domain: scco sdv

text:
Davranche Karen

Giraud Dorian

Hays Arnaud

Gajdos Thibault

High-intensity physical activity enhances cognitive decision processes

Keywords: acute effect, exercise-cognition interaction, perceptual decision-making task, postexercise

The present study aims at deciphering the effect of a high-intensity interval exercise on cognitive processes involved in perceptual decision-making through computational modelling. To that end, participants performed a perceptual decision task (RDK) before and after a high-intensity interval exercise (8 x 5min, 85 ± 8 % HRmax). Cognitive processes were measured by best-fitting parameters of a drift diffusion model (DDM) to behavioral data (accuracy and response times). Drift Diffusion modeling revealed faster non-decisional time and more efficient drift rate suggesting a better sensory encoding, a greater allocation of attentional resources and a faster processing speed following acute exercise.

High-intensity physical activity enhances cognitive decision processes

April 15th, 2019. Notre-Dame is burning. A fireman eventually reaches the top of the tower. He now has to decide on which side the fire should be attacked first. Will his decision be impacted by the intense physical effort he just made? And if so, which precise underlying cognitive processes are altered? Meta-analytic studies actually suggest that acute (single) bout of physical activity enhances performances in various cognitive tasks (e.g., Psychomotor Vigilance Task, Flanker task, Critical Flicker Fusion). However, these results mainly concern moderate physical exercise intensities, which involves different cellular and molecular changes than intense physical activity such as those provided by the fireman [START_REF] Herold | Dose-Response Matters! -A Perspective on the Exercise Prescription in Exercise-Cognition Research[END_REF], and therefore might not have the same impact on cognitive processes. Moreover, the underlying cognitive mechanisms have so far received less attention (e.g., [START_REF] Pontifex | A primer on investigating the after effects of acute bouts of physical activity on cognition[END_REF][START_REF] Sudo | The effects of acute highintensity aerobic exercise on cognitive performance: A structured narrative review[END_REF].

Assessing the impact of physical exercise on cognitive processes is challenging because they are not directly observable. The cognitive computational approach provides a way to tackle this issue. It provides theoretically grounded models, whose parameters represent latent cognitive processes and can be inferred from behavioral data. Among the cognitive computational models, the Drift Diffusion Model (DDM, [START_REF] Ratcliff | A theory of memory retrieval[END_REF]) has proven to be particularly fruitful [START_REF] Ratcliff | Diffusion Decision Model: Current Issues and History[END_REF]. It belongs to the wide class of Evidence Accumulation Models (EAM, [START_REF] Bogacz | The physics of optimal decision making: A formal analysis of models of performance in two-alternative forced-choice tasks[END_REF], that postulate that decisions result from the continuous accumulation of a stochastic evidence until a given amount of evidence is attained. The basic DDM contains four parameters, each related to a different cognitive process: the starting point of the accumulation process (z), which represents the bias of the decision; the drift rate of the accumulation process (v), which depends on the difficulty of the task or on the subject's ability; the distance between the bounds corresponding to each response (a), which represent the subject's cautiousness (the larger a, the more accurate and slower the responses); and a non-decision time (Ter), that encompass the encoding of relevant information and the decision execution processes.

In this study, we relied on the DDM to decipher the impact of high-intensity interval exercise on cognitive processes involved in a perceptual decision-making task. Specifically, we used the random dot motion task (RDK), for which the DDM has consistently provided excellent accounts of behavioral data. Behavioral data were collected before and immediately after an intense aerobic physical activity generating a stress leading to noteworthy physiological repercussions notably on heart rate, blood lactate and glycemia levels.

Method

Participants

Twenty young adults (one women; age range: 18-34; mean age: 24 years) voluntarily participated in the experiment. All participants were healthy and practiced regular physical activities (peak oxygen uptake: 55 ± 7 mL kg -1 min -1 ; maximal heart rate: 185 ± 8 bpm). This sample size was determined based on prior studies reporting significant effects on cognitive performance using comparable physiological intensity (range 16 -19 subjects; [START_REF] Peirce | PsychoPy2: Experiments in behavior made easy[END_REF] [START_REF] Ando | Cognitive Improvement After Aerobic and Resistance Exercise Is Not Associated With Peripheral Biomarkers[END_REF][START_REF] Ramdani | Action monitoring fails when motor execution is too fast: no time for correction[END_REF]. All participants were fully informed about the study and signed a written informed consent before inclusion. The study was approved by the Ethics Committee for Research in Science and Technology of Physical Sports Activities (IRB00012476-2022-21-01-148).

Apparatus

The experiment was programmed in Python, using components of the PsychoPy toolbox [START_REF] Peirce | PsychoPy2: Experiments in behavior made easy[END_REF], and was run on a PC computer natively running Windows 10.

Responses were communicated to the computer by means of two buttons (one for each hand).

Random dot motion task (RDK)

The task requires participants to determine the global direction of a random dot kinematogram featuring a proportion of dots moving coherently in the left or right signal direction. Each trial started with the presentation of the random dot motion stimulus, which remained on the screen until the participant responded. A response time deadline was set to 5 s. The interval between the response to the stimulus and the next trial was 1.5 s. The coherence parameter (proportion of dots moving in the same direction) was set for each participant at the beginning of the experiment according to a 2 up and 1 down staircase method lasting 30 trials. White dots were presented within a virtual 12.6° circular aperture centered on a 24.8° 3 13.9° black field. Each dot was a 4 x 4 pixel (0.05° square), moving at a speed of 8°/s. Dot density was fixed at 16.7 dots/deg2/s. Random dot motion was controlled by a white noise algorithm [START_REF] Pilly | What a difference a parameter makes: A psychophysical comparison of random dot motion algorithms[END_REF].

Procedure

Participants visited the laboratory on three occasions (a preliminary session, a familiarization session, and an experimental session) at least 48h apart. Participants were seated on an upright cycle ergometer (Lode, Excalibur, Netherland), which included two thumb response buttons on the right and left handle grips. A screen computer was placed at eye level in front of the participant at 1m. The preliminary session was carried out to individually adjust the difficulty of the cognitive task, determine the V ̇O2max and estimate the power associated to the ventilatory thresholds [START_REF] Wasserman | Principles of Exercise Testing and Interpretation: Including Pathophysiology and Clinical Applications[END_REF] (see Table 1 for details). Participants were seated on the cycle ergometer (Lode Excalibur Sport, Groningen, The Netherlands), fitted with a facemask to measure gas exchange data (Innocor CO, Cosmed, Italia) and a heart rate monitor. The incremental cycling exercise to exhaustion test started at an initial power level defined according to the participant's level (100 watts for non-cyclists and 150 watts for cyclists) and increased by 30 watts every 2 minutes until exhaustion. The end of the test was determined by volitional cessation of exercise or failure to maintain pedal cadence above 60 rpm despite strong verbal encouragement. During the first step of this maximal test, 30 trials of the RDK task was performed to set up the consistency parameter according to a staircase procedure.

Table 1. Anthropometric and physiological characteristics of participants. PSV: Power corresponding to the ventilatory threshold, HIE: high-intensity exercise, V ̇O2max: maximal oxygen consumption.

A familiarization session (about 1 250 trials), identical in all respects to the following experimental cognitive session, was carried out in order seemed to minimizing potential of learning or practicing effects, avoiding individual differences inherent to a design protocol, and excluding day-to-day variations of performance. During this session, participants completed the cognitive task at rest before and after the completion of the high-intensity interval exercise (lasting about 48 min), then the exercise started with 30s step performed at 75 Watts, and the intensity gradually increases in power up to 90% of the first ventilatory thresholds (SV1). This fairly low intensity was deliberately chosen in order to consider the additional physiological cost induced by the cognitive task. At this intensity, corresponding to an individual heart rate range between 62-97% HRmax, participants carry out 5 min cycling interspersed with 1 min active recovery. The RDK task was performed continuously while cycling (average 130 trials, ranged from 68 to 176 trials). Participants had to identify the motion direction (leftward vs. rightward) by pressing the corresponding button with their left or right thumb. They were instructed to respond as quickly and accurately as possible.

Capillary blood samples from the fingertip were taken just before and after exercise to measure lactate and glucose. The skin was cleaned with alcohol, allowed to dry and then punctured with an automated lancet. Blood sample was analyzed using Biosen blood analyzer (EKF diagnostics, UK). During the experimental session, participants completed the exact same protocol.

Data Analyses

The analyses presented here focus exclusively on pre-and post-exercise data collected at rest. The data recorded during high-intensity exercise, compared to after exercise, induces very different physiological responses which implied other cognitive processes. They will thus be the object of another study. Anticipations (RTs < 150 ms; 0.11 %) were discarded from all analyses. Two subjects did not perform the perceptual task appropriately (i.e., percentage of accuracy under 50%) and were excluded from the initial sample of 22 participants.

The Drift Diffusion Model (DDM) parameters were estimated using a hierarchical Bayesian procedure implemented with the DMC package [START_REF] Heathcote | Dynamic models of choice[END_REF] for the R software (R Core Team, 2016). Specifically, we considered the DDM with inter-trial variability in the drift rate (sv) and the starting point (sz), and let the drift (v), threshold (a)

and nondecision time (Ter) vary across conditions. We used truncated normal priors at the individual level (bounds: [0,5] for a, [-5,5] for v, and [0,1] for all other parameters). At the group level, we assumed broad truncated normal distributions for the means and uniform distribution on [0,1] for the standard-deviations. In order to fit the model to the data, we used the two-steps procedure described by [START_REF] Heathcote | Dynamic models of choice[END_REF]. In a first step, we fitted each participant's data individually. The averaged resulting parameters were used in a second step as starting values for hierarchical sampling. The quality of the fit was evaluated by visually inspecting Markov chain Monte Carlo chains, comparing predicted data according to best fitting parameters to actual data, and computing Brooks and Gelman's (1998) R statistics (see Supplemental Data). Finally, we tested the presence of an effect of the condition (before vs.

after exercise) on the parameter values by computing Bayesian p values [START_REF] Heathcote | Dynamic models of choice[END_REF].

Results

Physiological measures

The intensity set up during the high-intensity interval exercise corresponds to 85 ± 8 % of the maximal hearth rate (HRmax) (range from 62 to 97 % of HRmax). Paired t-test showed higher heart rate at the end of the 8 th block (159 ± 16 bpm) compared to the 1 st block (151 ± 16 bpm, t = -4.71, p < .001, d = 19, CI [-11.97, -4.60]) showing a classical derive of heart rate through the high-intensity interval exercise (Figure 1). Blood sample analyses confirmed the physiological repercussions of the protocol on lactate and glucose levels. Following exercise lactate concentration was higher (+2.2 ± 0.7 mml -1 , t = -4.77, p = 2.54e-05, df = 39, CI [-2.28, -0.92]) and glucose was lower (-0.6 ± -1 x 10 -3 mml -1 , t = 3.85, p < .01, df = 39, CI [0.28, 0.92]) than before exercise.

DDM parameters

Visual inspection of Markov chain Monte Carlo chains (Supplemental Data, graph 1), comparison between predicted and actual data (Supplemental Data, graph 2), and Brooks and Gelman's (1998) R statistics (Supplemental Data, table 4) show that the estimation procedure was satisfactory.

We investigated which component of the perceptual decision-making process was impact by exercise by comparing the best-fitting parameters of the DDM across conditions at the group level (detailed results of the fitting procedure are available in the Supplementary Data). Table 3 shows the parameter estimates before and after exercise and the probability value associated: the drift v rate increases significantly following exercise compared to before, the non-decision time Ter decreases by about 70 ms, and the boundary a increases. Additional simulations allow to quantify the impact of the variation of the drift and the threshold. The increase in the drift and the threshold (drift rate: +0.010, threshold: + 0.0044) have opposite effects of similar size on RT (about 30 ms), and very small effects on accuracy.

Table 3. Diffusion model best-fitting parameters before and after intense exercise, with 95% credible intervals.

Discussion

The present study aimed at deciphering the subsequent effect of a high-intensity interval exercise on cognitive processes involved in perceptual decision-making. To that end, participants performed a perceptual decision task (RDK) before and after a high-intensity interval exercise (i.e., 8 x 5min, 85 ± 8 % HRmax response times). We found that high-intensity interval exercise notably modulates nondecisional and decisional processes immediately following physical activity.

Specifically, we observed a diminution of non-decision time (Ter), which measures the mean duration time required for processes unrelated to the decision process in perceptual decision-making task. This observation is consistent and comparable with the results reported by [START_REF] Davranche | Information processing during physical exercise: a chronometric and electromyographic study[END_REF][START_REF] Davranche | Physical exercise facilitates motor processes in simple reaction time performance: An electromyographic analysis[END_REF] showing a facilitation of non-decisional processes during a single bout of moderate physical activity. Using the decomposition of reaction time, with respect to the electromyographic activity of response agonists (a chronometric and electromyographic study), these studies actually showed that exercise enhances motor processes involved in response execution as well as peripheral sensory processes involved in early sensory operations. Additionally, we observed an increase of the drift rate (v) after completion of high-intensity interval exercise. This finding is in line with the fact that (i) high-intensity physical activity is positively associated with changes in brain-indices associated with arousal levels and attention allocated to the task [START_REF] Du Rietz | Beneficial effects of acute high-intensity exercise on electrophysiological indices of attention processes in young adult men[END_REF] and

(ii) vigilance state induced by sleep-deprivation modulates the drift rate in DDM [START_REF] Ratcliff | Diffusion model for one-choice reactiontime tasks and the cognitive effects of sleep deprivation[END_REF].

These results are fully consistent with the increase in central nervous system excitability associated with the release of central catecholamines during exercise and more particularly during such high-intensity exercise. The massive release in catecholamines renders the organism more receptive to sensory information [START_REF] Moxon | Influence of norepinephrine on somatosensory neuronal responses in the rat thalamus: A combined modeling and in vivo multi-channel, multi-neuron recording study[END_REF] and more prone to react [START_REF] Davranche | Transcranial magnetic stimulation probes the excitability of the primary motor cortex: A framework to account for the facilitating effects of acute whole-body exercise on motor processes[END_REF]. Moreover, other peripheral biomarkers specific to high-intensity exercise such as circulating lactate [START_REF] Hashimoto | Effect of Exercise on Brain Health: The Potential Role of Lactate as a Myokine[END_REF], blood glucose, circulating cortisol level or neurotrophic factors could also contribute to cognitive changes in a synergistic way. All these adaptive modulations (for a review see, [START_REF] Singh | The effects of acute aerobic exercise on the primary motor cortex[END_REF] most likely participate to enhance motor cortex sensitiveness to upstream influences, thereby increasing sensory sensitivity (promoting stimulus encoding), raising arousal level (accelerating processing speed) and modulating corticospinal excitability (promoting the execution of the response).

We also observe a modulation of the decision threshold (a), with more cautious decisions after exercise. This effect is, however, statistically more fragile. To the best of our knowledge, there is little reason to expect that physical exercise should modulate speedaccuracy trade-off. For instance, neither the bromocriptine (a dopamine receptor agonist, [START_REF] Winkel | Bromocriptine does not alter speed-accuracy tradeoff[END_REF], nor sleep deprivation [START_REF] Ratcliff | Diffusion model for one-choice reactiontime tasks and the cognitive effects of sleep deprivation[END_REF]

Figure 1 .

 1 Figure 1. Heart rate (bpm) evolution during the high-intensity interval exercise, lactate and glucose levels (mml.L -1 ) before and after exercise. Error bar represent ½ SD.

Graph 2 :

 2 Fit quality for Accuracy rate (left) and Responses time (right) before and after highintensity interval exercise. Note. Open points: data; solid points: model prediction; error bars show the corresponding 95% credible intervals.

Table 2 .

 2

			Before	After
	Percentage of correct response	87% (34) 87% (34)
	Mean RT	RT correct RT error	0.99 (0.63) 0.92 (0.63) 1.4 (0.79) 1.3 (0.79)

Table 2 .

 2 Response times in second and percentage of accuracy averaged across subjects before and after highintensity intermittent exercise. Standard deviation are in parentheses.

  were found to modulate decision threshold. Therefore, the robustness of the observed modulation of decision threshold after high intensity exercise, as well as the potential underlying physiological mechanisms remain open to further investigations.Most studies aiming at better understanding the acute effects of physical activity on cognitive processes, have focused on moderate-intensity continuous exercise. It is only very

	recently that there has been a growing interest in high-intensity exercise. By applying DDM
	model on a perceptual decision-making task, the present results provide a new insight into
	cognitive mechanisms underlying high-intensity exercise-induced changes. Faster non-
	decisional time and more efficient drift rate suggest a better sensory encoding, a greater
	allocation of attentional resources and a faster processing speed following exercise. Less time-
	consuming, more ecological and particularly efficient, high-intensity exercises appear a very
	promising alternative to traditional light-to moderate-exercises.

Table 4 :

 4 Group parameters estimates

			2.5%	50%	97.5%	Rhat
	Hyper location
		z	0.50	0.53	0.55	1.0
		sv	0.02	0.33	1.02	1.0
		sz	0.01	0.08	0.17	1.0
				Before
		a	1.74	2.05	2.34	1.0
		v	1.07	1.71	2.40	1.0
		Ter	0.36	0.48	0.59	1.0
				After
		a	1.82	2.13	2.41	1.0
		v	1.16	1.83	2.56	1.0
		Ter	0.05	0.40	0.74	1.0
	Hyper scale	z	0.04	0.06	0.09	1.0
		sv	0.51	1.00	1.91	1.0
		sz	0.07	0.13	0.21	1.0
				Before
		a	0.44	0.61	0.94	1.0
		v	1.03	1.43	1.93	1.0
		Ter	0.12	0.17	0.84	1.1
				After
		a	0.43	0.60	0.92	1.0
		v	1.09	1.51	1.96	1.0
		Ter	0.15	0.26	1.76	1.0
	Note. Ter: non-decisional time, a: decision thresholds, v: drift, Rhat: Brooks and Gelman's
	(1998) R statistics

Table 5 .

 5 Individual parameters median before and after high-intensity interval exercise Note. Z: starting point, sv: drift rate variability, sz: starting point variability, Ter: non-decisional time, a: decision thresholds, v: drift rate.

	Before	After

Supplementary data

Graph 1: Markov chain Monte Carlo trace and density of DDM parameters (z: starting point, sv: drift variability, sz: starting point variability, t0: non-decisional time (Ter), a: decision thresholds, v: drift) before (C0) and after (C4) high-intensity interval exercise.


Keywords: Mercury, Tropical soils, French Guiana, gold-mining, XRD, selective extraction, speciation

ferralsols and acrisols. Gold-mined gleysols were strongly disorganized by former activities as neither the original structure nor the texture was preserved. Soil granulometry was dominated by gravels, sands and silts. Hg concentrations (0.09-9.22 µg.g -1 ) largely exceeded those in pristine soils. µXRF allowed the identification of Au-amalgamated Hg and of elemental Hg droplets. Pyrolysis confirmed Hg to be mainly present in its elemental form in contaminated soils. Selective extractions showed additional minor contributions of Hg(II) associated to OM, and to Al or Fe oxides.

The combination of selective extractions with XRD and µXRF data showed that extraction efficiency is strongly dependent on the soil type, and that this efficiency needs to be determined on a soil-by-soil basis for Hg speciation studies.

KOH extraction was especially delicate as crystalline and amorphous oxides were extracted together with organic matter.

Abstract.

Mercury (Hg) speciation was compared in French Guiana pristine soils and in Hg contaminated soils impacted by former (~1950's) gold-mining activities which used Hg for gold amalgamation. Four selective extractions were performed on soil samples to assess the fraction of Hg present as Hg(II) and bond to organic matter (extracted by NH 4 OH and KOH), to amorphous iron oxides (ascorbate) and to soil components other than refractory minerals (HCl/HNO 3 ). In addition, pyrolysis was used to quantify the content of elemental Hg in contaminated soils. X-ray diffraction (XRD) and X-ray fluorescence micro-mapping (µXRF) were used in combination to selective extractions to assess the nature of targeted components, the possible overlaps between the different extraction procedures and the spatial correlation between Si, K, Fe, Au and Hg.

In soil profiles from pristine toposequences, Hg concentrations (0.01-0.49 µg.g -1 ) decreased with increasing depth in soil matrix. Hg concentrations also decreased from ferralsols to acrisols and further to gleysols. In pristine soil matrix, Hg was mainly associated to the clay size fraction (< 2 µm) which was mainly constituted of amorphous and crystalline Fe oxides (Al-substituted goethite and hematite), gibbsite and fine organic matter (OM), whose relative abundances vary along the soil association. Total Hg concentration was positively correlated with sulfurs and organic carbon suggesting the association of Hg with OM sulfur-bearing functional groups.

Gleysols were depleted in Hg because of the prevailing reducing conditions that lead to the dissolution of iron oxides. In the same soil profiles, Hg concentrations in ferruginous nodules, which make up most of the soil coarse fraction (> 2 mm), were similar to those reported in the pristine soil matrix. These nodules mainly contained Al-substituted hematite and goethite and were especially abundant upslope in

Introduction

Tropical soils from the Amazonian basin are known to have accumulated atmospheric Hg over millions of years, thus inducing geochemical backgrounds higher than those reported in boreal and temperate climate soils [START_REF] Carmouze | Le Mercure en Amazonie Rôle de l'homme et de l'environnement, Risques sanitaires[END_REF]. In addition, past and current gold mining activities, which represent the main contribution to anthropogenic emissions [START_REF] Lacerda | Global mercury emissions from gold and silver mining[END_REF][START_REF] Roulet | The geochemistry of mercury in central Amazonian soils developed on the Alter-do-Chao formation of the lower Tapajos River Valley, Para state, Brazil[END_REF][START_REF] Guedron | Weathering versus atmospheric contributions to mercury concentrations in French Guiana soils[END_REF], contribute to increase further the total Hg concentrations in these soils.

Small-scale mining activities have increased significantly during the worldwide gold rush, created by the gold price increase in the 1980's. UNIDO (United Nations Industrial Development Organization) estimates that in 2004 10 to 15 million people were working in small-scale gold mines releasing 650-1000 tons of Hg annually [START_REF] Veiga | Protocols for environmental and health assessment of mercury released by artisanal and small scale miners[END_REF]. In addition to this major atmospheric emission, gold mining activities release large amounts of Hg-rich particles into hydrosystems where methylmercury (MMHg) production has been clearly identified in anoxic and suboxic areas [START_REF] Benoit | Geochemical and biological controls over methylmercury production and degradation in aquatic ecosystems[END_REF][START_REF] Coquery | Methylmercury formation in the anoxic waters of the Petit-Saut reservoir (French Guiana) and its spreading in the adjacent Sinnamary river[END_REF]. In turn, MMHg accumulation along the aquatic food chains is a threat to Amerindian populations whose diet relies mainly on fish [START_REF] Lebel | Evidence of early nervous system disfunction in Amazonian populations exposed to low levels of methylmercury[END_REF][START_REF] Frery | Goldmining activities and mercury contamination of native Amerindian communities in french Guiana: key role of fish in dietary uptake[END_REF][START_REF] Barbosa | Mercury Biomagnification in a Tropical Black Water, Rio Negro, Brazil[END_REF]. To assess Hg mobility and its availability to methylating microorganisms, it is thus crucial to determine how Hg is bond to soil particles.

The retention capacity of tropical soils varies as a function of soil components which depends on soil types and horizons [START_REF] Charlet | Monovalent ion adsorption by an oxisol[END_REF][START_REF] Charlet | Bivalent ion adsorption by an Oxisol[END_REF][START_REF] Fontes | Simultaneous competitive adsorption of heavy metals by the mineral matrix of tropical soils[END_REF]. In particular, the relative proportions of soil components responsible for Hg retention [clay minerals, Fe-, Al-, and Mn-(oxyhydr)oxides, organic matter] vary with the geochemical conditions which in turn depend on the topographic position along the soil association [START_REF] Boulet | Landscape geochemistry: role of soil cover[END_REF][START_REF] Valle | Speciation and quantification of mercury in Oxisol, Ultisol, and Spodosol from Amazon (Manaus, Brazil)[END_REF][START_REF] Fritsch | Transformation of haematite and Al-poor goethite to Al-rich goethite and associated yellowing in a ferralitic clay soil profile of the middle Amazon Basin (Manaus, Brazil)[END_REF][START_REF] Fritsch | From Plinthic Acrisols to Plinthosols and Gleysols: iron and groundwater dynamics in the tertiary sediments of the upper Amazon basin[END_REF].

Hg has a high affinity for soil organic matter, especially for reduced sulfur groups such as thiol ligands [START_REF] Schuster | The behavior of mercury in the soil with special emphasis on complexation and adsorption processes-a review of the literature[END_REF][START_REF] Skyllberg | Binding of mercury(II) to reduced sulfur in soil organic matter along upland-peat soil transects[END_REF][START_REF] Khwaja | Binding constants of divalent Mercury (Hg 2+ ) in soil humic acids and soil organic matter[END_REF][START_REF] Skyllberg | Complexation of Mercury(II) in Soil Organic Matter: EXAFS Evidence for Linear Two-Coordination with Reduced Sulfur Groups[END_REF]. High Hg levels can also be associated to Fe-(oxyhydr)oxides. In particular, amorphous or poorly crystalline oxides are known as sinks for metal contaminants owing to their large surface area and/or microporous structure [START_REF] Trivedi | Ni and Zn Sorption to Amorphous versus Crystalline Iron Oxides: Macroscopic Studies[END_REF]. Ferruginous nodules, formed during the lateritic weathering process, also contain elevated Hg contents [START_REF] Roulet | Geochemistry of mercury in pristine and flooded ferralitic soil of a tropical rain forest in French Guiana, South America[END_REF][START_REF] Roulet | The geochemistry of mercury in central Amazonian soils developed on the Alter-do-Chao formation of the lower Tapajos River Valley, Para state, Brazil[END_REF][START_REF] De Oliveira | Soils as an important sink for mercury in the Amazon[END_REF][START_REF] Brabo | Assessment of mercury levels in soils, waters, bottom sediments and fishes of the Acre state in brazilian amazon[END_REF].

Solid-phase chemical speciation has been widely used on sediment samples to decipher metal distribution in contaminated systems [START_REF] Wallschlager | Mercury speciation in floodplain soils and sediments along a contaminated river transect[END_REF][START_REF] Martin-Doimeadios | Chemical availability of mercury in stream sediments from the Almaden area, Spain[END_REF][START_REF] Beldowski | Horizontal and vertical variabilities of mercury concentration and speciation in sediments of the Gdansk Basin, Southern Baltic Sea[END_REF][START_REF] Bloom | Selective extractions to assess the biogeochemically relevant fractionation of inorganic mercury in sediments and soils[END_REF][START_REF] Boszke | Assessment of mercury mobility and bioavailability by fractionation method in sediments from coastal zone inundated by the 26 December 2004 tsunami in Thailand[END_REF]. Most of the recent studies of Hg speciation in natural or contaminated sediments, soils and tailings used sequential extraction procedure (SEP) or Hg pyrolysis procedure following published recommendations [START_REF] Eagenhouse | Geochemistry of mercury in Palos Verdes sediments[END_REF][START_REF] Di Giulio | Mercury in soils, and clams from a North Carolina peatland[END_REF][START_REF] Biester | Determination of mercury binding forms in contaminated soils: Mercury pyrolysis versus sequential extractions[END_REF][START_REF] Bloom | Selective extractions to assess the biogeochemically relevant fractionation of inorganic mercury in sediments and soils[END_REF]. While some studies strictly follow the described SEP [START_REF] Sanchez | Mercury and trace element fractionation in Almaden soils by application of different sequential extraction procedures[END_REF][START_REF] Beldowski | Mercury transformations in marine coastal sediments as derived from mercury concentration and speciation changes along source/sink transport pathway (Southern Baltic)[END_REF], many authors adapt it to the studied matrix. Each extraction step of the SEPs for soils and sediments is critical, as it is challenging to obtain an adequate recovery by preventing losses, contamination or speciation changes, and limiting the interferences [START_REF] Leermakers | Mercury in environmental samples: Speciation, artifacts and validation[END_REF].

In the present study, the speciation of Hg among soil components was determined in soil profiles along pristine soil toposequences and in soils contaminated with Hg by former gold mining in a French Guiana watershed.

Separate selective extractions were used to quantify Hg distribution between soil carrier phases, in order to avoid cumulative errors intrinsic to SEPs. In addition, the combination of X-ray diffraction (XRD) and chemical analysis allowed the identification of the extracted phases and of possible overlaps between selective extractions (cross recoveries). Intrinsic limitations of the selective extraction procedure are discussed in the light of these results.

Materials and methods.

Research areas

The former gold mine flat is located in French Guiana (Fig. 1) on the Combat Creek watershed (52°23'W, 4°35'N), a small catchment of ~1 km² covered by tropical rain forest. Except for the two hilltops and for the lowland, the relief is characterized by steep slopes (15-30%). The climate is tropical humid, with an annual average rainfall of ~4000 mm [START_REF] Barret | Illustrated Atlas of French Guyana[END_REF].

The Combat Creek watershed is located on the 'Amina series' of the Guiana Proterozoic shield consisting primarily of darkschist and thin sandstones [START_REF] Milési | Mineralizations of the northern French Guiana in their geological setting[END_REF]. Large gravel deposits from ancient rivers contain large amounts of gold, resulting from the weathering of auriferous quartz veins from the Proterozoic shield [START_REF] Milési | Mineralizations of the northern French Guiana in their geological setting[END_REF].

Soil distribution within the Combat Creek watershed is typical of French Guiana and is related to soil position along the slopes [START_REF] Boulet | Relationships between soil organization and water dynamics of septentrional French Guiana. Agronomic consequences of an evolution controlled by a mainly tectonic desequilibrium[END_REF][START_REF] Grimaldi | Sources, budget and transfers in soils and sediments[END_REF][START_REF] Guedron | Weathering versus atmospheric contributions to mercury concentrations in French Guiana soils[END_REF]. Ferralsols dominate upslope [START_REF] Deckers | World reference base for soil resources[END_REF], having typically a high clay (< 2 µm size fraction) content and a micro-aggregated structure extending over 1 m depth, which allows a good vertical water drainage [START_REF] Guehl | Water dynamic in French Guiana tropical humid forest soil. Influence of the pedological cover[END_REF]. Ferruginous nodules are present throughout the entire ferralsol profiles. Halfway down the slopes, ferralsols steadily evolves to acrisols, a massive alteritic horizon with a high content of fine silts at shallow depth (< 1 m). During rainfalls, a perched aquifer forms on the slope above this massive alteritic horizon.

Following rainfalls, the aquifer is evacuated laterally, exporting preferentially clay-size particles and dissolution products [START_REF] Molicova | Using TOPMODEL towards identifying and modelling the hydrological patterns within a headwater humid, tropical catchment[END_REF][START_REF] Grimaldi | Behavior of chemical solutes during a storm in a rainforested headwater catchment[END_REF]. Downslope, the soils become hydromorphic, with dominant sands. A permanent aquifer is present and slowly drained by the river, thus imposing reducing conditions.

Whatever the soil type, field observations have shown that quartz, kaolinite, and Fe-Al-(oxyhydr)oxides dominate mineralogy, quartz being the sole remnant from the primary rock-forming minerals. In the massive alteritic horizon, a few muscovite crystals were also observed. Soil pH ranged from 4.2 to 4.9. The upper part of the studied watershed (ferralsols and acrisols) was considered to be pristine based on the soil structure and texture.

In the lowland, ancient 'Long Tom' sluices and gold-bearing gravel heaps attest of former gold mining activities dated from the early 1950's. These activities involved the removal of fine particles with water, in order to concentrate heavier gold-rich particles. Soils are thus strongly disorganized, and neither original structure nor texture is preserved. Present day soil granulometry reflects the former activity as gravels, sands and silts are dominant, while the clay-size fraction is almost absent. Hg droplets were also observed in these gold-mined gleysols during a prospective "panning" campaign. These soils can be described as disorganized gleysols according to their present geochemical characteristics.

Sampling collection and analysis

Soil collection

Three toposequences were sampled in the pristine part of the watershed, (i) the first in the upper part of the basin, (ii) the second on the west (mountain) side and (iii) the third next to the outlet of the basin (Fig. 1). Toposequences II and III reached the gold-mined flats (profiles II-0 and III-0 in Fig. 1).

Thirteen profiles were collected in the former gold-mined flat. SL0 to SL9 profiles were mesh-sampled over a restricted 250 m² area in the flat zone (Fig. 1). G5 profile was sampled on a gravel heap. Soil profiles were sampled systematically every 10 or 20 cm, down to 1-2 m depth, using an auger and collected in sterile polyethylene bags.

Soil conditioning, granulometry and chemical analysis

Granulometry was determined with standard sieving and sedimentation procedures [START_REF] Avery | Soil survey laboratory methods[END_REF][START_REF] Rowell | Soil Science : methods and applications[END_REF]. Identification of the various fractions was performed according to the Udden-Wentworth classification scheme [START_REF] Wentworth | A scale of grade and class terms for clastic sediments[END_REF], and "gravel", "sand", "silt" and "clay" thus refer to particle diameters (x) of x > 2 mm, 2 mm < x < 50 µm, 50 µm < x < 2 µm and x < 2 µm, respectively. Total soil organic carbon ([C]), sulfur ([S]), and nitrogen ([N]) concentrations were determined from the dry combustion of soil sample aliquots crushed and sieved to 63 µm, using a Fisons 1500CHNS auto-analyzer.

Soil samples aliquots used for Hg analysis, selective extractions and XRD analysis were freeze-dried and sieved to x < 2 mm. This size fraction was subsequently crushed to x < 63 µm. Ferruginous nodules were crushed also to x < 63 µm and subsequently freeze-dried. Total Hg concentrations ([HgT]) were determined by atomic absorption spectrophotometry after dry mineralization and gold amalgamation with an automatic mercury analyzer (Altec, Model AMA 254). All analyses were duplicated. The relative error was routinely ±5% and always under ±10% [START_REF] Roos-Barraclough | An analytical protocol for determination of total mercury concentration in solid peat samples[END_REF]. Detection limit (defined as three times the standard deviation (SD) of the blank) is 0.005 µg g -1 . Concentrations obtained for repeated analyses of certified reference materials (CRMs) never exceeded the published range of concentration (0.090 ±0.012 µg g -1 and 0.091 ±0.008 µg g -1 for CRMs 7002, and MESS-3, respectively). Total dissolved Hg concentration [(HgT) D ] were analyzed by cold vapor atomic fluorescence spectrometry (CVAFS) after conversion of all mercury species to Hg 0 [START_REF] Bloom | Determination of volatil mercury species at the picogram level by low-temperature gas chromatography with cold-vapor atomic fluorescence detection[END_REF], using a Tekran ® instrument (Model 2500). Additional information on the method is available elsewhere [START_REF] Bloom | Determination of volatil mercury species at the picogram level by low-temperature gas chromatography with cold-vapor atomic fluorescence detection[END_REF]. (HgT) D concentrations obtained for repeated analyses of CRMs never exceeded the published range of concentration (12.6 ±1.1 ng L -1 for ORMS-3). The detection limit is 0.05 ng L -1 [START_REF] Bloom | Determination of volatil mercury species at the picogram level by low-temperature gas chromatography with cold-vapor atomic fluorescence detection[END_REF].

Dissolved Fe and Al were determined by inductively coupled plasma-atomic emission spectrometry (ICP-AES) using a Perkin-Elmer optima 3300DV. Calibration was performed with using standard solutions for Fe and Al (Fluka ® 44903 for Fe and Fluka ® 06155 for Al). Relative analytical errors were estimated for each sample from triplicate measurements and were lower than 10%.

Selective extraction procedure for Hg and major element analysis

Sample selection

Along soil profiles, samples were selected on the basis of characteristics such as granulometry, C and/or Hg contents, reflecting the textural and structural variations along soil profiles. In pristine soils, the selection criteria were extreme contents of C, Hg, clay-size fraction, and fine-silt fraction which increased in alterites.

In contaminated gleysols from the gold-mined flat, the selection relied mainly on the abundance of the clay-and sand-size fractions, as well as on C and Hg concentrations.

In addition to selected samples, selective extractions were performed for quality assurance/quality controls (QA/QC) on 2 CRMs, namely a light sandy soil (CRM 7002 -Czech Metrological Institute) and a marine sediment (MESS-3 -National Research Council of Canada -Ottawa) and on two natural samples. The latter two samples [acrisol I-1 (0-10 cm), and contaminated gleysol SL6 (30-50 cm)] were chosen as models for the pristine and contaminated parts, respectively, of the watershed. On all samples [HgT] was measured on both the supernatant and the solid residue to assess extraction recovery. In addition, XRD data was systematically collected on solid residues to identify dissolved mineral species.

Selective extraction materials and procedure

Four chemical extractions were chosen to selectively extract the main Hg carrier phases reported in the literature for tropical soils: organic matter, amorphous Fe oxides, and crystalline Fe/Al oxides.

For a given sample, selective extractions were performed on separate aliquots of dry soil (~ 40 mg). All analytical procedures were conducted using ultra clean sample handling to avoid laboratory contamination of low-level sample extracts and a cross-contamination of high-level samples [START_REF] Cossa | Mercury speciation in the Lower St. Lawrence estuary[END_REF]. Specifically, all materials in contact with the samples were previously acid washed (1 week in HNO 3 20%, 1 week in HCl 10%). All solutions were prepared from reagent grade chemicals and supra-pure acids. Selective extractions were performed under a laminar hood in 8 ml Teflon ® vessels at a 1:100 solid-to-liquid ratio [START_REF] Bloom | Selective extractions to assess the biogeochemically relevant fractionation of inorganic mercury in sediments and soils[END_REF]. At the end of the extraction time, samples were centrifuged to 3000 rpm for 20 min. The supernatant was analyzed for major elements. The solid residue was rinsed 3 times with 4 mL MilliQ ® water to obtain a final volume of ~16 mL, which was subsequently freeze-dried before Hg analysis. The Hg content extracted by a given extraction was calculated as:

[Hg] extracted (ng g -1 ) = ([HgT] × M sample -M Hg in residue ) / M sample (1)
where M sample is the mass of the aliquot used (in g) and M Hg in residue the mass of Hg measured in the residue (in ng).

To extract Hg bond to fulvic and humic compounds, a sample aliquot was digested in NH 4 OH (1M) for 1h [START_REF] Di Giulio | Mercury in soils, and clams from a North Carolina peatland[END_REF][START_REF] Martin-Doimeadios | Chemical availability of mercury in stream sediments from the Almaden area, Spain[END_REF][START_REF] Veiga | Protocols for environmental and health assessment of mercury released by artisanal and small scale miners[END_REF]. Another extraction focused on organo-chelated Hg was performed by a 18h KOH digestion (1M) [START_REF] Bloom | Selective extractions to assess the biogeochemically relevant fractionation of inorganic mercury in sediments and soils[END_REF]. Extraction of Hg bond to amorphous Fe(III) oxide minerals and ferrihydrite was performed by adding ascorbate to a sample aliquot and allowing it to react at room temperature for 24h [START_REF] Kostka | Partitioning and speciation of solid phase iron in saltmarsh sediments[END_REF]. Finally, extraction of Hg associated to all soil components except refractory minerals (i.e., silicates, primary minerals) was determined after the digestion of soil sample aliquot in a Suprapur HCl/HNO 3 solution (1/9 v/v ratio) for 10h at 70°C [START_REF] Coquery | Speciation and sorption of mercury in two macro-tidal estuaries[END_REF][START_REF] Bloom | Selective extractions to assess the biogeochemically relevant fractionation of inorganic mercury in sediments and soils[END_REF]. All species associated to a specific extractant are labeled as follow: (i) j where i is the element and the subscribe j describes the extractant (i.e., (i) NH4OH for NH 4 OH, (i) KOH for KOH, (i) Asco for ascorbate and (i) HCl/HNO3 for HCl/HNO 3 ) and square brackets,

[i] j , are used for calculated concentrations (1). The concentration of Hg related to crystalline and refractory minerals (RC) is calculated as the difference between [HgT] and ascorbate plus NH 4 OH extractions:

[Hg] RC (ng g -1 ) = (([HgT] × M sample )-M Hg Asco -M Hg NH4OH ) / M sample

(2)

This should be equivalent to a complete HF/HCl/HNO 3 extraction. Similar calculations were made to estimate the fraction of Hg bond to crystalline Fe and Al oxides ([i] Cryst ).

For this purpose, concentrations obtained after HCl/HNO 3 extraction were considered as related to amorphous and crystalline Fe and Al oxides but not to refractory minerals. Thus, [i] Cryst was calculated as the difference between HCl/HNO 3 and ascorbate extraction :

[i] Cryst (mg g -1 ) = ([i] HCl/HNO3 × M HCl/HNO3 -[i] Asco × M Asco ) / M sample (3)
A complementary pyrolysis procedure was used to assess the amount of Hg 0 present in the soils [START_REF] Biester | Moglichkeiten der anwendung eines temperaturgesteuerten pyrolyseverfahrens zur bestimmung der bindungsform des quecksilbers in boden und sedimenten[END_REF][START_REF] Biester | Determination of mercury binding forms in contaminated soils: Mercury pyrolysis versus sequential extractions[END_REF][START_REF] Bollen | Mercury speciation analyses in HgCl 2contaminated soils and groundwater -Implications for risk assessment and remediation strategies[END_REF]. After heating a ~1g sample aliquot for 48 hours at 180°C in a porcelain crucible, the content of Hg 0 was determined from the difference in Hg concentrations between raw and treated samples.

Physical methods

X-ray diffraction

X-ray diffraction (XRD) was performed on selected samples [Nodules I-2 (10-20 cm), I-1 (30-40 cm) and I-1 (180-200 cm)] for routine mineralogical identification, but also to identify the minerals targeted by the various selective extractions on CRM 7002, and MESS-3 standards, as well as on samples I-1 (0-10 cm) and SL6 (30-50 cm). For this purpose, XRD patterns were collected on solid residues of the different extractions, and compared to those obtained on the untreated samples.

XRD patterns were recorded on randomly oriented powders using a Bruker D5000 powder diffractometer equipped with a Si(Li) solid-state detector from Baltic Scientific Instruments and CuKα radiation (λ = 1.5418 Å). Intensities were recorded from 5 to 80°2θ, using 0.04°2θ steps, and 40 s counting time per step.

Measurements were duplicated on the CRM 7002 set of samples to ensure sampling homogeneity and selective extraction reproducibility (data not shown).

Mineralogical identification and unit-cell refinement

Basic data processing operations (e.g. background removal, diffractogram normalization) and mineralogical identification, based on peak positions and relative intensities, were performed using the Bruker Diffrac plus EVA software and the ICDD database.

Relative intensities of XRD lines varied between raw and treated samples as the result of specific mineral dissolutions. To overcome the intensity variations due to the amount of measured sample, all XRD patterns were normalized to a selected quartz peak, as quartz was present in all samples and not dissolved by the reagents used. The peak used for normalization was selected so that (i) there is no peak overlap with other minerals and (ii) that its intensity is statistically meaningful. For iron oxides (hematite and goethite) present in Al-rich environments, experimental peak positions may differ significantly from theoretical ones as the result of isomorphic Alfor-Fe substitutions. In such case, theoretical unit-cell parameters of iron oxides were refined using the U-Fit program [START_REF] Evain | U-FIT: A Cell Parameter Refinement Program[END_REF] to assess their Al-contents.

Micro X-ray fluorescence mapping and elemental analysis.

SL6 (30-50 cm) sample was freeze-dried, sieved to 300 µm and used for elemental mapping focused on Hg, Au, Al, Cl, Fe, Cr, Si, Ti, Mn, Ni, Ca and K. X-ray fluorescence yields (XRF) were measured with an Eagle III µ-XRF spectrometer (Röntgenanalytik Messtechnik GmbH) equipped with a Rh anode and a 40 µm polycapillary. XRF was measured for 300 s per point over a 1.28×1.00 mm 2 surface area.

The spectrometer was operated under vacuum at 25 kV and 500 µA so as to maximize the fluorescence yield at the Hg L α edge (9.99 keV) while keeping a statistically significant signal on light elements (down to Al K α radiation -1.49 keV).

Further details on the method are given elsewhere [START_REF] Doering | Disilicide Diffusion Coating Inspection by Micro X-Ray Fluorescence Imaging[END_REF].

Statistical treatment.

Since geochemical data were not normally distributed, the following parameters are reported: mean, standard error on the mean (SEM), median, 25 th and 75 th percentiles (25 th perc. and 75 th perc., respectively) and the number of observations (N -Webster, 2001). In addition, non parametric Mann-Whitney rank sum test (U test) and Kruskal-Wallis one way analysis of variance on ranks (H test)

were used to compare two or more than two data sets, respectively. Pearson correlations were applied to compare multiple data set pairs. Correlation coefficient (CC) and P values (P) are reported. to the loss of Hg 0 in the supernatant following Hg II reduction [START_REF] Battke | Phytoreduction and volatilization of mercury by ascorbate in Arabidopsis thaliana, European beech and Norway spruce[END_REF].

Results

Blanks and CRMs

Consistent with this hypothesis, additional measurements of [(Hg) D ] in the supernatant confirmed a steady decrease with time at the end of the extraction.

Pristine soils

Granulometry, chemistry and mineralogy

In the pristine area, the relative proportion of the clay-size fraction (< 2 µm) decreased from ~90% in ferralsols to less than 30% in acrisols and gleysols (Fig. 2).

Ferruginous nodules made up most of the abundant gravel size fractions (x > 2 mm) in ferralsols and acrisols, whereas for gleysols vegetal debris prevailed in this size fraction. In the < 2 mm fraction, total C and S contents in superficial horizons decreased from ferralsols and acrisols to gleysols while the C/N ratios were similar for all soils, thus indicating an homogeneous mineralization of the fine organic matter (OM - [START_REF] Bravard | Characterization of fulvic and humic acids from an oxisol-spodosol toposequence of Amazonia, Brazil[END_REF].

Minerals extracted by HCl/HNO 3 in sample I-1 (0-10cm) were identified as Alsubstituted iron oxides (goethite and hematite) and gibbsite (Fig. 3). Quartz, anatase,

Hg in pristine soils

Total mercury concentrations measured in pristine soils matrix (0.01-0.49 µg.g -1 -Fig. 2) were consistent with those recently reported for French Guiana soils (0.09-0.50 µg.g -1 - [START_REF] Richard | Mercury levels of soils, sediments and fish in French Guiana, South America[END_REF][START_REF] Grimaldi | Sources, budget and transfers in soils and sediments[END_REF][START_REF] Guedron | Weathering versus atmospheric contributions to mercury concentrations in French Guiana soils[END_REF], the highest concentrations being measured in ferralsols.

[HgT] decreased along the slope in acrisols and in gleysols (Fig. 2).

[HgT] were positively correlated with steadily decreased with increasing depth.

Position of the iron oxide peaks (goethite and hematite) shifted to lower angular values with increasing depth (Fig. 6, inset), thus indicating the lengthening of unit-cell parameters, and thus the probable decrease of Al-for-Fe substitution, since the ionic radius of Al is smaller than Fe [START_REF] Shannon | Revised effective ionic radii and systematic studies of interatomic distances in halides and chalcogenides[END_REF]. The extent of this substitution was assessed for the two oxides by refinement of the unit-cell parameters and empirical relations between the Al content and the lattice parameters [START_REF] Schulze | The influence of aluminium on iron oxides. VIII. Unit-cell dimension of Al-substituted goethites and estimation of Al from them[END_REF][START_REF] Stanjek | The influence of aluminium on iron oxides. Part XVI: hydroxyl and aluminium substitution on synthetic hematites[END_REF]. Al substitutions in hematite decreased from 17 mol% (surface) to 10 mol% (deep alteritic horizons) and were almost constant (~20 mol%) over the entire profile for goethite. Uncertainty on lattice parameters (and therefore on Al substitution quantification) was low for hematite owing to the sharp and numerous diffraction peaks, but higher for goethite. Indeed, few isolated diffraction peaks were available for the determination of the unit-cell parameters and peaks were broadened.

The intensity of hematite diffraction lines increased with decreasing depth, thus indicative of a higher proportion of hematite towards the surface, consistent with its status of final alteration product of iron-rich phases [START_REF] Schwertmann | Properties of iron oxides in some new caledonian oxisols[END_REF]. Hematite and goethite are indeed the most thermodynamic stable iron oxides in surface conditions. Amorphous oxides were present as minor constituents since Al and Fe extracted by ascorbate and NH 4 OH never exceeded 7% of their HCl/HNO 3 counterparts (Fig. E5). As in pristine soils matrix, KOH extraction likely induced the partial dissolution of gibbsite as [Al] KOH was large (median = 51.5% of [Al] HCl/HNO3 ).

Hg in ferruginous nodules of pristine soils

For surface horizons, [HgT] were much lower in nodules than in the soil matrix.

[HgT] increased with increasing depth, similar values being obtained for nodules and soil matrix in the deepest sample of acrisol I-1 profile.

[HgT] were even larger in nodules than in soil matrix for ferralsol I-2 samples below 50 cm depth (Fig. E5).

[HgT] was positively correlated with [Hg] (Hg) NH4OH , and progressively decreased downwards in I-1 and I-2 profiles.

Contaminated gold-mined soils

Granulometry, mineralogy and chemistry

In the gold-mined flat, contaminated gleysols contained a large proportion of gravel size fractions (mainly quartz gravels and stones, mean ± RSD = 42.7 ±24.6% total weight) and the < 2 mm fraction was dominated by sands in contrast with pristine soils (Fig. 2b). and [Fe] NH4OH : median = 14.8% of [Fe] HCl/HNO3 ).

Hg in contaminated gold mined soils

[HgT] values measured in gleysols from the gold-mined flat (up to ~10 µg.g -1 in SL6 profile) were up to 5 times higher than those determined in gleysols from the pristine area (Fig. 2b). Although extremely variable, even over very short distances, these values were consistent with those determined in Hg-contaminated soils from different gold-mining regions [START_REF] Lechler | Mercury mobility at the Carson River Superfund Site, west-central Nevada, USA: Interpretation of mercury speciation data in mill tailings, soils, and sediments[END_REF][START_REF] Lechler | Elevated mercury concentrations in soils, sediments, water, and fish of the Madeira River basin, Brazilian Amazon: a function of natural enrichments?[END_REF][START_REF] Richard | Mercury levels of soils, sediments and fish in French Guiana, South America[END_REF][START_REF] Sladek | Evaluation of sequential and selective extraction methods for determination of mercury speciation and mobility in mine waste[END_REF], and positively correlated with [Hg] extracted by all four reagents (Tab. 2a and 2b). Contrarily to the pristine area, where gleysols were the pole of lowest [HgT], the only significant correlation of [HgT] with other soil parameters was observed with the sand-size fraction (P < 0.05).

µ-XRF map (Fig. 7) shows that Hg was not homogeneously distributed in sample SL6 (30-50cm). Indeed, Hg is essentially present as "hot-spots" of 30 to 100 µm in diameter. In these hot-spots, Hg concentration is not correlated with any element (data not shown), except for a covariation with Au (Fig. 7). These spots are thus likely Hg 0 droplets, possibly amalgamated with Au. Consistently, pyrolysis measurements showed that almost 60% of total Hg was desorbed at 180°C.

However, lower percentages of desorbed Hg were determined for SL8 and SL7 samples, thus suggesting that Hg 0 was not systematically the main Hg form over the entire former gold-mined flat (Fig. 8). Consistently, selective extractions have shown that Hg was partially associated to OM and amorphous oxides for some samples as shown by the NH 4 OH and ascorbate extraction yields. Such associations remained however minor as (Hg) NH4OH (median = 28.4%) and (Hg) Asco (median = 14.7%) extraction yields only seldom exceeded 50 and 30%, respectively (Fig. 8). Relative proportion of Hg associated to refractory minerals was negligible as (Hg) HCl/HNO3 extraction yields were systematically ~100%. In this case, large (Hg) RC reflect the proportion related to Hg 0 (Fig. 8). KOH extraction yields also were high (median = 86.5%), being always higher than 80% in the uppermost 40 cm.

Discussion

Selective extractions

Further investigation was performed to unravel the reactions leading to Hg reduction and loss during ascorbate extraction, although [Hg] Asco were not biased, being calculated from the analysis of the solid residue. Results of the pyrolysis procedure were also questionable as the pyrolysis (180°C) of marine sediment MESS-3 has shown no significant desorption of Hg, while almost 70% of total Hg desorbed from light sandy soil CRM 7002 under the same conditions. It is thus likely that in addition to Hg 0 , Hg bond to OM was partially desorbed during pyrolysis.

Pyrolysis temperature (180°C) was indeed close to the temperature range reported by [START_REF] Biester | Determination of mercury binding forms in contaminated soils: Mercury pyrolysis versus sequential extractions[END_REF] for the thermal release of Hg bound to organic compounds (200-350°C). This is especially relevant for the assessment of the different Hg-compartments in organic-rich contaminated soils.

Cross recoveries between selective extractions were observed for both CRMs and natural samples, but it was also possible to attribute selective mineral extractions to each reagent. The selective character of a given extraction depends on the considered soil matrix, as reagent selectivity depends both on the nature of components present and on their reactivity with respect to a given reagent.

Overlapping extractions further increase the uncertainty on the relative proportion of Hg associated to any carrier phase. Although chemical data may help to assess cross recoveries, the restricted and variable selectivity of the different reagents precludes the use of selective extractions as standardized procedures for environmental studies. Specifically, the use of selective extractions needs preliminary investigation to assess reagent selectivity for a given soil matrix.

Hg distribution in pristine soils

The study of Hg distribution in a soil has to take into account the original soil cover formation, its current evolution and its present topographic position, that is its position in the soil association [START_REF] Fritsch | From Plinthic Acrisols to Plinthosols and Gleysols: iron and groundwater dynamics in the tertiary sediments of the upper Amazon basin[END_REF]. These factors are indeed responsible, at least partially, for the relative abundance and the reactivity of soil organic and mineral components, including Hg carriers, thus providing additional insight in the Hg natural equilibrium and contents.

Hg carrier phases in soil profiles

A positive correlation between the relative amount of the clay-size fraction and C, S, [Fe] and [Al] extracted by HCl/HNO 3 , NH 4 OH and ascorbate is shown in Table 2. Hg is thus likely associated with finely divided Fe and Al organic complexes and/or with organic coatings on Fe/Al oxides. Several authors have already shown that in Amazonian micro-aggregated horizons, micropeds develop from the bonding between clays, organic matter and iron oxides through the formation of carboncoatings on mineral surfaces [START_REF] Tandy | Mineralogical and textural changes in French Guiana oxisols and their relation with microaggregation[END_REF][START_REF] Malengreau | Short-time dissolution mechanisms of kaolinitic tropical soils[END_REF][START_REF] Do Nascimento | Podzolization as a deferralitization process: a study of an Acrisol-Podzol sequence derived from Palaeozoic sandstones in the northern upper Amazon Basin[END_REF].

Specific bonding of Hg with sulfur groups from finely divided organic matter may be inferred from the above described correlations for all pristine soils. This is consistent with previous reports of organics, and more especially of reduced sulfur groups, being the most effective sorbents for Hg in acidic environments (pH < ~4.5-5.0), compared to iron oxides and clay minerals [START_REF] Andersson | Mercury in soils[END_REF][START_REF] Schuster | The behavior of mercury in the soil with special emphasis on complexation and adsorption processes-a review of the literature[END_REF][START_REF] Roulet | Geochemistry of mercury in pristine and flooded ferralitic soil of a tropical rain forest in French Guiana, South America[END_REF][START_REF] Skyllberg | Binding of mercury(II) to reduced sulfur in soil organic matter along upland-peat soil transects[END_REF][START_REF] Skyllberg | Complexation of Mercury(II) in Soil Organic Matter: EXAFS Evidence for Linear Two-Coordination with Reduced Sulfur Groups[END_REF][START_REF] Manceau | Relationships between Hg(II)-S bond distance and Hg(II) coordination in thiolates[END_REF].

In addition to this essential organic contribution, Hg contents in soils from

French Guiana are also controlled by the actual nature of Fe and Al (oxyhydr)oxides [START_REF] Roulet | Geochemistry of mercury in pristine and flooded ferralitic soil of a tropical rain forest in French Guiana, South America[END_REF][START_REF] Roulet | The geochemistry of mercury in central Amazonian soils developed on the Alter-do-Chao formation of the lower Tapajos River Valley, Para state, Brazil[END_REF]. In pristine soil matrix, large [Hg] Asco and [Hg] HCl/HNO3 values were indeed attributed to Al-substituted amorphous and crystalline Fe oxides. As a result of their larger surface areas compared to their crystalline counterparts, amorphous or poorly crystalline species have an increased adsorption capacity, [START_REF] Schwertmann | Properties of iron oxides in some new caledonian oxisols[END_REF][START_REF] Schwertmann | Iron oxides in the laboratory : preparation and characterization[END_REF]. The positive correlation between [Hg] KOH and [Al] KOH supports also the importance of Al oxides as a reservoir for Hg. This reservoir is accessible through KOH and, to a lesser extent, through ascorbate extractions, thus the large [Al] Asco plead for the partial dissolution of (amorphous) Al (oxyhydr)oxides [START_REF] Schwertmann | Properties of iron oxides in some new caledonian oxisols[END_REF].

In values. This observation is consistent with the strong affinity of Hg(II) for gibbsite (Kim et al., 2004a;Kim et al., 2004b;[START_REF] Weerasooriya | Transition state kinetics of Hg(II) adsorption at gibbsite-water interface[END_REF].

Finally, the contribution of refractory minerals (identified as muscovite, anatase, rutile and kaolinite) is non negligible, although minor, in pristine soils as the median (Hg) HCl/HNO3 extraction yield is only 89.8%.

Influence of soil structure on Hg distribution in soil profiles

From the above description, it appears that the vertical distribution of OM, Al/Fe (oxyhydr)oxides and ferruginous nodules in the soil matrix rules Hg distribution.

In the following section, pedological and chemical characteristics responsible for the spatial distribution of these components in soil profiles will be discussed.

Upslope, large [HgT] have been measured in the matrix of the ferralsol microaggregated horizons (i.e., A and B horizons). The micro-aggregated structure confers a good water drainage capacity to ferralsols, favoring water flow and oxidizing conditions. As a result, Hg is spread throughout these micro-aggregated horizons as the result of both significant leaching and migration of atmospheric inputs [START_REF] Guedron | Weathering versus atmospheric contributions to mercury concentrations in French Guiana soils[END_REF]. Plant litter is rapidly mineralized in surface horizons, and the rapid turnover of humic substances leads to the migration of fulvic acids in deeper organomineral horizons where they are complexed to Fe and Al oxides [START_REF] Roulet | Geochemistry of mercury in pristine and flooded ferralitic soil of a tropical rain forest in French Guiana, South America[END_REF]. Thus, Hg originating from plant litter decomposition and/or from atmospheric fallouts can migrate into the organo-mineral horizons as organic-Hg complexes and progressively adsorb onto Al/Fe (oxyhydr)oxides. Soil ecosystem engineers (soil invertebrates and roots) also play an important role in the particulate transfer of Hg by enhancing aggregation [START_REF] Velasquez | This ped is my ped: Visual separation and near infrared spectra allow determination of the origins of soil macroaggregates[END_REF] and soil hydraulic conductivity [START_REF] Grimaldi | Mercury distribution in tropical soil profiles related to origin of mercury and soil processes[END_REF]

Influence of soil formation on the distribution of Hg over the soil association

The soil association results from the ferralsols current imbalance, which leads to temporal and spatial evolutions [START_REF] Boulet | Landscape geochemistry: role of soil cover[END_REF][START_REF] Grimaldi | Behavior of chemical solutes during a storm in a rainforested headwater catchment[END_REF]).

Because of their major role as Hg reservoirs, the following description of Hg distribution along the toposequence will thus focus on OM and Fe oxides behavior in the soil association.

In organic horizons, the [HgT] decrease along the slopes correlates with the decrease of their C and S contents. However, organic horizons in gleysols are characterized by an increased proportion of OM in gravel size fractions (> 2 mm) and thus by a lower degree of mineralization of coarse OM because of hydromorphy.

Consequently, the overall reactivity of coarse OM towards Hg (including the reactivity of S groups) decreases when all soil fractions are considered even if C and S remain abundant [START_REF] Andersson | Mercury in soils[END_REF][START_REF] Kerndorff | Sorption of metals on humic acid[END_REF][START_REF] Schnitzer | Reactions of fulvic acid with metal ions[END_REF][START_REF] Ochs | Coordinative and hydrophobic interaction of humic substances with hydrophilic Al 2 O 3 and hydrophobic mercury surfaces[END_REF][START_REF] Gasper | A critical review of three methods used for the measurement of mercury (Hg 2+ )-dissolved organic matter stability constants[END_REF].

The decreasing proportion of Fe and Al (oxyhydr)oxides down the slope results from the combined effect of diffuse erosion and leaching due to the lateral drainage of horizons overlying the alteritic horizons of acrisols and of the progressive occurrence of hydromorphy [START_REF] Boulet | Relationships between soil organization and water dynamics of septentrional French Guiana. Agronomic consequences of an evolution controlled by a mainly tectonic desequilibrium[END_REF][START_REF] Fritsch | Transforming systems of ferrallitic cover in French Guiana, structural analysis of a supergene formation and mode of representation[END_REF][START_REF] Fritsch | From Plinthic Acrisols to Plinthosols and Gleysols: iron and groundwater dynamics in the tertiary sediments of the upper Amazon basin[END_REF][START_REF] Grimaldi | Behavior of chemical solutes during a storm in a rainforested headwater catchment[END_REF][START_REF] Lucas | Soil genesis and dynamics in equatorial areas[END_REF]. Drainage induces a texture coarsening from the original clayey texture of ferralsols to the sandy-loam texture of gleysols, whereas hydromorphy induces the dissolution of crystalline and amorphous Al-bearing Fe oxides and the export of the reduction products through the hydrographic network [START_REF] Grimaldi | Mercury distribution in tropical soil profiles related to origin of mercury and soil processes[END_REF]. Both processes result in the relative increase of coarse fractions composed mainly of quartz and neoformed kaolinite [START_REF] Boulet | Existence of high lateral differentiation systems in French Guiana's ferrallitic soils: a new example of an imbalanced pedological cover[END_REF][START_REF] Roulet | The geochemistry of mercury in central Amazonian soils developed on the Alter-do-Chao formation of the lower Tapajos River Valley, Para state, Brazil[END_REF] which possess a low affinity for Hg [START_REF] Sarkar | Adsorption of mercury(II) by variable charge surfaces of quartz and gibbsite[END_REF][START_REF] Sarkar | Adsorption of mercury(II) by kaolinite[END_REF].

Influence of former gold mining activities on anthropogenic Hg pool in soils

In contrast to pristine soils, Hg appears to be associated mainly with the prevailing sandy fraction. In highly contaminated sites Hg has been identified as Hg 0 , insoluble cinnabar and metacinnabar [START_REF] Lechler | Mercury mobility at the Carson River Superfund Site, west-central Nevada, USA: Interpretation of mercury speciation data in mill tailings, soils, and sediments[END_REF][START_REF] Slowey | Speciation of mercury and mode of transport from placer Gold Mine Tailings[END_REF][START_REF] Slowey | Transformations of mercury, iron, and sulfur during the reductive dissolution of iron oxyhydroxide by sulfide[END_REF]. In the present study, mercury sulfides (cinnabar and metacinnabar) are most likely insignificant as no positive correlation was found between Hg and S. (Hg) HCl/HNO3 extraction yields are systematically close to 100%

and support further the low amount of mercury sulfides which are essentially insoluble in concentrated HCl/HNO 3 [START_REF] Mikac | Extractability of HgS (cinnabar and metacinnabar) by hydrochloric acid[END_REF][START_REF] Mikac | Influence of chloride and sediment matrix on the extractability of HgS (cinnabar and metacinnabar) by nitric acid[END_REF]..

The probable presence of Hg 0 is supported by the observation of macroscopic Hg 0 droplets during a prospective "panning" in the sandy horizon of gold-mined gleysols (50-100 cm depth) next to profile III-0. It was however impossible to assess the distribution of the Hg 0 droplets along vertical profiles. µXRF confirmed the presence of isolated Hg 0 droplets (~100 µm in diameter) in sample SL6 (30-50cm), possibly amalgamated with micrometric gold particles. Consistently, pyrolysis measurements have shown that Hg 0 generally prevail in the former gold-mined flat soils, with some exceptions (e.g., SL7 and SL8 profiles). In the latter profiles, the reduced contribution of Hg 0 can result from its oxidation, known to be fast in tropical environments [START_REF] Dominique | Simulation of the Chemical Fate and Bioavailability of Liquid Elemental Mercury Drops from Gold Mining in Amazonian Freshwater Systems[END_REF]. If geochemical conditions are not permanently reducing, as in the surface horizons, Hg 0 can be oxidized, allowing adsorption onto OM and minerals. The relative proportion of Hg bond to OM is however lower than in pristine soils, (Hg) NH4OH extraction yields rarely exceeding 50%. As previously discussed, the overall limited mineralization of OM is most likely responsible for the low reactivity of OM for Hg. Similarly, the relative proportion of Hg bond to amorphous Fe oxides is low (up to 15%), these oxides being scarce in hydromorphic environments. Finally, the part related to refractory minerals (i.e., quartz, kaolinite and muscovite) appears to be negligible since (Hg) HCl/HNO3 extraction yields are always close to 100%.

Conclusion

The combination of selective extractions with physical techniques (XRD and µXRF) significantly improved the determination of Hg speciation by allowing the identification of Hg carrier phases targeted by the different extractants. However, the quantification of Hg associated to a given carrier phase is affected by intrinsic bias, especially because of probable overlaps between the different extraction procedures.

Thus, selective extractions can not be used as a standard procedure for natural samples since the use of selective extractions requires the preliminary assessment of reagent selectivity for a given soil matrix.

By coupling XRD and selective extractions, the main Hg carrier phases in pristine soils were identified as sulfur groups from organic matter, amorphous and crystalline Al-substituted Fe oxides and, to a lower extent, Al oxides. The relative contribution of these carriers to the overall Hg concentration was dependent on their relative abundance which is controlled by the pedogenetic evolution along the slopes, and more especially by redox conditions, hydric properties, and ecosystem engineers. In the former gold-mined flat, Hg was found mainly as Hg 0 , possibly amalgamated with Au, and as oxidized Hg II associated with organic matter, Fe and/or Al oxides in surface horizons.

Concluding Remarks

These findings have major implications on the contamination of hydrosystems in tropical regions, where soil erosion due to deforestation, gold mining and agricultural processes are intense and lead to the release of Hg-rich clay-size particles as shown by the low proportion of clay-size fractions in gold-mined gleysols.

When entering suboxic and anoxic environments (e.g. river or dam sediments), Hg bond to clay-size particles indeed becomes accessible to ferri-and sulfato-reducing bacteria that are the main factors of Hg methylation [START_REF] Fitzgerald | Geochemistry of mercury in the environment[END_REF][START_REF] Fleming | Mercury methylation from unexpected sources: molybdate-inhibited freshwater sediments and iron-reducing bacterium[END_REF]. Hg bound to OM and Fe oxides is specifically concerned as these major components of the clay-size fraction are essential nutriments for methylating micro-organisms and final electron acceptors of their metabolism. In addition, former gold mined soils are potential important sources of Hg for methylating bacteria. Indeed, [START_REF] Dominique | Simulation of the Chemical Fate and Bioavailability of Liquid Elemental Mercury Drops from Gold Mining in Amazonian Freshwater Systems[END_REF] have shown that anthropogenic Hg 0 from former gold-mining activities also promotes the production of MMHg in the Amazonian hydrosystems and its availability to trophic webs. [HgT] (µg g -1 )

[Hg] Asco (µg g -1 ) (Hg) Asco (%)

[Fe] Asco (mg g -1 )

[HgT] (µg g -1 )

[Hg] NH4OH

(µg g -1 )

(Hg) NH4OH (%)

[Fe] NH4OH (mg g -1 )

[Al] NH4OH (mg g -1 ) Clay (g/100g) Sand (g/100g) Table E1: Percent recoveries of Hg in supernatant and solid residue for Certified materials CRM 7002, MESS-3 and sample I-1 (0-10 cm) for ascorbate, NH 4 OH , KOH and HCl/HNO 3 selective extractions.

Figure captions

  kaolinite, and muscovite being essentially unaffected by the HCl/HNO 3 extraction (Supplementary data -Fig.E3e.).For HCl/HNO 3 and ascorbate extractions, Fe and Al concentrations were correlated to the content of the clay size fraction (Tab. 1) showing that crystalline and amorphous Fe and Al oxides were central in this fine fraction. Large Al and Fe concentrations were measured in supernatants following KOH, ascorbate and NH 4 OH extractions. XRD confirmed that no crystalline Fe or Al oxides were dissolved by NH 4 OH, thus supporting the dissolution of amorphous (or poorly crystalline) Fe and/or Al minerals. In addition, goethite was partially dissolved by ascorbate and hematite by KOH, as indicated by the ~10-20% intensity decrease of their characteristic XRD lines after these chemical extractions (Fig.3). For all pristine soil samples, partial dissolution of these well-crystallized species is supported by the higher Al and Fe concentrations measured in KOH (median = 52.6% and 12.1% of [Al] HCl/HNO3 and [Fe] HCl/HNO3 ) and ascorbate (median = 24.7% and 21.7% of [Al] HCl/HNO3 and [Fe] HCl/HNO3 ) extracts compared to NH 4 OH extracts (median=9.1% and 3.6% of [Al] HCl/HNO3 and [Fe] HCl/HNO3 ) (H test, P < 0.001). [Fe] HCl/HNO3 , [Al] HCl/HNO3 , [Fe] Asco and [Al] Asco decreased steadily along the slopes from ferralsols to gleysols (Fig. 4), [Fe] Asco and [Al] Asco being commonly lower than [Fe] Cryst and [Al] Cryst for all profiles (Fig. 4). In ferralsols and acrisols, amorphous Fe and Al oxides were most abundant in the A horizon and in the top 50 cm of the B horizon, where weathering was most intense and granulometry dominated by clays. In the C horizon, the relative proportion of amorphous oxides decreased while well crystallized oxides and residual primary minerals became predominant, more especially in the fine silt size fraction. Al-for-Fe substitutions were identified in goethite (~33 Al mol%) and hematite (~10 Al mol%) from XRD unit-cell determinations and confirmed by the positive correlations between [Fe] Cryst and [Al] Cryst in B and C horizons (Fig. 4 -CC = 0.76; P < 0.01). Similar correlation was observed between [Fe] Asco and [Al] Asco (CC = 0.98; P < 0.01) for the whole profiles of pristine soils. The better correlation found between [Fe] and [Al] for ascorbate than for crystalline oxide is suggestively due to an increase in [Al] related to Al extraction from gibbsite and in a lesser extent from kaolinite during HCl/HNO 3 extraction.

  [Hg] extracted by HCl/HNO 3 , KOH, NH 4 OH and ascorbate (Tab. 1). In turn,[Hg] extracted by the four reagents were positively correlated to the content of the clay-size fraction,[S] and[C]. The clay-size fraction, which is composed of OM (S-groups) and Fe and Al minerals, thus represents the main Hg reservoir (Tab. 1).In general,[Hg] extracted by all four reagents decreased with depth and from ferralsols to gleysols. However, Figure5shows that Hg extraction yields can be separated in two sets: (i) ferralsols and superficial acrisols and (ii) deep acrisol alteritic (C) horizons and gleysols. In both sets, NH 4 OH extraction yields were significantly larger than ascorbate ones but followed the same trend. (Hg) NH4OH and (Hg) Asco extraction yields were highest in superficial horizons of both ferralsols and acrisols and steadily decreased with depth. Only in the upstream profiles I-1 and I-2 (Hg) NH4OH and (Hg) Asco extraction yields were constant with depth. In gleysols and deep alteritic horizons of acrisols, both (Hg) NH4OH and (Hg) Asco decreased rapidly with depth, whereas (Hg) RC extraction yields increased strongly with increasing depth.(Hg) RC decreased with increasing depth in the B horizons of ferralsols and acrisols, then increasing steadily in the ferralsol C horizons. (Hg) KOH extraction yields were highly variable with highest values in ferralsol and acrisol B horizons. In pristine gleysols (profile II-1), (Hg) KOH extraction yields increased with increasing depth over the first 50 cm, while decreasing in the C horizon.3.3 Ferruginous nodules in pristine soils3.3.1 Chemistry and mineralogyFerruginous nodules (> 2 mm) were abundant (mean ±RSD = 45.8 ±28.6% total weight), especially in superficial horizons of the pristine toposequences, their relative abundance decreasing from ferralsols to gleysols. Nodules from samples I-2 (10-20 cm), I-2 (30-40 cm) and I-2 (180-200 cm) contained quartz, Al-substituted hematite and goethite, gibbsite and kaolinite. Figure6shows the steady increase of muscovite (Mu), paragonite (Pa), gibbsite (Gb) and rutile (Ru) contents from surface (sample I-2, 10-20 cm) to depth. This mineralogical evolution is consistent with chemical data as[Fe] HCl/HNO3 and [Al] HCl/HNO3

  through biogenic soil organization. In the micro-aggregated B horizon of ferralsols, the distribution of amorphous Fe oxides is positively correlated to[HgT], although their relative abundance is lower than or similar to that of the crystalline varieties. The comparison of[Fe] Cryst and[Fe] Asco indicates that the relative proportion of crystalline Fe oxides is increased further in the superficial layer and in the deep alteritic horizons compared to the micro-aggregated B horizon of ferralsols.In addition, the positive correlations between [Hg] RC and[Fe] Cryst or[Al] Cryst throughout the entire soil profile suggest that [Hg] RC is partially associated to Alsubstituted crystalline Fe oxides. In this case, the sum of [Hg] adsorbed onto amorphous and crystalline Fe oxides would be comparable or larger than the part related to organic compounds.The micro-aggregated structure of ferralsols disappears progressively with increasing depth, giving rise to deep mineral horizons with a continuous structure composed of large mineral relics. Parental material relics "dilute" Al/Fe oxides and thus reduce the overall sorption capacity of deep horizons. Another essential factor is the lower permeability of deep horizons which limits the downward migration of Hg[START_REF] Guedron | Weathering versus atmospheric contributions to mercury concentrations in French Guiana soils[END_REF]. Hg content thus mainly results from rock weathering and pedogenesis[START_REF] Guedron | Weathering versus atmospheric contributions to mercury concentrations in French Guiana soils[END_REF],[HgT] being mainly associated with coarsegrained goethite and hematite.In ferralsol nodules, Hg is mainly bond to Al-substituted hematite and goethite, and to gibbsite. As in ferralsol matrix, highest[HgT] values were measured in the micro-aggregated horizon. Indeed, the downward decrease of (Hg) HCl/HNO3 extraction yields and the mineralogical evolution suggest that A and B horizons nodules are primarily composed of neo-formed minerals, thus indicating an advanced stage of pedogenesis and weathering in superficial horizons. Mineral neoformation also appears to favor the incorporation of atmospheric Hg inputs.Halfway down the slope, in acrisols, a similar mineralogical and structural contrast is observed between superficial (A and B horizons) and alteritic horizons. This transition is sharp as evidenced by the increase of the silt fraction and by the decrease of[HgT]. As for ferralsol, the increase of refractory minerals with increasing depth is most likely responsible for the observed decrease of[HgT]. Downslope, in gleysols,[HgT] were lower since fine organic fraction, S and amorphous oxides are less abundant than upslope, even though carrier phases were similar to those identified in ferralsols and acrisols. Gleysols are depleted in iron oxides and the main minerals are kaolinite, gibbsite, muscovite and quartz. Hg extracted by NH 4 OH never exceeds 40% of [HgT] in gleysol surface horizons and rapidly decreases with depth. Hg bond to amorphous oxides never exceeds 20% of [HgT], and almost 50% of [HgT] is likely associated to Al-substituted crystalline Fe oxides, gibbsite and to refractory minerals. Consistently, Hg, Fe, and Al extracted by HCl/HNO 3 are together positively correlated in the gleysol profile. In depth, Hg is less abundant and mainly associated to refractory minerals since (Hg) RC extraction yields increase with increasing depth.

Fig. 1 :

 1 Fig. 1: Top left: french Guiana map with the studied site location (closed circle). Right

Fig. 2 :

 2 Fig. 2: Evolutions with depth of total Hg, C and C/N ratio for (a) pristine and (b)

Fig. 3 :

 3 Fig. 3: XRD patterns normalized on quartz peak (refer to the text for details) for raw

Fig. 4 :

 4 Fig. 4: Top : Evolutions with depth of Fe and Al concentrations extracted by

Fig. 5 :

 5 Fig. 5: Evolutions with depth of (Hg) HCl/HNO3 , (Hg) CR , (Hg) Asco , (Hg) NH4OH , and (Hg) KOH

Fig. 6 :

 6 Fig. 6: XRD patterns of nodules from pristine soils I-2 (10-20cm), I-2 (30-40cm), and

Fig. 7 :

 7 Fig. 7: µXRF mapping of Si, K, Fe, Au and Hg of SL6 (30-50 cm) sample and counts

Fig. 8 :

 8 Fig. 8: Evolution with depth of (Hg) HCl/HNO3 , (Hg) CR , (Hg) Asco , (Hg) NH4OH , (Hg) KOH and (Hg 0 ) pyrolysis extraction yields (%) in contaminated soils.

Fig

  Fig. 1.

Fig

  Fig . 8.

Fig. E1a :Fig. E1e .Fig. E2e .Fig. E3e .

 E1aE1eE2eE3e Fig. E1a: X-ray diffraction pattern of CRM Mess-3 (black trace) showing identified

  Total organic C largely exceeded the concentrations determined in pristine soils and elevated C/N ratios were characteristic of poorly mineralized OM (data not shown). Leaves and wood debris were visible in the litter.

	0, SL0 and G5 profiles.
	As for pristine soils, partial gibbsite dissolution by KOH was evidenced by
	chemistry data as [Al] KOH (median = 76.3% of [Al] HCl/HNO3 ) were larger than [Al] Asco
	(median = 55.7% of [Al] HCl/HNO3 ) and [Al] NH4OH (median = 28.5% of [Al] HCl/HNO3 ) (U test,
	P < 0.05). Fe oxides were also more attacked by ascorbate ([Fe] Asco median = 31.1%
	of [Fe] HCl/HNO3 ) than by KOH and NH 4 OH ([Fe] KOH : median = 17.3% of [Fe] HCl/HNO3

Minerals present in sample SL6 after HCl/HNO 3 extraction were quartz, kaolinite, muscovite, diaspore, rutile and microcline. Gibbsite was for the most part dissolved by HCl/HNO 3 , which also possibly partially dissolved kaolinite. The absence of Fe oxides is consistent with the low

[Fe]

HCl/HNO3 values (0.35 mg.g -1 ).

Amorphous and crystalline Fe and Al oxides were scarce in contaminated soils as shown by the low Al and Fe concentrations extracted by any reagent compared to pristine soils. For all soil profiles, [Al] HCl/HNO3 and [Fe] HCl/HNO3 were maximum in surface horizons, and sharply decreased to ~5 mg.g -1 at ~40 cm depth, except for II-

Table 1 :

 1 Pearson correlation matrix (correlation coefficient (CC), P value (P) and number of samples (N)) of pristine soils extracted Hg, Hg extraction yields, Fe, Al,

	Clay size fraction, Fine silts, C and S for total and (a) HCl/HNO 3 (labeled HCl) and
	ascorbate (labeled Asco) selective extractions, and (b) KOH and NH 4 OH selective
	extractions.

Table 1b Table 2 :

 1b2 Pearson correlation matrix (correlation coefficient (CC), P value (P) and number of samples (N)) of contaminated soils extracted Hg, Hg extraction yields, Fe, Al, Clay size fraction, Fine silts, C and S for total and (a)

	HCl/HNO 3 (labeled HCl) and ascorbate (labeled Asco) selective
	extractions, and (b) KOH and NH 4 OH selective extractions.

Table 2a

 2a

	Stati	[Hg] HCl	(Hg) HCl	[Fe] HCl	[Al] HCl	Clay	Sand	C	S	[Hg] KOH	(Hg) KOH	[Fe] KOH	[Al] KOH	Clay	Sand	C	S
	stics	(µg g -1 )	(%)	(mg g -1 )	(mg g -1 )	(g/100g)	(g/100g)	(g/100g)	(g/100g)	(µg g -1 )	(%)	(mg g -1 )	(mg g -1 )	(g/100g)	(g/100g)	(g/100g)	(g/100g)
	CC	1.00	0.22 -0.29 -0.34 -0.52	0.50 -0.09 -0.08	0.88	0.22 -0.21 -0.38 -0.52	0.50 -0.09 -0.08
	P 4.E-86 2.E-01 8.E-02 4.E-02 1.E-03 2.E-03 6.E-01 7.E-01	2.E-12 2.E-01 2.E-01 2.E-02 1.E-03 2.E-03 6.E-01 7.E-01
	N	3 7	3 7	3 7	3 7	3 7	3 7	3 7	3 7	3 5	3 5	3 7	3 7	3 7	3 7	3 7	3 7
	CC		0.22 -0.30 -0.35 -0.52	0.50 -0.09 -0.08		0.55 -0.20 -0.29 -0.46	0.52 -0.27 -0.25
	P		2.E-01 8.E-02 4.E-02 1.E-03 2.E-03 6.E-01 7.E-01		7.E-04 3.E-01 9.E-02 6.E-03 1.E-03 1.E-01 1.E-01
	N		3 7	3 7	3 7	3 7	3 7	3 7	3 7		3 5	3 5	3 5	3 5	3 5	3 5	3 5
	CC			-0.50 -0.80 -0.14	0.22	0.21	0.19			0.01	0.18 -0.04	0.26 -0.40 -0.34
	P			2.E-03 3.E-09 4.E-01 2.E-01 2.E-01 3.E-01			9.E-01 3.E-01 8.E-01 1.E-01 2.E-02 4.E-02
	N			3 7	3 7	3 7	3 7	3 7	3 7			3 5	3 5	3 5	3 5	3 5	3 5
	CC				0.86	0.37 -0.32 -0.14 -0.08				0.54	0.37 -0.29	0.00	0.04
	P				8.E-12 3.E-02 5.E-02 4.E-01 6.E-01				6.E-04 3.E-02 8.E-02 1.E+00 8.E-01
	N				3 7	3 7	3 7	3 7	3 7				3 7	3 7	3 7	3 7	3 7
	CC					0.42 -0.41 -0.11 -0.07					0.57 -0.49	0.09	0.22
	P					1.E-02 1.E-02 5.E-01 7.E-01					2.E-04 2.E-03 6.E-01 2.E-01
	N					3 7	3 7	3 7	3 7					3 7	3 7	3 7	3 7
	CC						-0.85	0.05	0.09						-0.85	0.05	0.09
	P						4.E-11 8.E-01 6.E-01						4.E-11 8.E-01 6.E-01
	N						3 7	3 7	3 7						3 7	3 7	3 7
	CC							-0.38 -0.41							-0.38 -0.41
	P							2.E-02 1.E-02							2.E-02 1.E-02
	N							3 73 7							37	37
	CC								0.94								0.94
	P								2 . 1 E -1 8								2.E-18
	N								3 7								37

Table 2b

 2b

		Stati	[Hg] Asco	(Hg) Asco	[Fe] Asco	[Al] Asco	Clay	Sand	C	S	[Hg] NH4OH	(Hg) NH4OH	[Fe] NH4OH	[Al] NH4OH	Clay	Sand	C	S
		stics	(µg g -1 )	(%)	(mg g -1 )	(mg g -1 )	(g/100g)	(g/100g)	(g/100g)	(g/100g)	(µg g -1 )	(%)	(mg g -1 )	(mg g -1 )	(g/100g)	(g/100g)	(g/100g)	(g/100g)
		CC	0.89 -0.23 -0.27 -0.40 -0.52	0.50 -0.09 -0.08	0.96	0.10 -	0.15 -0.27 -0.52	0.50 -0.09 -0.08
		P	1.E-13 2.E-01 1.E-01 2.E-02 1.E-03	2.E-03 6.E-01 7.E-01	7.E-21	5.E-01		4.E-01	1.E-01	1.E-03 2.E-03 6.E-01	7.E-01
		N	3 7	3 7	3 6	3 6	3 7	3 7	3 7	3 7	3 7	3 7		3 7		3 7	3 7	3 7	3 7
		CC		0.12 -0.34 -0.45 -0.53	0.48	0.04	0.02		0.31 -	0.18 -0.25 -0.50	0.53 -0.15 -0.13
		P		5.E-01 4.E-02 6.E-03 8.E-04	3.E-03 8.E-01 9.E-01		6.E-02		3.E-01	1.E-01	1.E-03 8.E-04 4.E-01	4.E-01
		N		3 7	3 6	3 6	3 7	3 7	3 7	3 7		3 7		3 7		3 7	3 7	3 7	3 7
		CC			-0.26 -0.00	0.25 -0.25	0.39	0.35			-	0.08	0.14 -0.02	0.18 -0.13 -0.05
		P			1.E-01 1.E+00 1.E-01	1.E-01 2.E-02 3.E-02				7.E-01	4.E-01	9.E-01 3.E-01 5.E-01	8.E-01
		N			3 6	3 6	3 7	3 7	3 7	3 7				3 7		3 7	3 7	3 7	3 7
		CC				0.85	0.30 -0.32 -0.10 -0.03					0.41	0.37 -0.32	0.47	0.43
		P				8.E-11 8.E-02	6.E-02 6.E-01 9.E-01					1.E-02	2.E-02 5.E-02 3.E-03	7.E-03
		N				3 6	3 6	3 6	3 6	3 6						3 7	3 7	3 7	3 7
	[Al] Asco (mg g -1 )	CC P N					0.56 -0.53 4.E-04 8.E-04 7.E-01 3.E-01 0.06 0.17 3 6 3 6 3 6 3 6						0.46 -0.44 4.E-03 7.E-03 2.E-01 0.23 3 7 3 7 3 7	0.33 5.E-02 3 7
	Clay (g/100g)	CC P N						-0.85 4.E-11 8.E-01 6.E-01 0.05 0.09 3 7 3 7 3 7							-0.85 4.E-11 8.E-01 0.05 37 37	0.09 6.E-01 37
	Sand (g/100g)	CC P N							-0.38 -0.41 2.E-02 1.E-02 3 73 7								-0.38 -0.41 2.E-02 1.E-02 37 37
	C (g/100g)	CC P N								0.94 2.E-18 37	C (g/100g)							0.94 2.E-18 37

Acknowledgments

This research was supported mainly by the CNRS through its "Mercury in French Guiana" research program and by the Boulanger Mine Company (CMB -Cayenne) through a Ph.D. granted to Stéphane Guédron. The authors thank Manuel Munoz and Mathieu Corazzi (LGCA -Grenoble) for the assistance with µXRF mapping, Vincent Perrot and Nicolas Geoffroy (LGIT -Grenoble) for technical support during the project, and Max Sarrazin (IRD -Cayenne) who performed soil granulometry and C, N and S analyses.