm originally proposed by Debevec et al. [START_REF] Debevec | Recovering high dynamic range radiance maps from photographs[END_REF] to estimate the radiance values. Regarding to the operation of the tone mapping, it is the Reinhard et al. [START_REF] Reinhard | Photographic tone reproduction for digital images[END_REF] algorithm which has been chosen and implemented. Some results are identical compared to other methods implemented on CPU. They reach a framerate of 65 fps for producing HDR images, and 103 frames per second for performing the tone mapping. However, they do not have time to load textures on the GPU. The majority of time is spent in sending pixels to the GPU. Radiance computations and weighting have little impact on the speed calculation, and the framerate of the final system.

The most popular complete vision system is based on the Mann architecture [START_REF] Mann | Realtime hdr (high dynamic range) video for eyetap wearable computers, fpga-based seeing aids, and glasseyes (eyetaps)[END_REF]. In 2012, a welding helmet composed of two computer-controlled video cameras has been presented. The data received by these cameras are recorded line by line in an external memory SDRAM. Several FIFOs store pixels and read them simultaneously line by line. The number of FIFOs depends on the number of images used in the HDR reconstruction. A LUT containing precomputed values is used to combine multiple exposures. This LUT is inspired of the work by Ali et al. [START_REF] Ali | Comparametric image compositing: Computationally efficient high dynamic range imaging[END_REF], the estimation of radiances is done with a CCRF ("Comparametric Camera Response Function"). With this method, they are able to obtain a video with a fixed latency, and a controlled calculation (real-time) on a Xilinx Spartan-6 LX45 FPGA. Ureña et al. [START_REF] Ureña | Real-time tone mapping on gpu and fpga[END_REF] published in 2012 two tone mapping architectures, described both on GPU and FPGA. The implementations were done on a battery portable operating circuit. A new generation of tone mapping is presented in this article, rather than considering existing operators, because they require many computation time and memory. The tone mapping operator includes both local and global calculation. Typically, for the overall look, it highlights areas containing low contrasts, but can also protect areas where the contrast is well. Locally, it reduces the areas that are too bright in order to improve the image details. The overall improvement is based on the brightness histogram adaptation of each channel in the HSV colour space. On the other hand, the local enhancement is based on the retina-like technique. To summarize, the Gaussian filters, the weighting and the human visual system consideration are the main advantages of the operator. The FPGA implementation produced a video with a high frame rate, consuming little electric power, while the GPU implementation provides greater sensibility in the calculation of HDR pixels, but uses a lot of resources. The two systems can be reduced to a mobile application running on batteries.

In 2012 Guthier et al. [START_REF] Guthier | A real-time system for capturing hdr videos[END_REF] introduced an algorithm with a good HDR quality, that can be implemented with the same number of capture LDR. The choice of exposures is performed optimally selecting the better shutter speeds that will add the more useful information to contribute to the final HDR image. Their context can be real-time, by minimizing the number of catches. Basically, the exposure times are chosen so that the brightness value at a position i, j, where at least one LDR image captured has a well exposed pixel. First, a good approximation of the value radiance E is calculated taking into account the response function of the camera and a contributing function. A weighting function, also contributes to the value of the final radiance. The histogram of radiances is used to calculate a sequence of shutter speeds choosing it corresponding to and the peaks of the contribution function. A useful relationship is made between the histogram of radiance vector and the contribution that indicate potentially changes in the scene. A stability criterion is also introduced to the sequence which allows each frame to be adjusted until a stable shutter sequence is found. Finally, with this algorithm, they save capturing time and are able to reduce the number of LDR exposures without loss of quality at the end of the computation.

Ching-Te et al. [START_REF] Chiu | Real-time tone-mapping processor with integrated photographic and gradient compression using 0.13um technology on an arm soc platform[END_REF] suggests a methodology to develop a tone mapping processor optimized using an ARM SOC platform (System On Chip). Their processor evaluates both photographic compression method by Reinhard et al. [START_REF] Reinhard | Photographic tone reproduction for digital images[END_REF], and the gradient compression method by Fattal et al. [START_REF] Raanan Fattal | Gradient domain high dynamic range compression[END_REF], for different applications. The new processor can compress 1, 024 × 768 HDR images at 60 fps. The core needs 8, 1mm 2 of physical area with 0.13m TSMC technology.

Bachoo [START_REF] Bachoo | Real-time exposure fusion on a mobile computer[END_REF] developed a dedicated technical application of exposure fusion (initiated by Mertens et al. [START_REF] Tom Mertens | Exposure fusion[END_REF]), to merge a real-time 1600 × 1200 video at 20 fps using three black and white videos. They are able to control the speed of image generation, to have a constant frame rate, relative to the defined processing block size. They perform an alternative Goshtasby algorithm [START_REF] Goshtasby | Fusion of multi-exposure images[END_REF]. The implementation is done on CPU and GPU. The algorithm is divided into two parts so that the power of the CPU processing and GPU ("Graphics Processing Unit") is used wisely. The CPU perform massively sequential operations such as calculating entropy blocks. The GPU is used to merge the blocks together, operation which can be parallelized to increase execution speed of the fusing process. The speed can be increased if the video resolution is reduced or if the size of processing blocks increases. As this, a compromise between calculation speed and quality can be chosen. Nothing is said about the choice of exposure time and no method is proposed to estimate exposures. It is recorded that the use of additional exposures may produce a bottleneck in the fusing process.

III. A DEDICATED HDR SMART CAMERA

The dedicated hardware system is built around a CMOS sensor board and an evaluation board from Xilinx (see Figure 1(a)). The parallel architecture presented in this paper operates in several stages. At the first stage, an FPGA input interface receives sequentially three pixel streams (produced by the e2v sensor), and stores them to a SDRAM memory as colour frames. A Multiple Exposure Control (MEC) based on the histogram computation also operates in parallel to select the proper exposure times. It changes the sensor configuration each time an image is captured. At the same time, a memory management core reads the previous frames stored into the SDRAM, and delivers it as a three live parallel video outputs. At the third stage, the different pixel streams are combined using the Debevec et al. algorithm [START_REF] Debevec | Recovering high dynamic range radiance maps from photographs[END_REF], knowing the response curve of the imaging system and the exposure times. This stage produces a complete radiance map of the captured scene. Finally, the High Dynamic Range frame is tone mapped by the Reinhard et al. algorithm [START_REF] Reinhard | Photographic tone reproduction for digital images[END_REF] and can be displayed on a standard LCD monitor. This full process is continuously updated in order to perform a real time HDR live video at 60 fps with a 1280 × 1024-pixel resolution. Our real-time constraint is that the availability of a new HDR data from the LDR captures must not exceed a fixed latency of 1ms, guaranteeing that the HDR process is imperceptible to the viewer.

A. Multiple Exposure Control

Our camera must be automatically adapted to the illumination level, just as the human eye do. So, a best set of exposures have to be captured. But, when we perform HDR stitching, traditional auto exposure algorithms fail. We present a similar approach of a previous state of the art algorithm, adapted to our real-time hardware requirements. Our sensor is able to send us the complete image histogram. Using the histogram of each image will allow to have a real-time preview of the total range of brightness that will be recorded. Gelfand et al. [START_REF] Tico | Motion-blur-free exposure fusion[END_REF] use the FCam programmable API to capture two images, alternating short and long exposure. They require that fewer than 10% of the pixels in the images are bright for the short exposure, and require that fewer than 10% of pixels have values less than 16 for the long exposure. When the two exposures are stable, the metering is complete and they perform pseudo-HDR computation. They do not take into account future changes in light conditions in the captured scene, which could corrupt their dynamic range value. We use a similar approach to select three proper exposures ∆t L , ∆t M and ∆t H related to our scene.

Histogram comes through 64 categories, coded with 16-bit depth representation. Depending on which image is receiving (low (I L ) or high exposure (I H )) we apply these functions:

Q L = h=4 h=1 q(h) N Q H = h=64 h=60 q(h) N (1)
where Q L and Q H are respectively the proportion of pixels present on a specific part of the histogram (among N pixels which compose an image). q h is the quantity of pixel in each histogram category h. Calculation is made with the first four and the last four category histograms of images I H and I L . As output pixels are coded with 10-bit (coded between 0 to 1023), four categories correspond to a range of 64 pixel values. Then, we calculate two parameters for the two extreme exposure times like this:

δQ L/H = |Q L/H -Q L/H,req | (2)
where Q L/H,req is the required quantity of pixel for the part of histogram concerned. δQ L/H determines how far is the quantity of pixel with the desired quantity. Once we have these parameters, we can perform a series of decisions:

∆t L/M/H,t+1 ← M EC(∆t L/H,t ) (3
where thr m (minus) an thr p (plus) are the threshold values in order to have 2 levels of precision on how we will adjust the exposure values. x is an extra exposure time corresponding to the integration time of one sensor row. ∆t L/M/H,t+1 are the exposure times which will be programmed into the sensor for the next frames I L/M/H . The middle exposure time is a combination of ∆t L and ∆t H . As we work with highly parallelizable architecture, we can do estimations of the dynamic range of the scene during HDR processing. If needed, we correct the exposure times if lighting conditions have changed.

B. MMU

The use of external off-chip memories is judicious for our application that processes large amount of data and high data rates. For our case, video processing requires two frames of data to be stored (the third frame is given by the sensor). In practice, this storage is implemented using DDR3 SDRAM chip which is a part of our hardware development platform. It requires fast and efficient direct memory access logic to achieve high dynamic range video in real-time.

The sensor is able to send full-resolution images at 60 frames/s. Initialization of our specific HDR Memory Management Core is shown in Fig. 2. I L and I M are first stored in DDR3 memory. The first frame (I L ) is stored row by row W Λ λ I L , where λ indexes row number (1 <= λ <= 1024). For example W Λ 1 I L means "writing of the first row Λ1 of I L into memory". Each row write operation is followed by inter-row delay, due to horizontal sensor synchronization. For the second frame I M , the image is also stored row by row (W Λ λ I M ). This initialization step is required before the generation of the first HDR frame. We can't avoid waiting for these two first exposures. After this step, the Memory Management Core can start (see Fig. 3).

During the capture of the last frame (I H ), rows of the two previous frames stored are synchronously read from the memory during inter-frame (RΛ λ I L , RΛ λ I M ) and buffered into Block RAMs (BRAMs) while each new captured row (W Λ λ I H ) is stored in memory. It's important to notice that the design is a pure-hardware system which is processor-free and must be able to absorb a continuous pixel flow of about 80 MegaPixels per second from the sensor (called "Memory In" in Fig. 2 and in Fig. 3) while reading two other pixel flows corresponding to the two stored images (respectively called "Memory Out 1" and "Memory Out 2" in Fig. 3).

The HDR content is computed with the methods described in Sections III-C and III-D. The HDR process needs a continuous stream of pixels of three images and then can only be performed while receiving the third frame I H . Then, the process can iterate throughout the capture of the fourth frame (low exposure I ′ L ) and the readout of the second and third frame (I ′ M and I ′ H ). Finally, our memory management system is able to deliver two parallel pixel streams that have been acquired and stored into the memory and a third pixel stream directly from the sensor. With this technique, each HDR pixel only requires three memory accesses (one write and two read operations during one row interval), saving many memory access operations. The main advantages of such a technique are (1) to store only two images in memory, and (2) to avoid the waiting for the three images to compute an HDR image. A latency corresponding to 136 clock rising-edges (i.e. 1.2us for a 114M Hz system clock) is required by the system to create HDR tone mapped data (grey part of HDR output in Fig. 3) from the three captured lines. And then, it delivers an HDR video stream at 60 fps directly updated at each time the sensor sends an image.

C. HDR creating

The evaluation of the inverse of the response curve of the system g only requires the evaluation of a finite number of values (typically 1, 024 values for a 10-bit precision sensor), as depicted in the paper of Debevec et al. [START_REF] Debevec | Recovering high dynamic range radiance maps from photographs[END_REF]. These values can be preliminary evaluated from a sequence of several images, then stored in the camera, and reused further to convert pixel values. For our case, the curve g has been calculated, in a first step, using the Matlab code provided with the Debevec paper. In a second step, this curve has been stored in LUTs on the hardware platform. For recovering the HDR luminance value E ij of a particular pixel, all the available exposures of this pixel are combined using the following equation: ln

E ij = p=3 p=1 ω ′ (Z p,ij )[g(Z p,ij ) -ln ∆t p ] p=3 p=1 ω ′ (Z p,ij ) (7)
where p indexes the image number, i and j indexes pixel position and ω ′ (z) is a weighting function giving higher weight to values closer to the middle of the function:

ω ′ (z) = z -Z min for z ≤ 1 2 (Z min + Z max ) Z max -z for z > 1 2 (Z min + Z max ) (8)
where Z min and Z max values depend on the sensor output dynamic (typically 1, 024 values for a 10-bit precision sensor). Considering Z 1,ij , Z 2,ij and Z 3,ij as Z L,ij , Z M,ij and Z H,ij in a 3-frame HDR system, the overall scheme is visible in the pipeline architecture depicted in Fig. 4 Fig. 4. HDR creating using three different pixel streams.

Computation of luminance values requires the use of 32bit arithmetic operators (substractors, multipliers etc.) and transition from 10-bit to IEEE754 32-bit wide (called "Fixedto-Float" in Fig. 4). LUTs are used to store the inverse of the response curve g and make the transition from exposure time values ∆t L/M/H to neperian logarithm field.

D. Tone Mapping

Once the radiance map is recovered, HDR image pixels have to be mapped to the display range of a selected material, typically a LCD monitor. In our case, the displayable range is 2 8 values. The global part of Reinhard et al. [START_REF] Reinhard | Photographic tone reproduction for digital images[END_REF] algorithm requires one global computation: the log average luminance found in the image, calculated by:

Ēij = exp   1 N i,j ln (δ + E ij )   (9)
where E i,j is the scene luminance for pixel (i,j), N is the total number of pixels in the image. For our case, due to signal noise, we cannot have zero pixel value, so we can assume that δ = 0. The summation is only over non-zero pixels. Then, we want to map the middle grey scene luminance to the middle-grey of the displayable image. For the photographic tone reproduction operator, an approach is to scale the input data such that the log average luminance is mapped to the estimated key of the scene a, where a is a scaling constant appropriate to the illumination range of the image scene:

D ij = 255 • a Eij Ēij 1 + a Eij Ēij = 255 • 1 1 + Ēij a•Eij (10)
The tone mapping pipeline implemented is shown in Fig. 5. Frame enable permit to calculate the log average luminance each time a HDR image is receiving by the HDR creating pipeline.

IV. IMPLEMENTATION

Our work has been implemented on a Virtex-6 platform. We show the hardware implementation results in Table IV. Usually, FPGA-based image processing requires many specific devices such as SRAM memory, multi-port memory, video direct memory access, dedicated processors, and consequently, consumes many DSP blocks. This is not the case for our implementation. It consumes relatively low hardware complexity since the number of occupied slices is 6, 692 (about 17% of the device) and the number of LUTs is 16, 880 (i.e. 11% of the device). Captures of still images from the different video LDR stream are shown in Fig. 6. You can see at the same time the contributions from the different LDRs frames (Fig. 6-a, 6-b, and 6-c) in the HDR image (Fig. 6-d). As an example, we can distinguish the word "HDR" inside the lamp (high brightness), and the word "HDR" inside the tube (low brightness).

V. CONCLUSION

An HDR smart camera, with a complete hardware system from capture to display, has been designed for rendering HDR content at a 1.3-megapixel resolution and a high frame rate of 60 fps. Such a smart camera demonstrates that HDR video is feasible and exceeds other state of the art hardware platforms both in terms of resolution, speed, image quality and control. However, some effort has to be done in standardization, compression and sharing HDR data in order to provide an efficient HDR smart camera able to dynamically manage any variation in the scene. As an illustration, the multiple exposure technique can cause problems due to scene motion and generate artefacts in the resulting HDR video. In our case, our platform is not very affected with such a problem because extremely rapid scene motion does not happen in our captured scenes. This is partly due to the fact that we used a dedicated memory management core which delivers multiple videos in parallel at 60 frames per second, and that our pixel stream is continuously updated with the current frame sent by the sensor. However, in extremely rapid scene motion, real-time implementation of specific ghost removal algorithms need to be investigated in order to enhance the HDR video quality.

Fig. 1 .

 1 Fig. 1. Overview of our HDR smart camera

Fig. 3 .

 3 Fig. 3. Memory Management Core. Performing three parallel streaming videos with low (I L ), middle (I M ) and high (I H ) exposure times. The delayed HDR row output is shown after HDR and tone mapping computations (related to Section III-C and III-D.

Fig. 5 .

 5 Fig. 5. Tone mapping hardware pipeline.

Fig. 6 .

 6 Fig.6. Result of the complete system. Our Multiple Exposure Control can select the three proper exposures, and the specific memory management core permits us to display 3 bracketed images at the same time.

  Memory Management Core initialization. The sensor send sequentially low (I L ) and middle (I M ) exposure times. Writing operations into memory of each rows Λ indexed by λ of the first two frames. ∆t H,t+1 = ∆t H,t ± 1x for δQ H > thr Hm ∆t H,t ± 10x for δQ H > thr Hp (5) ∆t M,t+1 = ∆t L,t ∆t H,t

	Sensor		Low Exposure IL			Middle Exposure IM
	Memory In	W Λ1IL	W Λ2IL	...	W ΛλIL	W Λ1IM	W Λ2IM	...	W ΛλIM
	Fig. 2.

)

∆t L,t+1 = ∆t L,t ± 1x for δQ L > thr Lm ∆t L,t ± 10x for δQ L > thr Lp

(4)

TABLE II .

 II SUMMARY OF HARDWARE IMPLEMENTATION RESULTS ON THE VIRTEX-6 PLATFORM.


Guirec Querré
email: guirec.querre@univ-rennes1.fr

Thomas Calligaro

Salvador Domínguez-Bella

Serge Cassen

PIXE analyses over a long period: The case of Neolithic variscite jewels from Western Europe (5th-3th millennium BC)

Keywords: PIXE, variscite, calibration, provenance, Prehistory

teaching and research institutions in France or abroad, or from public or private research centers.

Introduction

The provenance and the circulation of variscite -a precious stone resembling turquoise with AlPO 4 .2H 2 O formula with iron traces -that was employed for ornaments of Early Neolithic to Chalcolithic periods (5 th -3 rd millennium BC) in Western Europe represent a main archeological issue (fig. 1). On one hand, many Prehistoric occupations with variscite artifacts have been excavated, and on the other several occurrences of this mineral have been located (fig. 2). The question of the provenance of the archeological variscite has motivated two research programs in Spain and France that were undertaken simultaneously and independently in the 1990. The first results obtained using LA-ICP-MS and PIXE showed that the variscite of the studied artifacts from Western France Neolithic graves were mined from Iberian deposits [1,2]. However, it was necessary to extend this work to a larger number of archeological artifacts and geological references samples to confirm this hypothesis and to establish on statistically significant grounds the origin of each bead and pendant from all archeological sites [START_REF] Querré | Circulations à longues distances de matériaux emblématiques[END_REF]. It was decided to further analyze samples from France and Spain using the transnational access to the AGLAE facility of the C2RMF because of its high analytical performance, central location and secure environment for the investigation of these precious artefacts.

The delays required to organize the transport of artifacts from museums and archaeological deposits in Spain, Portugal, United Kingdom and France to the C2RMF, to complete field missions in Western Europe variscite deposits to collect geological references from Spain, Portugal, France, Italy, England, and lastly to regularly apply to the "Call for Proposals" for the transnational access to the AGLAE facility explain the long duration of this program. Overall, 1720 analyses of major, minor and trace elements in variscite and in geostandards were carried out in thirteen runs from one to four days each distributed over 13 years, from 1999 to 2013. During this period, almost all Neolithic jewels from France and a large number of archeological artifacts from Iberian Peninsula were analyzed by PIXE. Variscite reference samples from all know ancient mines and from other geological outcrops identified in Western Europe were also analyzed.

Experimental

During that period, the AGLAE external beam line underwent experimental and spectrum processing improvements and consequently, the measuring conditions has evolve over time [START_REF] Calligaro | [END_REF]5]. Some parameters have been kept constant, such as the proton beam energy (3 MeV) and intensity (about 2 nA to avoid any beam-induced damage), the geometry (low and high energy detectors placed 45° relative to the beam axis), the filters used (a helium flux of 1-2 l/min, permanent magnets to deflect backscattered particles away from the low energy detector, 50-µm thick aluminum absorber for the high energy detector). The mean analysis time per sample was about 4 minutes and 24 chemical elements were quantified: Na, Mg, Al, Si, P, S, Cl, K, Ca, Ti, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, Ga, As, Rb, Sr, Y, Zr, Nb, U. A 5-mm 2 pellet of the international geostandard Diorite DR-N [6] was analyzed at the beginning and the end of each run, and regularly within the sequence. In addition, from 2004 onwards, a variscite archaeological bead (MeH40) coming from the archaeological site of Mane-er-Hroeck, Locmariaquer (Morbihan, France) was promoted to a standard status and was systemically analyzed. The beads and pendants were directly submitted to the beam without preparation apart from cleaning with alcohol. On the other hand, some experimental parameters have evolved during the period [START_REF] Calligaro | [END_REF]5]. The Si(Li) detectors were replaced subsequently to failures or improvements: the first Si(Li) detectors employed were from Kevex, the crystals of which were later replaced by ones from Gresham. Eventually the Si(Li) detectors were replaced by SDD detectors. All detectors featured different crystals specifications: thickness and active surface, windows technology (1-2 µm carbon absorber to block light in front of the SuperQuantum and MOXTEK thin entrance windows) and finally an ice layer buildup in front of the detector crystal. During the 1999-2005 period, the measuring strategy was to carry out single spot analyses (100-µm diameter) which was later changed to scanned area (20 µm, 500x500µm area) to better reflect the concentration of such heterogeneous samples. The spectrum treatment strategy was to process the low energy spectra with GUPIX in iterative mode with a fixed H value, forcing the concentration of main elements in oxide form to sum up to 100%. The iron value determined in this step was subsequently used to calibrate the trace elements concentrations from the high energy spectra. The filters thickness parameters were continuously adjusted. During the period of 13 years, the GUPIX program was upgraded several times (from DOS-based GUPIX to GUPIXWIN v 2.3) using incompatible parameter and data file formats.

Results and discussion

Reproducibility and reliability

Two main conclusions were deduced from the evolution of concentrations for major and minor elements obtained on 151 DR-N analyses (fig. 3). First, concentrations variations were more important before 2005 for most elements: Na, Mg, Al, Si, K, Ca and Fe. These variations are explained by the fact that the external beam is fixed and the grain size of the powder too coarse compared to the beam diameter (30-µm spot size). Indeed diorite is a multi-phased rock containing quartz, plagioclase, alkali feldspar, micas and minors minerals. After 2005, the grain effect was removed by scanning the pellet under the beam; the results obtained were then more representative of the average composition and the reproducibility was thus improved. Whereas this problem of heterogeneity exists for DR-N powder pellet, it is not the case for variscite samples. Indeed, this mineral occurs in homogeneous nodules or veins in micro-or cryptocrystalline form, with sub-micronic crystal grains much smaller than the beam size. The size of the scanned variscite area was 0.5x0.5mm. Note that the scanning was obtained exclusively by a mechanic displacement of the sample before 2012 and after, by a combination of vertical magnetic beam deflection and mechanic translation [5]. Overall, the PIXE concentration of major and minor elements obtained on the DR-N pellet varied within 5% from the recommended values. Natural variscite should exhibit a variable composition as it result from a solid solution of pure variscite [AlPO 4 .2H 2 O] and strengite [FePO 4 .2H 2 O] end-members according to Al and Fe substitutions. Stoichiometry of pure variscite is Al 2 O 3 =41.8% and P 2 O 5 =58.2% on anhydrous base and mass atomic P/Al ratio of 1.148. The substitution of Al atoms by Fe atoms induces an increase of P/Al ratio. Variscite also incorporates transition elements like Cr, V, As and its green color is generally ascribed to the presence of Cr +++ [7]. Note that important elements like P or Cr, V and As are not present in the DR-N standard and thus cannot be checked.

Let us first comment the major elements in the variscite, i.e. Al and P. When the P/Al ratio for all variscite samples is plotted as function of time (fig. 4), a variation between 1.1 and 1.5 is observed despite that the DR-N data from the same runs present a good reproducibility and reliability. In particular, three marked sequences of analyses can be noted, corresponding to the use of different detectors. This variation is probably related to the detection efficiency for P, because variscite is mainly composed P and Al in a dependent way (P 2 O 5 +Al 2 O 3 =100%) so that a small variation of P 2 O 5 will induce de facto a variation of Al 2 O 3 that will be amplified in the P/Al ratio. Two hypotheses can be proposed to explain this long-term variation: first, an instrumental effect like a change of in the low energy detector efficiency for P and/or Al (e.g. ice layer buildup or variable carbon filter thickness). Second, this effect could also derive from the spectrum processing using GUPIX, more precisely by selection of inadequate parameters in the detector description (e.g. dead layer thickness of Si(Li) detector, tailings). For example, a 1-µm dead layer of would reduce the detector efficiency for P by 20%, which would be left unnoticed in the DR-N composition. This effect is well illustrated in table 1 where analyses of the variscite bead standard (MeH40) during three periods extending over 9 years are reported. Compared to period 1, in period 2 we note a 1.4% decrease of P 2 O 5 and in period 3 a further 3% decrease that induce an apparent increase of Al 2 O 3 , while Fe 2 O 3 concentration is stable. The corresponding P/Al ratio decreases from 1.321 to 1.242 and finally to 1.176. If in the final campaign the strengite molecule is discarded (1.83% of Fe 2 O 3 ), the P/Al ratio closely approaches the value for pure variscite (P/Al=1.148). Note that this run was the first performed using SDD detectors (no dead layer) and GUPIXWIN with parameters adjusted in accordingly [5]. As for the trace element concentrations, the variations are less pronounced than for major elements, as is shown in figure 5 which depicts the evolution of Cr, V, Fe and Ga in the MeH40 variscite bead for over 9 years. This can be explained by the fact that the Fe pivot element value extracted from the major element spectrum used to normalize the trace element concentrations is less affected. The geochemical database based on the PIXE analyses of archeological and geological variscite over a period of 13 years appears to be coherent. All elements except P and Al, the two major elements of variscite, can be used to compare composition of the gemstone for provenance purposes.

Geographical references

Variscite is a rare mineral in Western Europe and the potential sources available to Neolithic people are limited (fig. 2). Three ancient exploitations are known, all located in Spain: Gavà -Can Tintorer Neolithic mines (Gavà, Barcelona), Encinasola -Pico Centeno mines (Encinasola, Huelva) and Palazuelo de las Cuevas-San Vicente de la Cabeza-El Bostal (Aliste, Zamora). All reference samples of these three ancient exploitations were collected in archaeological mining waste. Their chemical composition obtained by PIXE is probably very similar to the rocks used in the Neolithic to make jewelery. A single occurrence is known in France, Pannecé (Loire-Atlantique), discovered in 1970 in La Floquerie quarry that do not show any trace of ancient mining. Other occurrences might exist but were probably not exploited either because the deposit was too poor in variscite or yielded nodules too small to produce jewelry: Ervedosa, Deilao and Guadramil (Bragança, Portugal), Sarrabus (Cagliari, Italy). It is worth noting that several geological samples studied proved to be made not of variscite but of turquoise CuAl 6 (PO 4 ) 4 (OH) 8 •4H 2 O: Punta Corveiro (Pontevedra, Spain), Montebras (Soumans, France), St Austell (Cornwall, England). Overall, 194 PIXE analyses were performed on variscite and on a few strengite or turquoise samples from 14 localities.

In general, the composition for minor and trace elements in variscite samples from a particular deposit exhibit a correlated spread of values. This phenomenon is well known in geology by which specific petrogenetic processes in rocks induce during their formation characteristic geochemical trends that can be used as provenance fingerprints.

The ternary diagram representing chromium, vanadium and iron concentrations illustrates such fingerprints. In figure 6 is represented the values measured in several samples from the three Spanish variscite mines and from the Pannecé modern quarry (Brittany, France). The deposits from North-West Spain which comprise Palazuelos de las Cuevas and SanVincente de la Cabeza sources is characterized by a very large and correlated range of Cr and Fe concentrations whereas V appears always in low concentrations, leading the Cr/V ratio lying between 1.6 and 8. The variscite samples from Encinasola exhibit large range with important Fe concentrations and a large spread of Cr and V values, with the Cr/V ratio ranging between 1.6 to 0.2. Contrary to the two previous mines, the variscite from Can Tintorer at Gavà and from Pannecé in Brittany (France) present an homogeneous composition that explains the strong regrouping of their points in the Cr-V-Fe diagram. Conversely, Gavà samples appear almost completely deprived in Cr and V and proportionally enriched in Fe. The Pannecé deposit yields variscite samples richest in vanadium and the most depleted in chromium and iron with a Fe/Cr ratio equal to 1. On the base of three minor and trace elements, Cr, V and Fe, we could confirm that each deposit present geochemical characteristics including large variation of concentrations. Other features of trace element not discussed here, allowed us to further differentiate variscite sources: for example, high concentrations of Ca and As for Gavà samples, low Ga, high Zn concentrations for Deilao, Ervedosa and Sarrabus and high U level in El Bostal variscite.

Examples of provenance of archaeological artifacts

PIXE analyses were carried out on 851 beads or pendants from 39 archaeological sites. Archaeological sites are characterized by their localization and their dating and many variscite beads and pendants were discovered during their excavation. Their provenance could be inferred by comparison with the reference database obtained on reference samples. We present here three examples highlighting the usefulness of th Cr, V and Fe fingerprints discussed previously.

The first example deals with the dolmen Kervilor Mané Bras (La Trinité-sur-Mer, Brittany, Western France), a grave dated 4300-4000 BC of "Tombe à couloir" type located in the Carnac region, rich in megaliths [8]. A selection of 41 beads and pendants from this monument has been analyzed. The Cr, V and Fe concentrations show a large spread and overlap in the Cr-V-Fe ternary diagram, the representative points being dispersed along a line from iron pole to the centre of the triangle (fig. 7a). The Cr/V ratios vary from 0.2 to 1.6 and Fe reaches up to half of the sum of the three elements. This pattern matches the fingerprint of Encinasola deposit and never corresponds to the Pannecé deposit (fig. 6). Artefacts found in the grave of Kervilor probably come from the Encinasola prehistoric mine located in South Spain, more than 1000 km away and unexpectedly not from the Pannecé deposit located 100 km from the site (fig. 8). The second archaeological example is the Chalcolithic occupation of Leceia (Oeiras, Portugal), a fortified village located on the Tage estuary, West of Lisbon. People occupied this site during a long period corresponding to the beginning of cupper metallurgy in Portugal, but variscite jewels are dating from the Chalcolithic initial period 2800 BC [START_REF] Cardoso | Escavações do povoado fortificado pré-histórico[END_REF]. The Fe and Cr concentrations of the variscite artifacts show a large range whereas the V levels are always very low (fig. 7b). The line drawn in the Cr-V-Fe diagram appears to be very similar to that of variscite samples from Palazuelo-San Vicente mines (fig. 6). The jewels from Leceia probably come from these deposits located about 400 km to the North and surprisingly not from the Encinasola mine, distant only 200 km to the East direction (fig. 8). The third example deals with the site of Villeneuve-Tolosane/Cugnaux (France) near Toulouse, South of France dated 4,500-3,500 BC [START_REF] Vaquer | Défunts néolithiques en Toulousain[END_REF]. This characteristic Neolithic village was occupied by the first farmers of the "culture chasséenne" and provided numerous remains, among which variscite beads. Their compositions showed a high compositional homogeneity: all the representative points are grouped at the Fe pole and don't show any measurable Cr or V content (fig. 7c). This typical fingerprint matches that of variscite from Can Tintorer mine at Gavà. The source of variscite jewels is the nearest to the village, being accessible by a 100-km trip to in the north (fig. 8). These examples confirm that the determination of minor and trace element concentrations in variscite are useful for the determination of the provenance of the archaeological variscite jewels. The results obtained here contradict the conclusions of Odriozola and co-workers who analysed variscite samples from Encinasola (Pico Centeno mines) and isolated archaeological beads from south Iberian Peninsula using µ-XRF technique [11]. On one hand these authors concluded that the strongly scattered minor and trace elements composition measured within the deposit prevent deducing any information about their origin. On the other hand, they claim that the P/Al atomic ratio might reflect the paragenesis of the mineral and could constitute a fingerprint. The P/Al ratio reported in their work (P/Al=1.7) is questionable as it is much higher to what we have observed for years in hundreds of samples. In addition, such a high excess of P is hardly conceivable in a properly crystallised variscite as it can be seen in XRD and in thin section under polarizing light microscope. On the other hand, our PIXE analyses of samples from the same mines (P 2 O 5 =56% Al 2 O 3 =40 %) agree with theoretical composition and with most published analyses of variscite from Encinasola.

Conclusions

The constitution of a long-term geochemical database using PIXE is a real challenge. Because of instrumental changes among years (often related to improvement in detectors and in measurement strategies) and of the constant progress and refinement in spectrum progressing (new program releases, changes of format and parameters) data collected over a long period might exhibit virtual variations. The choice of adequate reference targets and application of systematic quality control are essential to reach proper reproducibility and the reliability. It is under these conditions that the intrinsic qualities of the PIXE technique can be reached, namely accuracy for determination of major constituents and high sensitivity for the measurement of trace element. These qualities can then be the strongest assets of the use of PIXE in archaeological studies, like in the present case the determination of the circulation of a variscite from precious ornaments of the Neolithic and Chalcolitic periods in Western Europe.

[11] Odriozola C. P., J.A. Linares-Catela b. V. Hurtado-Pérez. Journal of Archaeological Science 37 (2010) 3146-3157.

Figure 1 .

 1 Figure 1. Beads and pendants made of variscite from Neolithic graves of Brittany: Tumulus St Michel (Carnac, France) and Tumiac (Arzon, France).

Figure 2 .

 2 Figure 2. Location of Prehistoric occupations with variscite artifacts exclusively concentrated in Western Europe with Prehistoric mines and geological occurrences of the region.

Figure 3 .

 3 Figure 3. Stability of analysis of the DR-N geostandard over 14 years of PIXE analysis of variscite artifacts. Arrows indicate the change from punctual analysis to area scanning analysis.

Figure 4 .

 4 Figure 4. Evolution of P/Al ratio from archaeological and geological variscite samples over 14 years of PIXE analysis. Each group of symbol corresponds to the date of analysis specified in the bottom of the diagram.

Figure 5 .

 5 Figure 5. Stability of minor and trace element concentrations of MeH40 variscite bead from Mane er Hroeck, Locmariaquer (Brittany, France) over 9 years. Each point corresponds to one analysis -1: July 2004; 2-8: July 2005; 9-11: October 2008; 12-17: January 2009; 18-22: January 2013.

Figure 6 .

 6 Figure 6. Variscite from the 3 main Iberian prehistoric mines and Pannecé quarry in France

Figure 7 .

 7 Figure 7. Ternary diagram V-Cr-Fe for 3 different groups of variscite jewels. (a) Dolmen from Kervilor, La Trinité-sur-Mer (Brittany -France) (b) Chalcolithic occupation of Leceia, Oeiras (Lisbon-Portugal) (c) Neolithic village of Villeneuve-Tolosane (Languedoc, France).

Figure 8 .

 8 Figure 8. Location of the three archaeological sites where variscite beads come, Kervilor, Villeneuve-Tolosane, Leceia and geographical origin of the raw material proposed, respectively Encinasola, Gavà, Palazuelo.

Table captions Table 1 .

 captions1 Evolution of Al, P and Fe and P/Al ratio over 9 years obtained using PIXE of the same archaeological variscite bead (MeH40) (n: number of analyses, X: mean value and σ:

	standard deviation).

Acknowledgements

We are indebted to MM. J. Bosch, Gavà Museum (Spain), J.L. Cardosa, Lisbon University (Portugal), M.-P. Dabard, Rennes University (France), Pr B. Lasnier, Nantes University (France), C. Le Pennec, Vannes Museum (France), J. Vaquer, Toulouse University (France), E. Vigier, Carnac Museum (France) for the kind loan of geological samples and for providing the opportunity to investigate the archaeological artefacts. We acknowledge the support of November 2010 measurement campaign by the European program Charisma: project CALLAÏS. S. Domínguez-Bella acknowledges the financial support of the project HAR2008-06477-C03-02, PGE program of the Spanish Ministry of Science and Innovation in the sampling and studies on Iberian variscite.