A Douay

M Louzon

A Pelfrêne

B Pauget

F Gimbert

N Morin-Crini

F Douay

A De Vaufleury
email: annette.devaufleury@univ-fcomte.fr

Bioaccessibility of metal(loid)s in soils to humans and their bioavailability to snails: a way to associate human health and ecotoxicological risk assessment?

Keywords: bioindicators, bioaccumulation, organic matter, integrative risk assessment

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

Introduction

Human health risk assessment (HHRA) and ecotoxicological risk assessment (ERA) of contaminated soils are challenging because they involve a mixture of scientific, regulatory and budgetary requirements. In the current context of contaminated soils [START_REF] Ec | Soil threats in Europe. Status, methods, drivers and effects on ecosystem services[END_REF], HHRA and ERA are often conducted independently and are mainly based on the measurement of total contaminant concentrations [START_REF] Meem | Méthodologie nationale de gestion des sites et sols pollués[END_REF][START_REF] Song | Evaluation methods for assessing effectiveness of in situ remediation of soil and sediment contaminated with organic pollutants and heavy metals[END_REF]. Considering that the total amount of a contaminant in the soil is mobile and available for organisms could lead to discrepancies between the real and estimated mobility of contaminants. Indeed, contaminants could be highly mobile in slightly contaminated soil and relatively low mobile in highly contaminated soil. To prevent misinterpretation, risk assessment of contaminated soils should consider bioavailable concentrations, which may be modulated by the physicochemical properties of soils (e.g., pH, clays content, and organic matter (OM) content) [START_REF] Allen | Bioavailability of metals in terrestrial ecosystems: importance of portioning for bioavailability to invertebrates, microbes, and plants[END_REF][START_REF] Pauget | Use of chemical methods to assess Cd and Pb bioavailability to the snail Cantareus aspersus: A first attempt taking into account soil characteristics[END_REF][START_REF] Pauget | Ranking field site management priorities according to their metal transfer to snails[END_REF][START_REF]Soil Quality. Procedure for site-specific ecological risk assessment of soil contamination (soil quality TRIAD approach)[END_REF]. In this context, bioavailability assessment based on oral bioaccessibility (i.e., the fraction of an ingested contaminant that is soluble in digestive fluids) to humans and bioaccumulation by soil organisms are relevant surrogates for evaluating the exposure of organisms to contaminants in soils [START_REF]Soil Quality. Requirements and guidance for the selection and application of methods for the assessment of bioavailability of contaminants in soil and soil materials[END_REF]. In addition, assessment of organism exposure can be required for polluted soil management to determine the cause-and-effect relationships (toxicological bioavailability) [START_REF]Soil Quality. Procedure for site-specific ecological risk assessment of soil contamination (soil quality TRIAD approach)[END_REF][START_REF]Soil Quality. Requirements and guidance for the selection and application of methods for the assessment of bioavailability of contaminants in soil and soil materials[END_REF]. The oral bioaccessibility of contaminants in soils can be assessed with in vitro assays [START_REF] Ruby | Estimation of lead and arsenic bioavailability using a physiologically based extraction test[END_REF][START_REF] Oomen | Comparison of five in vitro digestion models to study the bioaccessibility of soil contaminants[END_REF], such as the unified bioaccessibility method (UBM) for arsenic (As), cadmium (Cd) and lead (Pb) [START_REF] Wragg | An inter-laboratory trial of the unified BARGE bioaccessibility method for arsenic, cadmium and lead in soil[END_REF][START_REF] Denys | In vivo validation of the unified BARGE method to assess the bioaccessibility of arsenic, antimony, cadmium and lead in soils[END_REF]. The principle of the UBM is to mimic the human digestive process with chemical extractions simulating gastric and gastro-intestinal phases [START_REF]Soil Quality. Assessment of human exposure from ingestion of soil and soil material -Procedure for the estimation of the human bioaccessibility/bioavailability of metals in soil[END_REF]. The UBM has been shown to be relevant in estimating human exposure in various contexts, such as mining soils [START_REF] Caboche | Modelling Pb bioaccessibility in soils contaminated by mining and smelting activities[END_REF], kitchen gardens and lawns [START_REF] Waterlot | Chemical availability of Cd, Pb and Zn in anthropogenically polluted soil: Assessing the geochemical reactivity and oral bioaccessibility[END_REF], old town soils [START_REF] Cave | Measuring the bioaccessibility, bioavailability and chemical form of lead in old dutch town soils[END_REF] and the influence of earthworm bioturbation [START_REF] Levêque | Influence of earthworm bioturbation on metals phytoavailability and human gastric bioaccessibility[END_REF]. The bioavailability of contaminants in soils can also be assessed using ex situ (e.g., in laboratory) bioaccumulation studies with bioindicators [START_REF]Soil Quality. Requirements and guidance for the selection and application of methods for the assessment of bioavailability of contaminants in soil and soil materials[END_REF], such as the terrestrial gastropod Cantareus aspersus [START_REF] Pauget | Assessing the in situ bioavailability of trace elements to snails using accumulation kinetics[END_REF][START_REF] Pauget | Assessment of the bioavailability and depuration of uranium, cesium and thorium in snails (Cantareus aspersus) using kinetics models[END_REF][START_REF] De Vaufleury | How terrestrial snails can be used in risk assessment of soils[END_REF]. This land snail integrates three pathways of exposure: digestive (ingestion of soil particles, up to 40% to satisfy its physiological needs), cutaneous (transfer from the soil to the snail foot) and pulmonary (inhalation of soil particles) [START_REF] De Vaufleury | How terrestrial snails can be used in risk assessment of soils[END_REF][START_REF] Scheifler | Transfer of Cd, Cu, Ni, Pb and Zn in a soil-plant-invertebrate food chain: a microcosm study[END_REF][START_REF] Vaufleury | Growing snails used as sentinels to evaluate terrestrial environment contamination by trace elements[END_REF][START_REF] Gimbert | Kinetic and dynamic aspects of soil-plant-snail transfer of cadmium in the field[END_REF][START_REF] De Vaufleury | Landsnail for ecotoxicological assessment of chemicals and soil contamination[END_REF]. For this ubiquitous soil invertebrate, relationships between total concentration, bioavailability, bioaccumulation, and the influence of various factors (sources of exposure, physicochemical parameters of soils, etc.) have been investigated in several studies, specifically for metallic elements in soils [START_REF] Vaufleury | Growing snails used as sentinels to evaluate terrestrial environment contamination by trace elements[END_REF][START_REF] Gimbert | Kinetic and dynamic aspects of soil-plant-snail transfer of cadmium in the field[END_REF][START_REF] De Vaufleury | Landsnail for ecotoxicological assessment of chemicals and soil contamination[END_REF][START_REF] Pauget | Soil parameters are key factors to predict metal bioavailability to snails based on chemical extractant data[END_REF], making this organism a relevant candidate to explore possible the convergence between HHRA and ERA.

Currently, HHRA and ERA approaches have rarely been conducted together on contaminated soils to offer an integrative risk assessment despite the growing interest in associating them in recent years [START_REF] Rahman | Arsenic bio-accessibility and bioaccumulation in aged pesticide contaminated soils: A multiline investigation to understand environmental risk[END_REF][START_REF] Yu | Relationships between the bioavailability of polybrominated diphenyl ethers in soils measured with female C57BL/6 mice and the bioaccessibility determined using five in vitro methods[END_REF]. Toxicological data for humans and ecotoxicological data are available but seldom associated, except in safety data sheets for chemical compounds. Surprisingly, their association for the evaluation of polycontaminated environmental matrices, e.g., in an a posteriori ERA approach, is infrequent [START_REF] Rahman | Arsenic bio-accessibility and bioaccumulation in aged pesticide contaminated soils: A multiline investigation to understand environmental risk[END_REF]. However, such an association needs to be developed for the preservation of both human and environmental health, e.g., to promote the One Health concept to assess the effects of multiple stressors at the human-animal-ecosystem interface [START_REF] Destoumieux-Garzón | The One Health Concept: 10 Years Old and a Long Road Ahead[END_REF]. For the time being, integrative risk assessment has focused on a few contaminants, such as nonylphenol [START_REF] Who | Integrated risk assessment: nonylphenol case study[END_REF], but rarely on polycontaminated matrices, as is often the case with soils. However, some recent soil quality indices developed with land snails have been shown to be relevant to highlighting the potential transfer of metals to living organisms, including human populations [START_REF] Mariet | Using bioindicators to assess the environmental risk of past mining activities in the Vosges Mountains (France)[END_REF]. The potential of such indices for the development of methodologies for an integrative risk assessment of contaminated soils remains to be explored.

In this context, the aim of this study is to confront assessment methodologies for exposure to metal(loid)s in soils for humans (UBM test) and for a soil fauna organism living at the air-soilplant interface (snail test). Using a wide range of soils, we also aim to estimate the influence of the physicochemical parameters of soils (e.g., texture, pH and OM content) on the metal(loid)s in soils that can potentially be absorbed by humans (i.e., bioaccessibility) and on the metal(loid)s absorbed and accumulated in snails (i.e., bioavailability).

Experimental

Soils

Twenty-nine soils were sampled from contaminated fields in France after humus removal (A horizon) (Fig 1), and the samples were dried (<40°C) and sieved at 250 µm. The physicochemical parameters were then measured with the appropriate ISO standard protocols (Tab 1). The pHwater ranged from 4.3 to 8.3, and the OM contents ranged from 15.4 to 360 mg kg -1 . The As, Cd and Pb concentrations were obtained by hot block system-assisted digestion (Environmental Express® SC100, Charleston, SC, USA) and determined by inductively coupled plasma mass spectrometry (ICP-MS, 7900, Agilent Technology, Les Ulis, France).

More specifically, 300 mg of soil sample was digested in a mixture of 1.5 mL HNO3 (70%) and 4.5 mL HCl (37%) at 95°C for 1 h and 30 min. After mineralization, digestion products were brought to 25 mL with ultrapure water (resistivity of 18.0 MΩ cm -1 ) and stored at 4°C prior to analysis. The recovery rates as determined with a certified standard (ERM CC141, Loam soil,

LGC Standards, Molsheim, France) for all metal(loids) were 115 ± 7%.

UBM test

The bioaccessibility was measured in triplicate for each soil sample with an in vitro validated extraction method: the UBM test [START_REF] Wragg | An inter-laboratory trial of the unified BARGE bioaccessibility method for arsenic, cadmium and lead in soil[END_REF][START_REF] Denys | In vivo validation of the unified BARGE method to assess the bioaccessibility of arsenic, antimony, cadmium and lead in soils[END_REF][START_REF]Soil Quality. Assessment of human exposure from ingestion of soil and soil material -Procedure for the estimation of the human bioaccessibility/bioavailability of metals in soil[END_REF] adapted by Pelfrêne and Douay [START_REF] Pelfrêne | Assessment of oral and lund bioaccessibility of Cd and Pb from smelter-impacted dust[END_REF] and Pelfrêne et al. [START_REF] Pelfrêne | In vitro digestion and DGT techniques for estimating cadmium and lead bioavailability in contaminated soils: Influence of gastric juice pH[END_REF]. Briefly, 0.6 g of dry soil was placed in a centrifuge tube and mixed with 9 mL of simulated saliva fluid. After quick manual shaking (10 s), 13.5 mL of simulated gastric fluid was added, and the pH of the solution was adjusted to 1.2 ± 0.05 with HCl (37%). The tubes were shaken end-over-end at 37°C for 1 h and centrifuged at 4500 x g for 5 min. The supernatant constitutes the gastric-only phase (UBM G). Then, the gastro-intestinal (GI) phase was prepared from the gastric phase, by adding 27 mL of simulated duodenal fluid and 9 mL of simulated bile solution. The final pH ranged from 5.8 to 6.8 by adjustment with NaOH (10 M). Tubes were shaken end-over-end at 37°C for 4 h and centrifuged at 4500 x g for 5 min (UBM GI). Bioaccessible concentrations of As, Cd and Pb in the supernatants of the UBM G and UBM GI phases were measured by inductively coupled plasma mass spectrometry (ICP-MS, 7900, Agilent Technology, Les Ulis, France). To evaluate analytical recovery, a blank and a NIST standard reference material (SRM2710a) were used. The recovery rates of SRM2710a (n=3) were 93.2 ± 4% on average for all metal(loid)s and UBM phases. For each metal(loid) and each phase of the UBM test, the percentage of the bioaccessible fraction was the ratio between the bioaccessible and soil concentrations.

Snail test

Juvenile land snails (Cantareus aspersus, Müller, 1774) were reared in the laboratory under controlled conditions (20°C, 80% relative humidity, and a photoperiod of 18 h of light and 6 h of dark) until the sub-adult stage (7-9 weeks), as described by Gomot-de-Vaufleury [START_REF] Vaufleury | Standardized growth toxicity testing (Cu, Zn, Pb and Pentachlorophenol) with Helix aspersa[END_REF]. The sub-adult stage was selected to avoid marked mass changes related to growth and reproduction [START_REF] Pauget | Ranking field site management priorities according to their metal transfer to snails[END_REF][START_REF] Gimbert | Kinetic and dynamic aspects of soil-plant-snail transfer of cadmium in the field[END_REF]. At the beginning of exposure, sub-adult snails weighed 4.95 ± 0.66 g, and the internal concentrations of As, Cd and Pb were measured in visceral mass from six sub-adult snails (0.127 ± 0.001, 1.53 ± 0.175, 0.510 ± 0.332 mg kg -1 dw, respectively). Snails were fed during growth with uncontaminated (As, Cd and Pb contents: 0.718, 0.430 and 0.784 mg kg -1 dw, respectively) commercial food (Helixal®, Berthon S.A., France) and were fed during the exposure stage with uncontaminated (As, Cd and Pb contents: 0.127, 0.648 and 0.108 mg kg -1 dw, respectively) fresh lettuce (organic farm, France).

For each soil, six snails were exposed for four weeks (28 days) in triplicate in transparent polystyrene containers of 4032 cm 3 (24 x 21 x 8 cm). Exposure modalities are detailed in Pauget et al. [START_REF] Pauget | Soil parameters are key factors to predict metal bioavailability to snails based on chemical extractant data[END_REF]. One week before exposure, 100 g of soil (DW, <250 µm) was introduced to the containers and humidified (water holding capacity (WHC) adjusted to 50%) with demineralized water (with a pH of 6.5). Every two days, the containers were cleaned to remove faeces, and the lettuce was renewed. Snail food was offered ad libitum (corresponding to 1.5 g lettuce day - 1 snail -1 ) in a Petri dish left on the bottom of the container. At the end of exposure, snails were starved in clean containers (without soil) for two days (the faeces were removed every 12 h).

Then, the snails were frozen (-80°C). After thawing, the visceral mass of each snail was dissected. Six visceral masses (2 per container x 3 replicates) per soil were freeze dried for two days before As, Cd and Pb analysis. Lyophilized viscera were digested between 47°C and 98°C for 265 min (DigiPREP MS, SCP Science, Courtaboeuf, France) in 7 mL of nitric acid (HNO3 at 65%, Optima ultra trace purity, Fisher Scientific, Illkirch, France) that was diluted with MilliQ water (43 mL). Then, samples were filtered at 1 µm (Hydrophilic Teflon©, DigiFILTER 1.0 µm, SCP Science, Courtaboeuf, France) for ICP-MS analysis (Thermo Scientific X Series II, Courtaboeuf, France). Analyses were validated with a certified standard (TORT-2, lobster hepatopancreas, LGC Standards, Molsheim, France) with recovery rates of 114 ± 9% on average for all metal(loid)s. The bioaccumulated metal(loid) concentrations in the snails and the soil metal(loid) concentrations were used to calculate the bioaccumulation factors (BAF).

Statistical analysis

Statistical analysis was performed with R (version 3.4.2) [START_REF] Core | R: A language and environment for statistical computing[END_REF]. The data (except pH) were transformed by log10 (x+1) to fulfil the residual normality and variance homogeneity requirements (Kolmogorov-Smirnov and Bartlett tests). Assessment of the relationships between metal(loid) concentrations in the soil and/or bioaccessible concentrations and/or bioaccumulated concentrations in viscera was performed by simple linear regression. Then, the influence of soil physicochemical parameters on bioaccessible concentrations and/or bioaccumulated concentrations in viscera was modelled with multiple linear regression. Based on the best models obtained, the bioaccessible concentrations were estimated from the concentrations in snails and soil physicochemical parameters. It is possible to test the efficiency of models on a subset of data when data from another experiment with other soils are not available by performing an internal cross-validation test [START_REF] Stone | Cross-validatory choice and assessment of statistical predictions[END_REF][START_REF] Gimbert | Modelling chronic exposure to contaminated soil: A toxicokinetic approach with the terrestrial snail Helix aspersa[END_REF]. In this approach, the proposed models were considered valid if the differences between adjusted q² and adjusted r² (r²adj.) do not exceed 0.3 [START_REF]Guidance document on the validation of (quantitative) structure-activity relationships[END_REF]. All the models were validated with an internal cross-validation test [START_REF] Stone | Cross-validatory choice and assessment of statistical predictions[END_REF][START_REF] Gimbert | Modelling chronic exposure to contaminated soil: A toxicokinetic approach with the terrestrial snail Helix aspersa[END_REF].

For this internal verification step, one-third (n=10) of samples were randomly chosen, and multiple regressions were re-modelled. Comparisons between q² (determination coefficient of the cross-validation test) and r² (models proposed) allowed for model validation. For each set of regressions, the best model (i.e., the one providing the best adjusted coefficient of determination with the lowest number of independent variables) was chosen using the corrected Akaike criterion (AICc) [START_REF] Burnham | Multimodel inference understanding AIC and BIC in model selection[END_REF].

Results and discussion

Oral bioaccessible fractions for humans and bioavailability to snails

The bioaccessible fractions for humans and bioaccumulated concentrations for snails are presented in Tab 2. The in vitro bioaccessibility of As, Cd and Pb measured in the twenty-nine soil samples ranged from 0.508 to 245 mg kg -1 , 0.082 to 321 mg kg -1 and 10.7 to 10730 mg kg - 1 of soil for the G phase and from 0.583 to 89.1 mg kg -1 , 0.035 to 142 mg kg -1 and 0 to 2460 mg kg -1 of soil for the GI phase, respectively (Tab 2). The mean ratios/percentages of the bioaccessible fractions of As, Cd and Pb in the G phase were 37 ± 23%, 84 ± 15% and 78 ± 23%, respectively, of the pseudo-total concentrations in the soils. In the GI phase, the bioaccessible fractions of As, Cd and Pb decreased to 30 ± 16%, 38 ± 13% and 11 ± 14%, respectively. Overall, for the twenty-nine soils studied, bioaccessible fractions of Cd and Pb were higher (2.3 and 4.6 times, respectively) in the G phase than in the GI phase. These results are explained by the pH of the simulated fluids, which are more acidic in the G phase and lead to higher solubilization of metals [START_REF] Ruby | Estimation of lead and arsenic bioavailability using a physiologically based extraction test[END_REF][START_REF] Wragg | An inter-laboratory trial of the unified BARGE bioaccessibility method for arsenic, cadmium and lead in soil[END_REF]. However, this is much less marked for As, which showed similar bioaccessible fractions, in most cases, in both phases with average values of 37% vs 30% (i.e., 1.2-fold less), for G and GI phases, respectively (Tab 2). This difference could be related to the particular geochemical behaviour of As in the simulated fluid conditions [START_REF] Wragg | An inter-laboratory trial of the unified BARGE bioaccessibility method for arsenic, cadmium and lead in soil[END_REF][START_REF] Rahman | Arsenic bio-accessibility and bioaccumulation in aged pesticide contaminated soils: A multiline investigation to understand environmental risk[END_REF], which may lead to reduced adsorption and precipitation reactions at the neutral pH in the GI phase for As than for Cd and Pb [START_REF] Ruby | Estimation of lead and arsenic bioavailability using a physiologically based extraction test[END_REF][START_REF] Wragg | An inter-laboratory trial of the unified BARGE bioaccessibility method for arsenic, cadmium and lead in soil[END_REF]. These results for the three studied metal(loid)s are in accordance with those in other studies [START_REF] Ruby | Estimation of lead and arsenic bioavailability using a physiologically based extraction test[END_REF][START_REF] Wragg | An inter-laboratory trial of the unified BARGE bioaccessibility method for arsenic, cadmium and lead in soil[END_REF][START_REF] Lu | Assessment of bioaccessibility and exposure risk of arsenic and lead in urban soils of Guangzhou city, China[END_REF][START_REF] Roberts | Relative oral bioaccessibility of arsenic from contaminated soils measured in the Cynomolgus monkey[END_REF], especially those of Denys et al. [START_REF] Denys | In vivo validation of the unified BARGE method to assess the bioaccessibility of arsenic, antimony, cadmium and lead in soils[END_REF],

in an in vivo validation of the UBM test on juvenile swine.

The in vivo bioavailability of As, Cd and Pb measured with the bioaccumulation test after C. aspersus in 28 days ranged from 0.098 to 21.9 mg kg -1 , 2.53 to 333 mg kg -1 and 1.42 to 856 mg kg -1 of dry weight (dw) viscera, respectively (Tab 2). The comparison between bioaccessible and bioaccumulated concentrations of As and Pb for each soil showed that the concentrations in snails were lower than the bioaccessible phase concentrations (e.g., the As and Pb concentrations in snails were approximately 9 and 6 times lower than those in the G phase, respectively). In contrast, for Cd, the concentrations were 2 times higher in snails than in the G phase of the UBM test due to the snail physiology and internal management of metal(loid)s; specifically, Pb is highly excreted with cell debris, while Cd is stored and associated with metallothionein in the cytosolic fraction [START_REF] De Vaufleury | Landsnail for ecotoxicological assessment of chemicals and soil contamination[END_REF][START_REF] Gimbert | How subcellular partitioning can help to understand heavy metal accumulation and elimination kinetics in snails[END_REF]. Hence, elevated BAFs were recorded for Cd (ranging from 0.859 and 25.3), and low BAFs were recorded for As and Pb (ranging from 0.004 to 0.169 or 0.055 to 0.769, respectively) (Tab 2). These BAFs are in accordance with those reported in various studies in which C. aspersus was classified as a deconcentrator of As and Pb and a macroconcentrator of Cd [START_REF] Vaufleury | Growing snails used as sentinels to evaluate terrestrial environment contamination by trace elements[END_REF][START_REF] Gimbert | Kinetic and dynamic aspects of soil-plant-snail transfer of cadmium in the field[END_REF][START_REF] Pauget | Soil parameters are key factors to predict metal bioavailability to snails based on chemical extractant data[END_REF]42,[START_REF] Coeurdassier | Arsenic transfer and impacts on snails exposed to stabilized and untreated Ascontaminated soils[END_REF].

We observed substantial inter-soil variability in bioaccessible fractions and bioaccumulated concentrations in snails (Tab 2). This variability highlights the influence not only of soil contamination (concentration of metal(loid)s and mixture) but also of the physicochemical parameters of soils (e.g., pH and OM content) on metal(loid) mobility and transfer.

Influence of soil parameters on oral bioaccessible concentrations for humans and bioavailability to snails

The relationships between the bioaccessibility of As, Cd and Pb and their total concentrations in soils were investigated. The modulating influence of the physicochemical parameters of soils was also examined because soil parameters can influence metal(loid) availability and bioavailability [START_REF] Pelfrêne | Bioaccessibility of trace elements as affected by soil parameters in smelter-contaminated agricultural soils: A statistical modeling approach[END_REF][START_REF] Dousouva | Effect of organic matter on arsenic(V) and antimony(V) adsorption soils[END_REF][START_REF] Masscheleyn | Effect of redox potential and pH on arsenic speciation and solubility in a contaminated soil[END_REF][START_REF] Redman | Natural organic matter affects arsenic speciation and soprtion onto hematite[END_REF][START_REF] Feng | Adsorption and desorption characteristics of arsenic on soils: kinetics, equilibrium, and effect of Fe(OH)3 colloid, H2SiO3 colloid and phosphate[END_REF]. Strong relationships between total concentrations of contaminants in soil and their extractible concentrations observed in the UBM test were evidenced by r²adj. values ranging from 0.63 to 0.99, according to the contaminant and bioaccessible phase (G or GI) considered (Tab 3). For As, very close relationships were found for the G and GI phases, while the r²adj values in the G phase were always higher for Cd and Pb. The neutral pH of the intestinal phase might have led to readsorption of Cd to OM particles of soil [START_REF] Yuan | Desorption of copper and cadmium from soils enhanced by organic acids[END_REF][START_REF] Loganathan | Cadmium sorption and desorption in soils: a review[END_REF]. For both phases, As bioaccessibility was positively modulated by the silt content of the soils. Hence, the As of this granulometric fraction seemed to be transferred to the simulated solutions of UBM tests.

A similar approach was carried out with As, Cd and Pb concentrations accumulated in snails as an indicator of their bioavailability (Tab 3). For each element, the total concentration in soils appeared as an important explanatory variable (r²adj. = 0.51, 0.92 and 0.85 for As, Cd and Pb, respectively); although physicochemical parameters of soils did not improve the regression model for Pb, some parameters improved the regression models for As and Cd (Tab 3). Hence, for As, the content of OM and silts increased the r²adj. up to 0.65, and for Cd, the OM content, pH and cation exchange capacity (CEC) increased the r²adj. up to 0.96. These results are in accordance with previous laboratory experiments with snails and are related to the low lability of Pb in soils and the reactivity of As and Cd to soil pH and components such as OM [START_REF] Pauget | Soil parameters are key factors to predict metal bioavailability to snails based on chemical extractant data[END_REF].

Relationships between oral bioaccessibility and bioavailability of metal(loid)s

We first looked for relationships between extractible concentrations in the UBM test and accumulated concentrations in the snail tissues of As, Cd and Pb (Fig 2). The related regressions revealed, regardless of the digestive compartment considered (G or GI), strong and positive relationships, particularly for Cd and Pb and to a lesser extent for As (Tab 4). As previously described, the potential influence of soil parameters was also investigated in a new modelling step to better connect the oral bioaccessible concentrations to humans with the bioaccumulated concentrations for snails. The obtained regressions were then strongly improved, especially when considering the soil OM content, with a rise of 17% and 15% of variance explained (r²adj.) for As in the G and GI phases, respectively and to a lesser extent for Pb (+4% and +6%) and Cd (+2%) (Tab 4). This improvement in estimating the bioaccessible concentrations can be explained by the limited ability of snails to access the metal(loid) fraction associated with organic particles in soils. Indeed, the pH in the snail digestive tract ranges between 6.1 and 7.5 [START_REF] Charrier | The gut microenvironment of helicid snails (Gastropods: Pulmonata): in situ profiles of pH, oxygen and hydrogen dertermined by microsensors[END_REF], which is probably not sufficient to reach the desorption capacities achieved by the very acidic pH in the human stomach [START_REF] Ottosen | Relation between pH and desorption of Cu, Cr, Zn, and Pb from industrially polluted soils[END_REF].

The robustness of the improved models was checked using a cross-validation approach. The small differences (< 0.17 (ranging from 0.78 to 0.95), demonstrating that bioavailability to snails may be an efficient way to estimate oral bioaccessibility for humans.

Our objective was not to oppose or to prioritize the UBM test and the bioassay with snails but to demonstrate their complementarity, both in terms of response and use. Indeed, to our knowledge, studies that try to link chemical approaches for bioaccessibility assessment and biological tests to estimate bioavailability with soil invertebrates are rare. The majority of the studies concerning the discovered relationships with mammals, such as mice, have shown that the UBM assay can estimate the bioavailability of As, Cd and Pb in contaminated soils [START_REF] Li | In vitro bioaccessibility and in vivo relative bioavailability in 12 contaminated soils: Method comparison and method development[END_REF][START_REF] Li | Lead bioaccessibility in 12 contaminated soils from China: correlation to lead relative bioavailability and lead in different fractions[END_REF][START_REF] Li | Assessment of cadmium bioaccessibility to predict its bioavailability in contaminated soils[END_REF][START_REF] Zhu | As, Cd and Pb relative bioavailability in contaminated soils: Coupling mouse bioassay with UBM assay[END_REF].

To date, only the study of Rahman et al. [START_REF] Rahman | Arsenic bio-accessibility and bioaccumulation in aged pesticide contaminated soils: A multiline investigation to understand environmental risk[END_REF] has reported correlations (r²=0.95) between bioaccumulation factors in earthworms (Lumbricus rubellus) and the human bioaccessible fraction (gastric phase) of As in six aged pesticide-contaminated soils. Thus, for these two bioindicators of soil quality (L. rubellus and C. aspersus), strong relationships between bioaccumulation and oral bioaccessibility to humans exist for As. Similarity between these results and ours was not necessarily expected because of the differences between the considered organisms (i.e., humans and soil invertebrates) in terms of sources, routes of exposure and physiology.

Conclusions

This study provides effective methods to establish links between the bioaccessibility to humans and the bioavailability to snails, and new evidence confirming that HHRA and ERA methodologies may converge to reinforce risk assessment procedures for both sanitary and environmental perspectives. Hence, in the case where only physicochemical properties of soils and environmental data for ERA are available, we propose a way to approach, in a first attempt, HHRA at least for As, Cd and Pb; similarly, HHRA data could be used to approach ERA.

In HHRA procedures, daily doses of exposure based on total concentrations of contaminants in soils are used to estimate a hazard quotient (HQ) [START_REF] Meem | Méthodologie nationale de gestion des sites et sols pollués[END_REF]. As discussed in the study of Jia et al. [START_REF] Jia | Assessment of soil heavy metals for eco-environment and human health in a rapidly urbanization area of the upper Yangtze Basin[END_REF] on a rapidly urbanization area of Yangtze (China), the measurements of oral bioaccessible and bioaccumulated concentrations can be used to refine HQs to provide a more accurate estimation of the exposure and consequently a better interpretation of the environmental state. However, these data and models are available for a limited number of contaminants and soil quality bioindicators.

The original findings we provide in this study rely on the establishment of relationships connecting the oral bioaccessibility to humans and bioavailability to snails for As, Cd and Pb.

In the current context of increasing sanitary and environmental crises, these results constitute a useful contribution to coordinated risk assessment strategies. As exposure assessment is a key factor in assessing the risk of contaminated soil, this contribution joins the current trend of the One Health concept, associating humans and other organisms in an integrative risk assessment.

Acknowledgements

The authors would like to thank ADEME for funding the study programme COMBINE:

Coupler des indicateurs chiMiques et Biologiques pour une évaluation Intégrative des risques sanitaires et Environnementaux (contract n°1572C0310) and the programme ODESSA:

Optimisation de la gestion DEs Sites et Sols pollués par une mesure simple de bioAccessibilité (contract n°1472C0046). The authors thank Dominique Rieffel and Caroline Amiot for their technical assistance. The authors warmly thank the reviewers for their constructive remarks.

Conflict of interest

TABLES AND FIGURES

Bioaccessibility of metal(loid)s in soils to humans and their bioavailability for snails: a way to associate human health and ecotoxicological risk assessment?

Tables:

Table 1: Soil types and physicochemical parameters (OM: organic matter, Corg: organic carbon, CEC: cation exchange capacity, Alox and Feox are exchangeable cations in soils, Emb.: embankment, Farm.: farming, Gras.: grassland, Indus.: industrial, U: unknown, Urb.: urban).

Table 2: Bioaccessible concentrations and fractions for humans and bioaccumulated concentrations and bioaccumulation factors (BAFs) for snails for each soil (results are presented in mg kg -1 dw for concentrations (mean for bioaccessibility and median for bioaccumulated concentrations for snails) and in % for bioaccessible fractions and BAF is the ratio between concentrations in snails and concentrations in soils. G and GI: gastric and gastro-intestinal phases of the UBM test, respectively).

  These results are related to the differential solubilization, precipitation and therefore absorption potential of the stomach and intestine, as discussed above. The consideration of soil parameters rather than just the total concentrations of metal(loid)s (Tab 1) can improve the regression models (Tab 3). For As in G and GI phases, the content of silt increased the r²adj. values up to 0.71 and 0.72, respectively, and for Cd in the GI phase, the OM content increased the r²adj. up to 0.96. No influence of soil physicochemical parameters was observed for Cd in the G phase or Pb in either phase. It is likely that the strong acidic pH of the first gastric solution of the UBM test prevented the influence of the soil physicochemical parameters on Cd and Pb bioaccessibility. For the GI phase, OM content negatively influenced the Cd bioaccessibility.

  ) between the r²adj. (Tab 4) and q²adj. (Tab 5) values testify to the efficiency of the proposed models for assessing metal(loid) bioaccessibility to humans using a bioavailability assessment with snails. Finally, we verified the estimation potential of these validated models by comparing measured and estimated values of bioaccessible concentrations (Fig 3). For each digestive phase and metal(loid) studied, the slopes were relatively close to 1

M. Louzon 1 , 1 Figures : Figure 1 :Figure 2 :

 11:12 Figures:

Figure 3 :

 3 Figure 3: Relationship between bioaccessible concentrations measured with the UBM test and estimated concentrations from snails (with equations in Tab 4, data are transformed by log10 (x+1); grey bands are 95% confidence intervals of the linear regression models that are represented by black lines).

[

  As]UBM G = 0.523*** + 1.27[As]snail*** [As]UBM G = -0.513* + 1.28[As]snail *** + 0.567[OM]*** [As]UBM GI = 0.493*** + 1.18[As]snail*** [As]UBM GI = -0.403* + 1.19[As]snail*** + 0.490[OM]*** UBM G = -0.647*** + 1.15[Cd]snail*** [Cd]UBM G = -1.07*** + 1.08[Cd]snail *** + 0.282[OM]** [Cd]UBM GI = -0.637*** + 0.963[Cd]snail*** [Cd]UBM GI = no influence of soil parameters 0UBM G = 0.510** + 1.04[Pb]snail*** [Pb]UBM G = -0.183 + 0.872[Pb]snail*** + 0.553[OM]*** [Pb]UBM GI = -0.735* + 1.14[Pb]snail*** [Pb]UBM GI = -1.83*** + 0.879[Pb]snail *** + 0.875[OM]

Fig 1 :

 1 Fig 1:

Fig 2 :

 2 Fig 2:

Fig 3 :

 3 Fig 3:

Table 3 : Influence of total metal(loid) concentrations and soil parameters on oral

 3

	bioaccessibility and bioaccumulation (significant variables are ranked with stars as a
	function of p-value obtained: * < 0.05, ** < 0.01, *** < 0.001, data are transformed by log10
	(x +1)).

Table 4 : Relationship between concentrations accumulated in visceral mass of snails and in the UBM test phases G and GI for gastric and gastro-intestinal phases, respectively

 4

	(significant variables are ranked with stars as a function of the p-value obtained: * < 0.05, **

Table 5 : Equations of the internal cross-validated models assessing the bioaccessible concentrations according to the accumulated concentrations in snails and physicochemical parameters

 5

	of soils (data are transformed by log10 (x+1); significant variables are ranked
	with stars as a function of p-value obtained: * < 0.05, ** < 0.01, *** < 0.001).

Table 1 :

 1

	Soils	Site use	Clay (%)	Silt (%)	Sand (%)	pHwater	OM (g kg -1 )	Corg (g kg -1 )	CaCO3 (g kg -1 )	CEC (cmol kg -1 )	Alox (cmol kg -1 )	Feox (cmol kg -1 )	As (mg kg -1 )	Cd (mg kg -1 )	Pb (mg kg -1 )
	O1	Urb.	15.2	41.4	41.9	7.7	161	92.7	15.0	20.9	0.023	0.005	13.4	1.32	430
	O2	Ind.	16.1	47.4	36.5	7.4	71.1	40.9	1.3	17.5	0.035	0.006	11.5	1.91	320
	O3	Ind.	23.1	47.8	29.1	8.0	61.1	35.1	84.0	18.0	0.020	0.005	228	257
	O4	Ind.	16.6	41.0	42.4	7.8	304	175	22.3	12.3	0.020	0.005	74.4	48.0
	O5	Ind.	12.3	35.0	52.7	6.8	360	207	3.6	11.7	0.054	0.007	108	85.7
	O6	Ind.	29.1	45.9	25.0	8.1	24.3	14.0	91.2	24.6	0.020	0.005	139	109
	O7	Ind.	21.5	44.0	34.5	8.3	112	64.1	145	22.3	0.020	0.005	12.8	4.2	385
	O8	Ind.	22.8	70.6	6.6	8.3	27.1	15.6	162	16.5	0.020	0.005	5.64	0.640	30.7
	O9	Ind.	20.0	56.9	23.1	8.0	111	63.9	38.6	17.3	0.020	0.005	23.3	7.34	534
	O10	Ind.	23.7	48.2	28.1	5.7	205	118	1.6	31.2	0.020	0.005	48.6	27.8
	O11	Ind.	16.2	55.1	28.7	6.8	72.9	41.9	<1.0	18.2	0.020	0.005	27.9	18.2
	O12	Ind.	15.7	52.1	32.2	4.3	46.8	26.9	<1.0	10.2	0.028	0.005	7.74	1.42	222
	O13	Ind.	16.8	46.9	36.3	5.2	59.3	34.1	<1.0	18.4	0.020	0.005	12.6	6.50	484
	O14	Ind.	33.3	59.3	7.4	8.0	75.2	43.2	40.7	38.8	0.030	0.008	23.4	15.4	719
	O15	Ind.	13.5	42.6	43.9	7.9	30.6	17.6	37.5	10.9	0.020	0.005	13.5	1.30	177
	O16	U	16.7	73.4	9.6	7.6	18.2	10.5	3.0	12.4	0.020	0.005	5.52	0.640	17.8
	O17	U	30.2	34.9	34.2	5.7	51.4	29.6	1.0	16.2	0.027	0.005	17.8	0.200	33.7
	O18	Farm.	41.6	21.5	36.3	8.0	35.8	20.6	27.0	28.4	0.020	0.005	74.4	0.520	46.6
	O19	Ind.	16.9	54.8	28.5	7.2	33.5	19.3	3.6	12.3	0.020	0.005	10.1	4.49	117
	O20	Ind.	22.0	29.5	48.5	8.1	15.9	9.1	17.9	10.2	0.035	0.005	26.0	0.370	150
	O21	Gras.	8.0	10.0	82.0	7.6	43.5	25.0	31	11.1	0.020	0.005	11.3	2.32	288
	O22	U	8.8	7.5	83.7	8.2	15.4	8.9	18	6.5	0.020	0.005	3.28	0.235	19.7
	O23	Farm.	16.3	38.1	45.6	6.8	28.3	16.3	3.2	7.2	0.020	0.007	57.0	0.102	660
	O24	Farm.	18.3	42.0	39.7	7.6	55.9	32.2	106	18.1	0.020	0.005	12.0	3.57	303
	O26	Ind.	11.3	16.9	71.8	7.5	41.7	24.0	169	4.3	0.020	0.005	13.3	0.450	312
	O27	Emb.	6.8	20.2	73.0	7.9	134	77.0	51.5	8.6	0.020	0.007	28.5	7.43
	O28	Emb.	9.1	30.3	60.6	7.8	230	132	16.9	12.1	0.020	0.007	25.8	2.60	467
	O29	Emb.	7.6	30.8	61.6	7.9	185	106	29.9	9.0	0.020	0.005	36.1	27.2
	O30	Emb.	9.0	22.0	69.0	8.1	179	103	27.2	10.1	0.042	0.005	28.3	12.8
	Min.		6.8	7.5	6.6	4.3	15.4	8.9	<1.0	4.30	0.020	0.005	3.28	0.102	17.8
	Max.		41.6	73.4	83.7	8.3	360	207	169	38.8	0.054	0.008	228	257

Table 2 :

 2

			As			Cd			Pb
	Soils
		G Phase	GI Phase Snail BAF	G Phase	GI Phase Snail BAF	G Phase	GI Phase Snail BAF
	O1	5.05 (38%) 5.08 (38%) 0.298 0.022 1.25 (95%) 0.413 (31%) 5.02 3.80	349 (81%)	111 (26%) 84.6 0.197
	O2	3.69 (32%) 3.39 (29%) 0.298 0.026 1.40 (73%) 0.407 (21%) 5.63 2.95	217 (68%)	7.93 (2%)	43.3 0.135
	O3	245 (108%) 112 (49%)	21.9 0.096 321 (125%)	142 (55%)	333 1.29 6542 (105%) 2460 (39%) 856	0.137
	O4	42.4 (57%) 28.5 (38%) 1.29 0.017 41.2 (86%)	11.9 (25%) 60.0 1.25	3964 (76%)	342 (7%)	652	0.125
	O5	64.5 (60%) 52.7 (49%) 2.25 0.021 75.9 (89%)	29.0 (34%) 73.6 0.859 10730 (120%) 1801 (20%) 731	0.081
	O6	111 (80%)	89.1 (64%) 19.2 0.138	104 (96%)	48.8 (45%) 307 2.83	2034 (93%)	100 (5%)	783	0.359
	O7	4.49 (35%) 3.25 (25%) 0.298 0.023 3.85 (92%)	1.04 (25%) 18.6 4.43	337 (88%)	9.52 (2%)	267	0.694
	O8	1.19 (21%) 1.19 (21%) 0.298 0.053 0.541 (85%) 0.250 (39%) 5.33 8.33	20.4 (66%)	3.11 (10%) 5.21 0.169
	O9	10.4 (45%) 9.72 (42%) 3.93 0.169 6.15 (84%)	2.75 (37%) 32.0 4.36	514 (96%)	11.8 (2%)	208	0.389
	O10	35.3 (73%) 25.4 (52%) 2.31 0.048 31.1 (112%) 11.2 (40%) 71.9 2.58 2330 (104%) 973 (44%)	503	0.225
	O11	14.0 (50%) 13.6 (49%) 3.78 0.135 15.4 (85%)	6.48 (36%) 52.5 2.91	1104 (88%)	124 (10%)	431	0.342
	O12	1.09 (14%) 1.25 (16%) 0.298 0.039 1.04 (73%) 0.478 (34%) 12.5 8.80	198 (89%)	101 (45%)	171	0.769
	O13	3.36 (27%) 3.67 (29%) 0.262 0.021 4.82 (74%)	1.10 (17%) 28.3 4.35	457 (94%)	42.8 (9%)	162	0.335
	O14	9.00 (38%) 15.2 (65%) 2.02 0.086 13.3 (87%)	8.72 (57%) 46.7 3.04	609 (85%)	14.4 (2%)	271	0.377
	O15	5.05 (38%) 3.64 (27%) 0.482 0.036 1.02 (78%) 0.814 (63%) 6.04 4.65	114 (64%)	0.745 (0%) 21.0 0.119
	O16	0.841 (15%) 0.910 (16%) 0.098 0.018 0.544 (85%) 0.203 (32%) 4.80 7.50	10.7 (60%)	0.000 (0%) 4.12 0.232
	O17	1.95 (11%)	1.50 (8%) 0.098 0.006 0.154 (77%) 0.120 (60%) 2.56 12.8	13.7 (41%)	0.733 (2%) 1.42 0.042
	O18	5.97 (8%)	5.58 (8%)	1.39 0.019 0.344 (66%) 0.135 (26%) 3.20 6.15	15.3 (33%)	0.391 (1%) 2.56 0.055
	O19	1.30 (13%) 1.39 (14%) 0.098 0.010 3.20 (71%)	1.26 (28%) 12.1 2.70	84.8 (72%)	2.36 (2%)	37.4 0.320
	O20	5.94 (23%) 6.08 (23%) 1.98 0.076 0.261 (71%) 0.126 (34%) 4.59 12.4	105 (70%)	2.30 (2%)	38.9 0.259
	O21	5.50 (49%) 4.96 (44%) 2.23 0.008 1.93 (83%) 0.721 (31%) 11.5 4.96	243 (84%)	3.03 (1%)	83.7 0.291
	O22	0.508 (16%) 0.583 (18%) 0.098 0.030 0.199 (87%) 0.132 (57%) 4.24 18.4	14.2 (72%)	3.54 (18%) 12.1 0.615
	O23	17.3 (30%) 14.1 (25%) 1.48 0.026 0.082 (82%) 0.035 (35%) 2.53 25.3	111 (17%)	19.2 (3%)	39.1 0.059
	O24	4.02 (34%) 2.90 (24%) 0.829 0.069 3.41 (96%)	1.03 (29%) 12.4 3.47	259 (86%)	5.47 (2%)	35.6 0.118
	O26	5.68 (43%) 3.70 (28%) 0.098 0.007 0.490 (109%) 0.275 (61%) 3.20 7.11	275 (88%)	8.19 (3%)	58.0 0.186
	O27	6.73 (24%) 4.48 (16%) 0.098 0.003 5.43 (73%)	2.86 (38%) 8.81 1.19	1281 (68%)	137 (7%)	137	0.073
	O28	7.36 (29%) 5.84 (23%) 0.098 0.004 2.18 (84%) 0.716 (28%) 5.52 2.12	292 (63%)	41.6 (9%)	25.5 0.055
	O29	8.58 (24%) 5.92 (16%) 0.379 0.011 13.3 (49%)	9.17 (34%) 28.3 1.04	5196 (99%) 1667 (32%) 820	0.156
	O30	7.69 (27%) 6.29 (22%) 1.16 0.041 10.3 (81%)	5.28 (41%) 20.4 1.60	3136 (97%)	783 (24%)	730	0.225
	Mean	21.9 (37%) 14.9 (30%) 2.38 0.043 22.9 (84%)	9.91 (38%) 40.8 5.63	1399 (78%)	303 (11%)	249	0.246
	Standard-deviation 48.9 (22%) 26.3 (16%) 5.16 0.044 62.1 (15%)	27.4 (13%) 80.3 5.55	2447 (22%)	632 (14%)	295	0.188

Table 4 :

 4

	Elements	Equations	r²adj.	p-value
	As

Table 5 :

 5

	Elements	Internal cross-validation equations	q²adj.	p-value
	As	[As]UBM G = -0.973 + 1.24[As]snail ** + 0.800[OM]* [As]UBM GI = -0.815 + 1.03[As]snail *** + 0.742[OM]**	0.800 0.843	<0.01 <0.001
	Cd	[Cd]UBM G = -1.61** + 1.37[Cd]snail*** + 0.286[OM] [Cd]UBM GI = -1.18** + 1.27[Cd]snail ***	0.921 0.859	<0.001 <0.001
	Pb	[Pb]UBM G = -0.374 + 0.959[Pb]snail* + 0.534[OM] [Pb]UBM GI = 2.66* + 1.93[Pb]snail** -0.012[OM]	0.789 0.714	<0.01 <0.01

The authors declare no conflicts of interest.

Bibliography


Guillaume Coulouma

Laurent Prevot

Philippe Lagacherie

Carbon isotope discrimination as a surrogate for soil available water capacity in rainfed areas: A study in the Languedoc vineyard plain

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

Introduction

Soil available water capacity (SAWC) or soil available water holding capacity (AWHC) is a well-known concept that has been used for a long time to express the capacity of soils to store water for plants (Veihmayer and Hendrickson, 1927). It has been demonstrated that SAWC is one of the most important soil factors for plant growth and that it influences photosynthesis rate, carbon allocation, and nutrient cycling [START_REF] Lebourgeois | Climate-tree-growth relationships of European beech (Fagus sylvatica L.) in the French Permanent Plot Network (RENECOFOR)[END_REF][START_REF] Breda | Temperate forest trees and stands under severe drought: a review of ecophysiological responses, adaptation processes and long-term consequences[END_REF]. It is therefore a first order parameter that is used in crop modelling [START_REF] Brisson | STICS: a generic model for the simulation of crops and their water and nitrogen balances. I. Theory and parameterization applied to wheat and corn[END_REF], land evaluation and, recently, soil ecosystem service assessment [START_REF] Dominati | A soil change-based methodology for the quantification and valuation of ecosystem services from agroecosystems: A case study of pastoral agriculture in New Zealand[END_REF].

Determining the SAWC requires costly and time-consuming measurements of soil properties.

Bulk density and volumetric water content at wilting point and field capacity require undisturbed sampling and physical measurements in the laboratory [START_REF] Klute | Water retention: Laboratory methods[END_REF][START_REF] Bruand | Water retention properties of the clay in soils developed on clayey sediments: significance of parent material and soil history[END_REF]. Moreover, determination of the SAWC for perennial plants having a deep root system requires investigation of the deep horizons, which are not always accessible.

Consequently, the SAWC data are extremely sparse in existing soil databases, which prevents the use of these databases as inputs for Digital Soil Mapping approaches [START_REF] Mcbratney | On digital soil mapping[END_REF] as is currently done for other more current soil properties (e.g., Organic Carbon, textural fractions). To overcome this problem, pedotransfer functions [START_REF] Rawls | Estimation of soil water retention properties[END_REF][START_REF] Al Majou | Prediction of soil water retention properties after stratification by combining texture, bulk density and the type of horizon[END_REF] can be used to estimate the specific water content from available soil properties, which has allowed the production of SAWC maps [START_REF] Leenaars | Mapping rootable depth and root zone plant-available water holding capacity of the soil of sub-Saharan Africa[END_REF][START_REF] Dobarco | Pedotransfer functions for predicting available water capacity in French soils, their applicability domain and associated uncertainty[END_REF]. However, these functions convey a great amount of uncertainty that could generate significant errors in SAWC maps [START_REF] Dobarco | Pedotransfer functions for predicting available water capacity in French soils, their applicability domain and associated uncertainty[END_REF]. Therefore, the increase in well-characterized sites with regard to SAWC is a prerequisite for a significant improvement of SAWC maps.

Using surrogates of the vegetal response to characterize SAWC across a great number of sites is a promising perspective. Remote sensing approaches that involve vegetation indices have been proposed. For example, [START_REF] Araya | Phenologic metrics derived from MODIS NDVI as indicators for Plant Available Water-holding Capacity[END_REF] proposed to directly test the multidate Normalized Difference Vegetation Index as a surrogate for the dynamic response of plants to soil functions, especially SAWC. A relationship between evapotranspiration-based covariates extracted from ASTER satellite imagery and soil depth, a first order parameter for SAWC calculation, was found in vineyards [START_REF] Taylor | The utility of remotely-sensed vegetative and terrain covariates at different spatial resolutions in modelling soil and watertable depth (for digital soil mapping)[END_REF].

In the same way, the carbon isotope ratio ( δ 13 C) is largely known as an indicator of plant water status and has been tested on different species such as wheat [START_REF] Merah | Relationships between carbon isotope discrimination, dry matter production, and harvest index in durum wheat[END_REF], conifers [START_REF] Warren | Water availability and carbon isotope discrimination in conifers[END_REF]vineyards (Gaudillère et al., 2002). In the case of vineyards, many studies have demonstrated the linear relationships between δ 13 C measured in berries at harvest and the minimal values of pre-dawn leaf water potential during ripening.

Van [START_REF] Van Leeuwen | The assessment of vine water uptake conditions by 13C/12C discrimination in grape sugar[END_REF] measured the δ 13 C in berries from 9 closed vineyards with different soils during contrasted years. They found a linear relationship between δ 13 C and the minimal values of pre-dawn leaf water potential during ripening (R²= 0.81). The soils and the years explained a large part of the variance. Gaudillère et al. (2002) found a linear relationship in case of various grapevine genotype (e.g. Cabernet Sauvignon, Cabernet Franc and Merlot). They also tested 31 grapevine varieties within a same growing condition and they measured δ 13 C values from -21.6 (Riesling) to -24.9 (Muscat). However, 24 varieties ranged between -22.5 and -23.8. Gomez-Alonso and Garcia-Romero (2010) found lower differences between 8 varieties in a same growing condition, from -20.5 (Airen) to 21.6 (Sauvignon blanc). [START_REF] Santesteban | Application of the measurement of the natural abundance of stable isotopes in viticulture: a review[END_REF] reviewed the δ 13 C datasets from the literature and proposed δ 13 C threshold values that correspond to significant differences in vineyard water status during the ripening period.

The low cost of δ 13 C measurements that allows the collection of large samplings was exploited in some studies. A large set of δ 13 C measurements was used to produce a spatial model of vine water status at the plot scale [START_REF] Herrero-Langreo | Mapping Grapevine (Vitis vinifera L.) Water Status during the Season Using Carbon Isotope Ratio (δ 13 C) as Ancillary Data[END_REF]. Some studies focused on the use of δ 13 C as an indicator of functional parameters in relation to vine water status. Guix-Hebrard et al. (2007) However, to our knowledge, δ 13 C measurements have still not been correlated with SAWC measurements. The vine water status via the predawn leaf water potential is known to be correlated to the fraction of transpirable soil water (FTSW) [START_REF] Pellegrino | Relationships between plant and soil water status in vine (Vitis vinifera L.)[END_REF], which, during the driest growing seasons, may be considered as a surrogate for SAWC in rainfed areas. Therefore, a relationship between easily accessible δ 13 C measurement and the SAWC is conceivable. Moreover, in the case of vineyards, the roots of grapevines are generally established throughout the entire horizons of soils, except for the limiting specific conditions (hydromorphic horizons, cemented horizons or C horizons with chemical or physical limitations), despite the high dependence of grapevine rooting patterns on the rootstock.

The aim of this paper is to directly test δ 13 C measured in vineyards at the harvest time as a surrogate of a large range of measured SAWCs in different soils of the Languedoc area.

Four years were monitored to investigate different soil water conditions during the growing seasons of the vineyards.

Materials and methods

2.1Study areas

The 21 sites that constitute the experimental dataset of this study were located in two study areas, both included in the vineyard plain of Languedoc in southern France (figure 1). The first study area is the Peyne River catchment which includes 13 sites. The second one is located near Narbonne close to the sea and includes 8 sites. The elevation ranges from 5 m (Pech Rouge) to 340 m (northwest of the Peyne area). The landscape has gentle landforms.

The grapevine varieties and the agricultural practices are representative of the region. The precipitation conditions were monitored during 25 years both in the Peyne catchment and in Pech Rouge station. The annual precipitation of 628 mm for the Peyne catchment and 562 mm for the Pech Rouge station are unevenly distributed throughout the year, with major precipitation occurring in autumn and spring. The annual reference evapotranspiration is 1109 mm. The mean maximum temperature is approximately 15°C in January and 30°C in July/August. The catchments present a typical Mediterranean hydrological response, with the potential annual water storage mainly dependent on the annual precipitation and the occurrence of extreme runoff events, which are not favourable for the water infiltration.

Therefore, the annual water balance highly varies between years.

The soil pattern of the Peyne catchment arises mainly from variations in lithology, and the main soil characteristics depend on the type of parent material (figure 1). The entire valley is underlain by heterogeneous Miocene marine calcareous sandstone and lacustrine limestone, which form the parent material of several types of soil, including calcaric leptosols, calcaric regosols, and calcisols (IUSS working group WRB, 2015). These Miocene sediments are partly overlain by successive alluvial deposits ranging from Pliocene to Holocene, and they differ in their initial nature and in the duration of weathering conditions. Therefore, these sediments have produced intricate soil patterns that include a great range of soil types such as calcisols, endogleyic calcisols, luvisols (chromic), and fluvisols. Recent volcanic activity and local transport of colluvium material along slopes have added to the complexity of the soil pattern. Consequently, the soils of the valley present contrasting characteristics in terms of texture, stoniness and soil depth, which determine their SAWC.

The second study area corresponds to the experimental station of INRA Pech Rouge located in the "La Clape" massif, a small Pyrenean thrust sheet composed of Cretaceous marine deposits. Contrasting sites were chosen among different available SAWCs. The main soils were developed over interbedded micritic limestones and orbitolina clayey limestones. The soils were generally thin over the limestones, with a high content of coarse fragments (Leptosols). In the bottom part of the fields, there were important accumulations of sediments, and the soil depth increased (Calcisols). <Figure 1 here>

2.2Site sampling

The sites were chosen to be representative of the diversity of soil characteristics, especially soil depth and SAWC (table 1 andfigure 1). A total of 13 sites were located in the Peyne catchment to calibrate the relations, and 8 additional sites were located in the Pech Rouge INRA station to validate the relations with independent sites. A site corresponds to approximately 15 m² (9 vines) within the vineyards to limit the spatial variability of soil properties and assign a SAWC to a site with a maximum of precision. Regarding agronomical aspects, the vineyards were chosen (i) to be representative of the regional vineyards and (ii) to avoid the situations where the relation between the SAWC and the vine water status may be disturbed (e.g., irrigated zones; young vineyards with insufficient root systems). The vineyards were 15-20 years old and without irrigation. The plantation density (4000 plants/ha), the trellising (2 stages), the pruning system (double cordon) and the number of buds (16 to 20) were the same at all sites. However, the variety differed, with Syrah (sites 6,9), Cabernet Sauvignon (sites 4,10,18), Sauvignon blanc (site 14), Grenache noir (site 5,8), and Merlot (sites 2,3,7,11,12).

2.3Soil survey

Soil pits were dug near each selected site during the winter of 2016 and the soil morphological parameters were observed in the field (soil depth, structure, colour, stones, roots abundance) according to the guidelines for soil description [START_REF] Fao | Guidelines for soil description[END_REF]. The soil horizons were determined in relation to these descriptions, and bulk densities (ρb) were measured by core sampling with 100 cm 3 stainless-steel cylinders [START_REF] Blake | Bulk density[END_REF] with 6 replicates per horizon. ρb was determined as the ratio between the dry soil mass and the total core sampling volume. Moreover, each sample was sieved to extract the coarse fragments (e.g. >2mm), and the bulk density of the fine earth (ρbFE) was determined as the ratio between the dry soil mass without the coarse fragments and the total core sampling volume without the volume corresponding to the coarse fragments. This volume was calculated from the mean bulk density of the coarse fragments (ρbCF) according to the type of pebbles already measured in the Peyne catchment and in Pech Rouge station (e.g. old alluvial pebbles 2.8 and limestone 2.5). Undisturbed soil samples of over 500 g were taken in each horizon for characterisation of the specific water retention at -33 kPa (field capacity) and -1500 kPa (wilting point) according to the pressure chamber method [START_REF] Klute | Water retention: Laboratory methods[END_REF].

Disturbed soil samples localized in the same horizons were used for classical texture and coarse-fragment analysis. The samples were sieved to separate pebbles greater than 2 mm in diameter from the fine earth. The particle size distribution was analysed following the destruction of organic matter and dispersion with sodium hexametaphosphate (AFNOR, N FX 31-107). The clay (< 2 µm) and silt (2-50 µm) contents were quantified by sedimentation, and sand (50-2,000 µm) was measured via sieving. The detailed results of the soil survey are summarized in Table 1.

2.4Soil available water capacity (SAWC)

The SAWC of each horizon was calculated based on equation (1). The morphological variables that impact the rooting were taken into account for the calculation of the actual SAWC. In the case of low content of coarse fragments (<10%), their contributions to the SAWC were neglected. However, in the case of high content of coarse fragments (Pech Rouge sites), additional SAWCs were calculated from the water content measured within the coarse fragments [START_REF] Tetegan | The contribution of rock fragments to the available water content of stony soils: Proposition of new pedotransfer functions[END_REF]. Considering that the 15-20 year-old studied vineyards had sufficient time to develop their root system, horizons without living roots did not contribute to the SAWC. The different causes were examined. Site 2 presented a deep horizon (1.95 -2.70 m) without roots due to (i) seasonal waterlogging within the horizon and (ii) vertic properties not suitable for roots. Site 4 presented a large soil depth but the deep horizons were temporary waterlogged, and no roots were observed. Horizon C of site 8 presented a high content of powder of calcium carbonate, and no roots were observed. The calculation of SAWC and general soil data are given in Table 1. samples were ground at the laboratory, and 2 ml samples were centrifuged and oven dried.

The resulting powder was analysed by a continuous-flow isotope ratio mass spectrometer (ISOPRIME, GV Instruments, Manchester). δ 13 C values are expressed with reference to the PeeDeeBelemnite (PDB) standard [START_REF] Farquhar | Carbon isotope discrimination and photosynthesis[END_REF]. In the case of grapevines, [START_REF] Santesteban | Application of the measurement of the natural abundance of stable isotopes in viticulture: a review[END_REF] proposed a correspondence between δ 13 C and the water deficit via the vine water status measured in a set of studies. The water deficit is considered as weak or null with δ 13 C lower than -26‰; conversely, the water deficit is severe with a δ 13 C higher than -24‰.

2.6Experimental protocol

The Peyne sites were first chosen to calibrate the relationship between δ 13 C and SAWC at the site scale. The relationships were separately analysed for each successive year to enable discussion of the results according to the specificity of each vintage. A classical leave-one-out cross validation was applied to validate the relationship on the Peyne sites for each year.

Three years (2015, 2017 and 2018) were chosen to calculate the δ 13 C mean for each site within the Peyne catchment and calibrate a new multidate relationship between δ 13 C and SAWC. This relationship was validated with the independent Pech Rouge sites using classical figures-of-merit, coefficients of determination (R²) and Root Mean Square Errors (RMSE).

Results

3.1Precipitation

The four years exhibited large variations of annual precipitation in the Peyne catchment The δ 13 C mean results from the Peyne site showed significant differences between years (Table 2). The ranges of values are in accordance with those found by [START_REF] Guix-Herard | Influence of watertable depths on the variation of grapevine water status at the landscape scale[END_REF] within the same region. As expected, the driest year (2016) presented a significantly higher δ 13 C mean and the highest maximum value. However, the minimum value measured in 2016 was comparable to that in the other years. The years 2017 and 2018 had lower δ 13 C values.

The δ 13 C measured values in the Pech Rouge sites during 2018 were significantly higher than those measured in the Peyne sites.

<Table 2 here>

3.3Relationship between δ 13 C and SAWC

The linear relationships between SAWC and δ 13 C were significant for the Peyne sites regardless of years (Figure 3). The increase of δ 13 C always corresponded to a decrease of SAWC. Regarding the cross validation, the year 2015 presented the lowest errors of prediction, which were of the same order of magnitude as the errors of the local determinations of SAWC from field laboratory measurements.

<Figure 3 here>

The errors were more important in 2017 and 2018, although the general trend was conserved. Conversely, the relationship during the year 2016 was different. δ 13 C values corresponding to sites with a medium SAWC (100 -200 mm) increased, particularly for sites 6,8,10,18. The sites with high (11,12) or low (3,5) SAWC had a relative stability through the years. Regarding the trend of the relationship, the measured δ 13 C for site 5 was always lower than expected.

<Figure 4 here>

For each site, the means of δ 13 C measured during 2015, 2017 and 2018 were calculated and compared with the SAWCs (figure 4). The new calibration over the Peyne sites during the three years presented better figures of merit than each separated year. Moreover, the successful validation of this new relationship with additional independent sites (Pech Rouge)

during 2018 confirmed the ability to predict SAWC from a punctual δ 13 C measurement. The RMSE decreased to 32 mm for the year 2018, which corresponds to satisfactory prediction.

However, the predicted SAWC values larger than 100 mm were significantly higher than the measured ones.

Discussion

4.1Relationship between SAWC and vineyard water status

The investigated situations were chosen to represent a large variety of soil depth and soil characteristics in relation to the SAWC, including soils with shallow groundwater and different rooting constraints, as reported by [START_REF] Leenaars | Mapping rootable depth and root zone plant-available water holding capacity of the soil of sub-Saharan Africa[END_REF]. Despite these greatly different situations, satisfactory linear relationships were found between δ 13 C and SAWC during each year. These results are new. Previously, δ 13 C as a surrogate for the vineyard water status was largely used to precisely determine soil-related terroir factors [START_REF] Van Leeuwen | Vine water status is a key factor in grape ripening and vintage quality for red Bordeaux wine. How can it be assessed for vineyard management purposes ?[END_REF]2018). The vineyard water status depends on the FTSW present within the rooted horizons.

During the driest growing seasons, the vineyard soil provides storage water in relation to its SAWC, considered as the maximum stored water within the soil. Our results show a relationship between the δ 13 C plant surrogate and the SAWC. The main hypothesis mainly relates to the fact that vine roots infiltrate the horizons included with the SAWC calculation.

4.2Climatic determinant of the SAWC predictions

The large variations of annual precipitation during the 4 years produced a variation of the water supply during the growing season mainly via the soil water storage before bud break.

The 2016 precipitation was largely below the 25-year annual precipitation average, and the water recharge before bud break can be considered incomplete. Conversely, the recharge during the other years was higher and corresponded to at least 200 mm.

Except for the year 2016, the trend of the relationship between δ 13 C and SAWC was conserved despite differences in precipitation that occurred during the growing season. The linear relationships present a relative stability, particularly with extreme situations. Higher SAWCs correspond to sites with sufficient water recharge to preserve a low vine water stress during the ripening, regardless of year. Conversely, lower SAWCs correspond to sites with shallow soils or soils with a rooting limit. The water recharge is not sufficient for the years, and the sites always have high δ 13 C values. The variations between years are significant for the sites with a medium SAWC and are more sensitive to precipitation during the summer period. For example, site 7 (121 mm) provided a very low δ 13 C due to a storm event at the beginning of August 2017. The year 2016 corresponds to a severe water deficit due to an incomplete water recharge of the SAWC. Therefore, the relationship from the 2016 dataset underestimates the SAWC.

4.3Vine variety determinant of δ 13 C variability δ 13 C can be prone to variations across the different vine varieties, related to different sensitivities to water stress [START_REF] De Souza | Impact of deficit irrigation on water use efficiency and carbon isotope composition (δ 13 C) of field-grown grapevines under Mediterranean climate[END_REF]. In this case study, merging five different vine varieties could constitute a disturbing effect. Indeed, the δ 13 C values measured in two sites with the same SAWC but with a different variety do not precisely express the same corresponding minimal values of pre-dawn leaf water potential. The specific driest year of 2016 could also exacerbate the variations due to the variety [START_REF] De Souza | Impact of deficit irrigation on water use efficiency and carbon isotope composition (δ 13 C) of field-grown grapevines under Mediterranean climate[END_REF].

However, the impact of vine variety on the relation between δ 13 C and pre-dawn leaf water potential could be strongly questioned. On one hand, the calibration of the linear relationship for the same grapevine variety between δ 13 C and pre-dawn leaf water potential shows relatively scattered data. For example, the linear relationship explained only 70% of the variance in the case of the Tempranillo variety [START_REF] Santesteban | Carbon isotope ratio of whole berries as an estimator of plant water status in grapevine (Vitis vinifera L.) cv. 'Tempranillo[END_REF]. [START_REF] Guix-Herard | Influence of watertable depths on the variation of grapevine water status at the landscape scale[END_REF] found only 80% of the explained variance for Syrah in the same Peyne valley. Additionally, the relationship from four different varieties showed 95% of the explained variance (Gaudillère et al., 2002). Gomez-Alonso and Garcia-Romero (2010) tested eight varieties in the same site with the same soil conditions. The standard deviation of δ 13 C measurement was only 0.7. Restricting δ 13 C to a unique vine variety is therefore not recommended since the added value to the δ 13 C -SAWC relationship is far from being demonstrated, whereas it may induce sampling difficulties related to the exclusive locations of each vine variety in specific pedo-climatic situations.

4.4Added value of a multidate approach

The climatic variability and intrinsic δ 13 C variations were combined with a relationship between a mean of each annual measurement of δ 13 C and SAWC. The results outperformed the relationships for each study year, excluding 2016. The relationships did not change for the sites with extreme SAWC, high or low. Conversely, the δ 13 C mean for the site with medium SAWC moderated the interannual variability. This integrated relationship was successfully tested for the independent Pech Rouge sites. The first analysis of figure 4 (right) seems to show an overestimation of SAWC > 100 mm. The measurement of SAWC in the case of thin soils with high coarse fragment content and with cracked bedrock is questionable. The contribution of coarse fragments to the water storage was included in the SAWC. However, the measurements of specific water content in coarse fragments were disturbed by the time of water extraction and pore connectivity. The lateral variability of cracks is not visible with punctual pit observations, especially in thin soils over limestones. In this specific case, δ 13 C probably constitutes a better integrated parameter to estimate the real SAWC than the conventional SAWC measurement.

4.5Limitations and further approaches

The study of four contrasted consecutive years shows that the use of the δ 13 C as a surrogate of SAWC is mainly dependent on the water recharge before bud break especially for the low SAWC. Furthermore, this surrogate cannot be applied in irrigated crops, which disconnect the SAWC and the water status of the plant. The importance of the climate-dependent water status argues for consolidating the relationships with additional study years with atypical water recharge, which was not monitored in this work. For example, a large amount of rain during the summer would dramatically decrease the δ 13 C .

The distribution of SAWC for the Peyne sites had an effect on the relationships between δ 13 C and SAWC. Only two sites presented a SAWC higher than 250 mm, and the majority of the Peyne sites had medium SAWC values between 100 and 200 mm. The relationship was more sensitive to extreme SAWC and future sites with lower SAWC and higher SAWC in the Peyne catchment might ameliorate the genericity of the relationship. In the same way, the validation in Pech Rouge suffered a lack of sites with high SAWC.

The relation between δ 13 C and SAWC was established in restricted crop situations, namely, rainfed vineyards. δ 13 C variations on other plants than vineyards have been demonstrated to be reliable to water stress. The present study could be extended to other land uses, with care in characterising the maximum rooting depth, which could induce underestimation of the SAWC, particularly in the case of annual plants.

Beyond the above-evoked limitation, this work demonstrated that δ 13 C can be considered in some particular landscapes as a simple and inexpensive surrogate for determining SAWC. It could therefore be used in further digital soil mapping (DSM) approaches that deal with SAWC as new soil input for calibrating or validating the DSM models. In addition to considerably increasing the density of measurement, the use of δ 13 C would lead to better accounting of the contribution of deep horizons in the case of perennial plants.

Conclusions

This work demonstrated that the δ 13 C values of grapes can be considered as a simple and inexpensive surrogate for determining SAWC in rainfed vineyards. Moreover, the use of proxies based on the perennial plant response, such as δ 13 C, provides first order information for comparison with theoretical SAWC, especially for the analysis of the contribution of deep horizons. Successive monitored years, with the means of each annual δ 13 C, combined climatic variability and intrinsic δ 13 C variations. The relations did not change for the sites with extreme SAWC, high or low. Conversely, the δ 13 C means for the sites with medium SAWC moderated the interannual variability. This integrated relationship between the δ 13 C means and SAWC was successfully tested for 8 independent sites. However, specific years without sufficient soil water recharge are not appropriate for the use of a SAWC surrogate. Finally, extensions of this study to other agro-systems are required to better define the potential area of use of δ 13 C.

data and his help in Pech Rouge site. The authors thank particularly P. Tillard for the δ 13 C analysis, J.L. Belotti for his help in soil analysis and D. Fages for the field sampling.

  used measured δ 13 C for revealing the influence of water table depth on the grape maturation. Van Leeuwen et al. (2018) considered δ 13 C as a highresolution tool among a set of indicators for characterizing vineyard terroirs. Costantini et al. (2010) delineated the Sangiovese terroir with a combination of proximal soil sensing and the measurement of δ 13 C in Sangiovese wines.

  δ 13 C sampling and analysis A total of 100 berries were collected at the harvest time from the 9 vines at each site during 4 successive years(2015)(2016)(2017)(2018) for the Peyne sites. The sampling dates varied between the 25 th August (2016), and the 10 th September (2015), depending on the vine variety and the climate of the year. The samples for the Pech Rouge site were collected only in 2018. The

(

  figure 2). Only the 2015 precipitation was close to the 25-year average precipitation. The 2016 precipitation was largely below this average. 2017 and 2018 precipitations exceeded the 25-year average precipitation. Although the 2017 growing season was the driest among the four years, most of the 2017 precipitation events occurred before bud break and secured the soil water storage. The precipitations during 2018 in Pech Rouge station were also upper than the 25-year average precipitation.

Table 2 :

 2 The whole ∆C13 results during the 4 years Differents letters denote statistically significant differences between means (ANOVA and Tukey's HSD based on the Student distribution, at P<0.01)

	∆C13	Peyne Catchment

Acknowledgements

This study was supported by the project RUEDESSOL financed by the french national research agency (ANR contract number 14 CE010011). The authors thank N. Saurin for the