Pascal Bonnaud

Philippe Santenoise

D Tisserand

Gilles Nourrisson

Bonnaud

) Nourrisson

Impact of compaction on two sensitive forest soils in Lorraine (France) assessed by the changes occurring in the perched water table

Keywords: Forest soils, compaction, restoration, perched-water-table

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

1-Introduction

Fine textured soils, more especially soils with a silty texture, are known to be very sensitive to physical degradation (MEDDE, 2015). This texture associates both the low reactivity of sands (small particles of quartz and feldspars with low specific area and no shrinking properties, and low cation exchange capacity) and the potential low permeability of de-structured clayey material. Sensitivity to degradation is increased with soil acidity because soil aggregation is low and unstable. Antagonistic characteristics occur in acid soils: low levels of flocculent alkaline earth cations (Ca and Mg) but high levels of flocculent Al [START_REF] Haynes | Influence of lime, fertilizer and manure applications on soil organic matter content and soil physical conditions[END_REF], high levels of protonated organic matter and low biological activity. Aggregation regulates the organic matter turnover, the water and solute transfer, the gas exchange and consequently the microbial community structure and function [START_REF] Six | A history of research on the link between (micro)aggregates, soil biota, and soil organic matter dynamics[END_REF].

The mechanization of silviculture can lead to soil deformation when the applied pressure exceeds the soil bearing capacity; this phenomenon increases with soil moisture (Ampoorter et al., 2012). Compaction, which is the decrease in porosity without any change in soil mass (de Paul and Bailly, 2005), represents a major risk for soil sustainability. According to its intensity, to the soil characteristics and moisture, it can drastically change soil properties e.g. bulk density [START_REF] Miller | Soil compaction and conifer growth after tractor yarding at three coastal Washington locations[END_REF], porosity and mainly macro-porosity (Herbauts, 1996;[START_REF] Bruand | Backscattered electron scanning image of soil porosity for analysing soil compaction around roots[END_REF], soil hydraulic properties [START_REF] Horton | Effect of compaction on soil hydraulic properties[END_REF], water and gas transfer [START_REF] Stepniewski | Effects of compaction on soil aeration properties[END_REF], and consequently soil biota (Doran and Power, 1983;Brussaard and Faassen, 1994). Compaction changes root configuration and growth [START_REF] Sands | Compaction of sandy soils in Radiata pine forests. II-Effects of compaction on root configuration and growth of Radiata pine seedlings[END_REF]Wronski and Murphy, 1994), root penetration (Heilmann, 1981) and it alters water and nutrient uptake of trees (Goranson et al., 2008;[START_REF] Alavi | The impact of soil moisture on stem growth of spruce during a 22-year period[END_REF]. It also decreases the earthworm biomass and their burrowing activity (Jordan et al., 2003).

The mechanization of forest practices represents a major risk for forest soil sustainability for fine textured acidic soils with low coarse material content if traffic of machinery is not strictly regulated according to soil moisture. Inappropriate management practices could lead to more or less irreversible changes [START_REF] Pischedda | Pour une exploitation forestière respectueuse des sols et de la forêt[END_REF] because, on the one hand, remediation of physical degradation is costly and technically difficult, and on the other hand, natural restoration of porosity is slow, especially in acidic soils where earthworms are not efficient [START_REF] Lee | Earthworms, their ecology and relationships with soils and land use[END_REF], dominated by epigeous worms whose habitat is limited to the soil surface layers [START_REF] Lee | Soil fauna and soil structure[END_REF]. Observations made in various situations, very often uncontrolled in terms of soil moisture at the time of compaction, but also in terms of machinery (real constraint per soil unit area, number of passes…), led to the conclusion that restoration of soil porosity takes a long time. For example, observations made on skid trails showed that the soil remained compacted for 30-40 years (literature quoted by Wronski and Murphy, 1994); observations made on military fields still showed compaction traces after 50 to 100 years; in Germany, the decreased gas diffusion still persisted after 10 years [START_REF] Schack-Kirchner | Struktur und Gashaushalt von Wald[END_REF]; the restoration of porosity and soil organic matter turnover rate was not achieved 10 years after compaction [START_REF] Rab | Recovery of soil physical properties from compaction and soil profile disturbance caused by logging of native forest in Victoria Central Highlands, Australia[END_REF]. In some specific conditions, restoration was more rapid e .g. soil bulk density was restored 5 years after compaction in a sandy soil [START_REF] Page-Dumroese | Soil physical property changes at the North American Long Term Soil Productivity sites ; 1 and 5 years after compaction[END_REF].

In fine textured soils with low permeability in the deep soil layer due to an abrupt change in clay content, a perched water table (PWT) generally occurrs after heavy rain events when soil is wet and evaporation rate low [START_REF] Rockefeller | Perched water table responses to forest clearing in northern Idaho[END_REF] i.e. during the winter period in temperate countries. This is an aggravating factor for soil degradation.

It could then be hypothesized first, that mechanization of practices in forests developed on soils sensitive to physical degradation, would reduce the soil porosity and increase the occurrence frequency of a PWT leading to hypo or anoxia processes in the soil, decreasing its ability to sustain its major functions, and second that the time lapse before complete recovery on this soil group would depend on soil mineral fertility i.e. quicker when higher because of its role on soil biological activity.

Forest soils on the Lorraine plateau fall in the category of non-hydromorphic but very sensitive soils to physical degradation (silt material laying on heavy clay, acid conditions) [START_REF] Staub | Sensibilité des sols forestiers en lorraine, cartographie et outil technique de mise en oeuvre[END_REF]. Because there is little information regarding the impact of land use on episaturation and more or less no information on the duration of the phenomenon, we selected physical and chemical characteristics of the perched water table as an indicator of soil degradation and restoration in two experimental sites, where a controlled compaction was carried out.

The objectives of the present study were then: i-To identify the impacts of a controlled and limited soil compaction of sensitive soils on the occurrence of a perched water table (frequency, level) and on geochemical indicators of redox phenomena (ferrous iron, sulphur, manganese, total geochemistry), ii-To clarify the effect of the mineral fertility level on these processes, comparing two soil environments in the plateau lorrain, submitted to the same stress of compaction, iii-To monitor the dynamics of the same parameters on a medium term, in order to identify the time necessary for recovery of soil porosity, 2 Material and methods

Study sites

Location and climate: two experimental sites were set up in the North-East part of France, at Azerailles (54) (AZ thereafter), in the 'Hauts Bois' estate forest (48° 29′19″N,6°41′43″ E) and at Clermont-en-Argonne (55) (49° 06′ 23″ N, 5° 04′ 18″ E) in the 'Grand Pays' estate forest (CA thereafter). The elevation of the sites is respectively 270 and 300 m a.s.l. for AZ and CA with a maximum of 8 m (AZ) and 3 m (CA) level variation within each site. The average annual precipitation and temperature over a 30-year period (Météo-France data), are 920 and 1000 mm.year -1 and 8.5°C and 9°C respectively for AZ and CA.

Forest stand prior to harvesting: the previous stands were a mature high forest dominated by Fagus sylvatica L. and secondarily by Quercus petraea L. at AZ, and high forest originating from the transformation of an old coppice with standards at CA, dominated by Fagus sylvatica L. and Quercus petraea L.with some Betula verrucosa Ehrh., Acer platanoides L.

and Populus tremula L.

Soil characteristics: soil description and selected soil parameters were measured before setting up the experimental designs, on samples taken from pits distributed over the entire site area (5 ha): 17 pits were dug at AZ and 13 at CA. For fine earth characterization, soil samples were collected in each pit at systematic depths (0-10; 10-20; 20-30; 30-45; 45-60; 60-75, 75-90; 90-110 cm). Soil samples were air-dried at the laboratory and sieved to separate coarse material from fine earth (<2mm); soil moisture was measured after oven-drying at 105°C for all samples. To estimate the soil bulk density, 250 cm 3 steel cylinders were used to collect two replicated samples every 10 cm in all the pits. Bulk density was calculated as the ratio between the soil mass (oven dried at 105°C over 72h) and the cylinder volume (a correction was made according to the coarse fragment content). The density of the solid was measured on dried and finely ground (200 μm) soil samples (one per block × depth) using pycnometers (Micrometrics).

Methods used for soil analysis

Particle size distribution was measured after the digestion of organic matter by H2O2, by sedimentation in deionized water, adding when necessary some drops of NaOH 1N for a perfect suspension; sampling was carried out with a Robinson pipet at a fixed level in the column, at times corresponding to specific particle sizes according to the Stockes law at a fixed temperature; particles bigger than 50µm were separated by sieving ; soil pH was measured in both 1M KCl and in deionized water, with a soil to solution weight ratio of 1:2.5 (Mettler TSDL25 pH meter). Cation Exchange Capacity and exchangeable cations were measured by the colbaltihexamine method (Ciesielski et al., 1997). Total soil Corg and Norg were determined with a elemental analysis system (ThermoQuest CE Instrument NCS 2500); total content of Al, Fe, Mg, Ca, K, Na, Mn in soil fine earth (<2mm) were determined after a HF digestion and ICP-AES measurements at the Inra-Soil Analysis Laboratory -Arras). Total chemical clay analysis was performed by the CNRS-CRPG rock and mineral analysis Laboratory using LiBO2 alcaline fusion and dissolution in 1N HNO3; concentrations were measured with a ICP-OES instrument for major element and by ICP-MS for trace elements (Carignan et al., 2001). Fe-oxides were quantified according to [START_REF] Mehra | Iron oxide removal from soils and clays by a dithionitecitrate system buffered with sodium bicarbonate Clays Clay[END_REF].

Soil clay mineralogy was characterized for 8 soil layers sampled from one central pit at each site (8 horizons each). The clay fraction was separated from the fine earth fraction (<2mm) according to [START_REF] Robert | Méthode de préparation des argiles des sols pour les études minéralogiques[END_REF]. The soil organic matter cement was digested using daily additions of dilute hydrogen peroxide (20 volumes which corresponds to a 1:5.5 dilution of the 110v mother solution) and heating at about 40°C until total elimination of organic carbon. Samples were then transferred to glass columns filled with deionized water to separate particle classes according to Stockes law of sedimentation for dilute systems. The clay fraction (<2 µm) and the fine silts were separated by siphoning until total disappearance (10 to 15 siphoning operations are usually necessary), then, the coarser fractions (coarse silts, fine and coarse sands) were quantified by sieving with deionized water. Clay minerals were then saturated by a cation absent of the clay structure (Ba) in order to directly obtain the Cation Exchange Capacity (CEC) from total chemical analysis.

Site setup and monitoring

Both sites were clear-cut over a 6 ha surface area, logs were removed using a cable-harvesting system, and in order to minimize the soil disturbance, all the slash was removed manually or with an iron horse.

Experimental design: each site was divided into three blocks positioned after a low scale soil mapping, each treatment was randomly distributed in each block. Each individual plot is 30 × 50 m. In AZ, four treatments were applied: control (C). trafficked (T), trafficked and decompacted by disking (D), and trafficked and local de-compaction at the plantation points (P).

At CA, because the soil was more acidic, a liming treatment was added, control limed (L) and trafficked limed (TL). In the present study only C and T treatments will be considered.

Experimental compaction:

In each trafficked plot, the same full-loaded forwarder drove for an equivalent of two passes. The forwarder (VALMET 840) traffic, took place in May 2007 and March 2008 respectively in the AZ and CA sites. The tyres (60 cm large) were inflated to the same pressure (360 kPa) and the total weight of the machine was of 23 and 17 t in the AZ and CA sites respectively, because the CA site was wetter at the time of traffic than the AZ site.

At AZ, the mean soil surface volumetric water content of the 0-10 cm layer, was 0.41 m 3 m -3 and ranged from 0.28 m 3 m -3 to 0.53 m 3 m -3 at the time the forwarder drove on the soil, while at CA it was 0.47 m 3 m -3 and varied from 0.25 to 0.59. Heavy traffic resulted in 'ruts' averaging 5 cm in depth at both sites [START_REF] Goutal | Soil compaction due to heavy forest traffic: measurements and simulations using an analytical soil compaction model[END_REF].

Compaction effects on bulk density and soil porosity: changes in bulk density were measured by comparing values in non compacted (2 replicates x 6 horizons [each 10 cm from 0 to 60 cm] x 3 blocks) and in compacted areas (4 replicates x 9 horizons [each 5 cm from 0 to 30 cm and then each 10 cm from 30 to 60 cm depth] x 3 blocks) one month after compaction; very deep ruts and creeping zones were avoided during sampling.

Soil porosity was calculated from bulk (da) and real (dr) soil densities using the formula total porosity = 1-(da/dr). Soil macroporosity was measured by the Wind methodology in one profile of each block at depths [0-10, 15-25, and 30-40 cm], as described by [START_REF] Hopmans | Chapter 3. The soil solution phase. Simultaneous determination of water transmission and retention properties[END_REF]. Briefly, soil micro-porosity was derived from the parameters obtained by the Wind method, using the relation between the matric potential and the pore diameter given by the Jurin/Young-Laplace laws (pF=log(h)); pF is the matric potential and h is the height in cm of the water column in the capillary; then ∆ h is inversely proportional to the pore diameter.

Monitoring of the meso-and pedo-climates in each site, rainfall, atmospheric vapour saturation, soil temperature, and soil moisture were recorded continuously (every four hours) on specific data loggers (DL2e Data Logger, Delta-T devices Ltd, England for rainfall and soil temperature, and Trase "B.E." by Soil Moisture, Sols Mesures -France, for soil water content) located approximately in the centre of the experimental design. Time domain reflectometry (TDR) probes and temperature sensors (five replicates per depth × treatment) were inserted into the soil at three depths (15, 30 and 50 cm in the undisturbed soil; 10, 25 and 45 cm in the compacted soil) (only one block equipped in each site). The captor depths in the trafficked plots were selected to account for the volume change after compaction. The TDR measurements (soil dielectric constant) were converted to volumetric water content using calibration curves according to [START_REF] Heathman | Time domain reflectometry field calibration in the Little Washita River Experimental Watershed[END_REF] and derived from laboratory calibration of TDR data, using undisturbed soil cores of each site.

The mean volumetric water content per day and the mean bulk density values were used to calculate the daily air-filled porosity, defined as the volume occupied by air to the volume of soil.

[1]

where εA is the soil air-filled porosity in m 3 m -3 , ρB is the soil bulk density in g cm -3 , ρS is the density of the solid in g cm -3 , and θV is the soil volumetric water content in m 3 m -3 .

The soil perched water table level was measured using Diver pressure probes (Diver, by Van Essen Instruments, SDEC France), collecting data every four hours from June 2009 (figure 1

B A V S ρ ε θ ρ = - - 1B
). These captors were installed in piezometers, distributed over the entire area of the plots, in the two C and T treatments (2 per treatment/plot and per block). The piezometers were built with a porous 3 cm diameter pipe inserted in a vertical drilled hole at a maximum depth less than 60 cm in order to avoid perforating the clayey floor, except one piezometer specifically installed in the clay layer at about 90 cm depth. Quartz sand was used to ensure the contact with soil, and bentonite was introduced around the top ten cm of the pipe in order to avoid direct water transfer from the soil surface.

The chemistry of the water table was collected each month since 2008 at both sites with a specific device designed to collect water without any contact with the atmosphere, especially for analysing the Fe 2+ and sulphur concentrations; samples were also used for total chemistry (figure 1A). This device consists of a solid compartmentalized casing, perforated at specific depths in order to collect specific levels of the PWT in contact with the main differentiated soil layers e.g. from 0 to 10, between 15 to 25, and between 45 to 55 cm (one was installed in the clay layer at 90 cm in the C treatment of each block).

Total chemistry of the PWT: after collection, samples were filtered next day at the laboratory with 0.45 µm Metriciel® acetate membrane filters and stored in the dark at 4°C. Samples were analyzed for pH (Mettler DL 7O ES Titrator ); anions (Cl -, NO3 -, H2PO4 -, NO2 -, SO4 2-, F -) were measured by ion chromatography (Dionex ICS2100); N-NH4 + was determined by molecular absorption spectrometry (Skalar San++ System) ; total Si, Al, Fe, Mg, Ca, K, Na, P and S were determined by ICP-AES (Agilent Technologies 700 series) ; total dissolved organic carbon (TOC) was measured with a Shimadzu TOC-L instrument.

Ferrous iron and sulphur in the PWT: dissolved reduced elements were used as indicators of the redox status of the PWT. Measurements were organized to allow the most accurate quantification: tests showed that measurement performed the next day in the laboratory were the most appropriate. Samples were first filtered through 0.45µm cellulose acetate membrane with filters fixed on syringes in order to avoid all contact with atmosphere. Quantification was performed by spectrophoto-colorimetry (Shimadzu UV-1800). All measurements were duplicated. Ferrous iron was quantified using the phenantroline method (Fortune and Melon, 1938): two mL of a buffer solution made of an admixture of potassium hydrogen phthalate and hydrochloric acid and 2 mL of a phenantroline solution were added to 5 mL of filtered samples. Measurements were made at 510 nm; calibration standards ranged from 0 to 2.00 mg.L -1 . Detection limit was 0.03 mg.L -1 .

Sulphur was measured using the methylene blue method (the reaction of sulphur with FeCl3

and N,N-dimethyl-p-phenylenediamine form methylene blue) (Centre D'expertise En Analyse Environnementale Du Québec, 2010): 1mL of the reagent was added to 5 mL of the filtered sample. Detection of the complex was made at 664 nm; calibration standards ranged from 0 to 1.0 mg.L -1 . Detection limit was 0.1 mg.L -1 .

Calculations and statistics

All calculations and statistics were carried out with R software (Core Team R, 2013) on two datasets per site corresponding to the PWT main physical characteristics i.e. depth level, thickness (from 2009 to 2015) and chemical properties (from 2008 to 2016).

A new variable, the annual average duration of PWT, was calculated from the PWT level dataset; it represents the number of days per year during which the PWT was at a level lower than about 44 cm depth, i.e. the clayey floor. For this, we calculated the average annual duration of corresponding captors for each plot, and weighted the average of each captor by considering the real number of days per year during which the captor was functional.

An analysis of variance (anova) was applied on each site from a linear model to test the significance of the fixed effect of one or more factors, related to the soil treatment, the period of time (year and seasons) and the spatialization (depth), on different quantitative variables:

PWT (1) daily level, (2) annual average duration and (3) chemistry properties (i.e. 21 chemical compounds). For the two first quantitative variables, an analysis was carried out either considering all blocks or per block. The general form of the model is the following:

= + ( ) ( , ) + + (I)
With the quantitative variable, the grand mean of the model, ( ) the -th fixed effect of an individual factor ( = 1) or combining a number of factors, the random effect normally distributed with mean 0 and variance . and the random error term normally distributed with mean 0 and variance . .

For the PWT daily level, a total of three factors (soil treatment, year and season) and all possible double and triple interactions were tested as fixed effects. The factor representing the number of the captor was added in the model as a random effect, and the variance of the error term was weighted by the number of measures collected for each day. Otherwise, groups for the season factor were defined from the astronomical dates and nested within groups of the year factor, to test interactions combining the two periods of time. Thus, each year started on

March 21 th and finished on March 20 th of the following year. For the analysis per block, the data of block 2 at CA collected from 2009 to 2012 were excluded because of a large amount of missing data. For the PWT annual average duration, only the soil treatment factor was tested as a fixed effect and a non-random effect was added in the model. For the PWT chemistry, three factors corresponding to the soil treatment (C and T), the annual time period and the sampling depth with all possible double interactions were tested as fixed effects at CA, and only the two first factors with their interaction at AZ. The interaction between the three factors was not considered in the model because the sample size was too small. The factor related to the number of the block was added in the model as a random effect. The sampling depths retained in the analysis are 25 and 45 cm for CA and 45 cm for AZ. For the other depths, sample sizes were too unbalanced between the two soil treatments.

In order to obtain a general overview of the compaction effect on PWT solutions, we used a standardized principal component analysis (PCA), first for individual sites, and second for comparing both sites. The PCA highlighted the impact of several relevant factors (site, block, soil treatment, and annual and seasonal time period). The PCA led to reducing the initial data represented in a -dimensional space to a -dimensional subspace, such as < . The new -dimensions generated represent the principal components (PCs), a linear combination of initial quantitative variables. We only considered a limited number of PCs ∈ {1, … , } from the PCA model, representing about 50 % of the total cumulative explained variance (maximum 4).

Otherwise, we calculated the " 2 -Hotelling's and #-residual distances to detect and identify outliers in the dataset [START_REF] Jackson | [END_REF]. The indices provided complementary information by describing the variation of each observation within and outside the newdimensional subspace respectively. Consequently, deleting observations with a high value of the " 2 -Hotelling's distance would have a large impact on the PCA model, but deleting those with a high value of the #-residual distance would have a limited impact on results. Finally, factors were represented as the centroid of observations projected in the -dimensional subspace, which belong to it. The dispersion of observations around the centroids, was represented by a 95 % confidence ellipse (Worley et al. 2013).

3-Results

The soils

General characteristics

At both sites soils are classified as Luvisol (ruptic) according to IUSS (2014), they are polycyclic i.e. developed from two geologic materials, a continental quaternary silt loam layer approximately 50 cm thick, laying on a more ancient clayey material. At AZ the fluvial loamy quaternary layer lies on weathered marls of the Keuper; in CA the loamy quaternary material lies on weathered gaize of the Cenomanian. This strong textural discontinuity causes a limited temporary water logging, but did not lead to hydromorphic soils; hydromorphic features were limited in both cases to the very lower part of the silty layer, at the contact with the clay rich layer. Consequently, these soils are considered as highly sensitive to compaction.

Nevertheless, this feature masked significant differences between the soils of the two sites [START_REF] Goutal | S Natural recovery rate of soil specific volume following forest soil compaction[END_REF][START_REF] Bedel | Unexpected calcium sources in deep soil layers in low-fertility forest soils identified by strontium isotopes (Lorraine plateau, eastern France)[END_REF] e.g. the clay content in both the upper and lower layers are lower at CA than at AZ respectively (13 to 15 at CA vs 22 to 24 at AZ) and (33 to 34 at CA vs 45 to 60 at AZ) (table 1); the clay mineralogy at AZ is an almost pure Illite in the deep soil layer and an complex admixture of Illite, kaolinite, chlorite and vermiculite, associated with interstratified and intergrade minerals in the upper soil layers. At CA, the clays in the deep clayey layer consist in an admixture of kaolinite, illite and a swelling clay of the Febeidellite group. In the soil upper layers, the same spectrum was identified, but the swelling Fe-Bedellitic material strongly decreased although still present in both pure and interstratified phases [START_REF] Bedel | Soil aggregation is a relevant indicator of soil mineral fertility: the case study of soils in the plateau lorrain[END_REF].

Soil geochemical context: both soils are acidic, at CA the pHwater was about 4.5 in the upper soil layers (0-45cm) and around 5.0 in the deep clayey horizons (below 60 cm), while at AZ the upper organic horizon has a significantly higher pH of about 4.8 that decreases to 4.6 in the loamy horizons poor in organic matter (10-45cm), then increases to 5.0 in the deeper clayey horizons. Organic C content was the same in the [0-10 cm] layer of the two sites (2.6 g 100g -1 ), but about two fold lower in the next horizons at CA compared with AZ. Norg is lower at CA (1.4 vs 1.8 g kg -1 in the [0-10 cm] horizon), and then about two fold lower in CA compared to AZ. The C:N ratio was higher in CA than in AZ soils (18 vs 15 on the [0-20 cm] layer). Cation exchange capacity at CA, varied from 3.5 to 4.0 in surface and from 16 to 18 cmol+ kg -1 in depth and at AZ it varied from 4.0 to 4.5 in surface and from 12 to 15 cmol+ kg -1 in depth. The "base" cation saturation rate was about two fold higher for comparable depths in the upper layers at AZ than at CA (63 vs 29% respectively for [0-10 cm] ; 24-30 vs 12-15% respectively for [10-45 cm]), but similar in the deep layers (50-70% at AZ vs 45-60 % at CA).

Changes in soil bulk density and porosity due to compaction

The initial dry bulk density was systematically about 10% higher at CA than AZ for both C and T treatments (Table 2). Because very limited recovery of bulk density was observed during site monitoring, this data set was used for the soil porosity and soil water reservoir content calculations. Total porosity was functionally linked to dry bulk density, with a common statistical linear relation, for both sites and treatments. On average, macro porosity represented 40 % of the total porosity at AZ and 48 % at CA. After compaction macro porosity was reduced by 70 % at AZ but only 56 % at CA.

Physical parameters of the perched water table (PWT)

level and duration of the PWT

The reference level expressed relative to the soil surface (level 0) is about the same at Azerailles (AZ) and at Clermont en Argonne (CA) ca. about 44-45 cm (table 3). It corresponds to the minimum level of measurement of the "Divers".

At both sites, and for both the C and the T treatments, the highest mean and maximal levels occurred during the winter period. In both cases the highest levels were for the compacted treatment, but the difference with the control was larger at AZ than at CA, and it was more pronounced for the mean (60%) than for the maximum (18%) levels.

The thickness of the PWT is another way to present the data (table 3):

-In winter, in C the mean thickness was 2.2 cm in AZ while it was 5 cm in CA; the maximum thickness was 18.8 cm in AZ while it was 25.6 cm in CA, -In winter, in T the mean thickness was 12.6 cm in AZ while it was 9.5 cm in CA; the maximum thickness was 33.1 cm in AZ while it was 38.2 cm in CA.

In the control C, considering all the seasons, the mean values for the thickness of the PWT during 7 years tended to be larger in CA than AZ, for both mean and maximum values, while in the compacted T treatment, they tended to be the largest in AZ except for the maximum levels in autumn and in winter.

Over the 7 years of monitoring, during the winter period when the PWT occurred the most frequently, the maximum levels in both C and T treatments did not change significantly at AZ. These maximum levels varied more widely in the C (extreme values of -16.5 cm in 2010 and -35 cm in 2013), than in the T (extreme values of -8.3 cm in 2015 and -11.9 cm in 2012)

(data not shown). The mean PWT levels during the same winter period showed a significant decrease for C (r = 0.71 significant for a probability of 5%) and a quasi statistically significant increase in T (r = 0.68 significant for a probability between 5 and 10 %). The fluctuation was larger in the T (range between -36.8 cm in 2010 and -27.8 cm in 2014 and 2015) than in the C treatment (range between -40.9 cm in 2013 and -40.8 cm in 2010). Over the 7 years, the winter rainfall did not change significantly (range between 140 and 260 mm per year) (figure 2A).

At CA the maximum level of the PWT in winter did not change significantly between 2009 and 2015 in the C treatment, while it decreased significantly in the T treatment (r=0.76 significant for a probability of 5%). The range of variation was from -15.1 cm in 2010 and -23.8 cm in 2013 in the C, and, between -2.3 cm in 2010 and -10.5 cm in 2015 in the T treatment (data not shown). During the same period, the mean level significantly increased in the control C (r = 0,92 significant for a probability of 5%), while it did not change significantly in the compacted T plots (figure 2B). During the winter period, the rainfall increased significantly between 2009 and 2015 (r = 0.81); this was also the case when cumulating autumn and winter rainfalls. days in CA, site where nevertheless the increase in frequency was evenly spread out during the whole wet period.

Additional relevant information came from the mean duration of a PWT event, comparing the C and T treatments, for different fixed levels, at the two experimental sites (table 5). A first divergence between the C and T treatments was observed for the number of events; this difference increased with the thickness of the PWT, e.g. the T: C ratio varied from 1.8 for the 5 cm thickness to 6.7 for the 20 cm thickness at AZ, while it varied from1.9 to 2.6 at CA for respectively the same levels. A larger difference appeared when considering the duration of events e.g. in C the mean duration was 4 to 5 times higher at AZ than at CA, and in the T it was 12 to 17 times higher at AZ, according to the thickness selected (5 to 20 cm). The ratios T: C were of 3.4 to 3.9 at AZ while they only varied from 1 to 1.2 according to the thickness considered at CA.

The changes in terms of duration for the occurrence of PWT during the 7 years of observation, showed no significant trend for the whole year, in both C and T treatments at CA and AZ. During the winter wet period no significant trend was noticed at CA but a significant increase in the number of days with PWT appeared in the T treatment of AZ (from 50 to 70 days), and a concomitant trend (only significant at 10%) to a decrease in the duration of PWT in the control C (from 20 to 10 days) (figure 3).

In terms of mean residence time of the PWT (figure 4), at AZ, no significant trend was noticed for the T (mean value =93 hours), but a constant decrease (only significant at 10%) from 40 to 20 hours in the C plots (mean value =30 hours) was found during the winter period (scenario 15 cm). Fluctuations were far more limited in the C than in the T. At CA, the pattern was rather different with very similar significant decreasing trends (significant at 5%) in winter for T (mean value =12 hours) and C (significant at 10%) (mean value = 9hours). Differences between the C and T treatments at CA decreased from 2008 and 2011 and the MRT of the PWT was very similar between treatments thereafter.

Chemistry of the PWT

Compaction effect on element concentration in the PWT

At Azerailles in the C, no sample was collected for water chemistry at 15 cm depth and only one sample was collected at 30 cm. Statistics were only possible for the deeper soil layer to directly compare C and T plots, which of course represents only a part of the compaction effects. Mean results for the observation period presented in the table 6 show that the effect of compaction was strongly significant for most elements, directly (treatment effect 15 over 22 measured elements) or indirectly (interaction treatment x year, 6 over 22 cases). At 45 cm depth, compaction increased the Fe, F, SO4 2-, S, P, Mn 2+ , Mg 2+ , Na + and DOC concentrations, but decreased Cl -, Si, Ca 2+ , NH4 + , TN and Norg concentrations. Year effect was significant (18 over 22 cases) for all elements but Fe 2+ , Si, K + and H + . The interaction between treatment and year was significant for Cl -, NO3 -, SO4 2+ , Na + , TN, Norg concentrations. In general, in the T treatment, concentrations decreased with depth for all elements except for F, NO3 -, SO4 2-, Si, Na + , NH4 + .

At CA where the frequency and duration of PWT were higher than at AZ in the soil surface layers, the PWT chemistry dataset was sufficient to carry out statistical analysis for the medium and deep PWT levels (the number of samples was 5 vs 55, 37 vs 96 and 203 vs 225 respectively for C and T and for the 10, 25 and 45 cm). The compaction effect (table 7) was significant for both levels for most elements (14 and 17 vs 22 and 17 and 19 vs 22, respectively for the 25 cm and 45 cm depths). For the 25 cm depth PWT level, compaction increased Fe 2+ , NO3 -, Cl -, P, Fe, Al, NH4 + and DOC concentrations, but decreased F, SO4 2+ , Si, and Mg 2+ concentrations. For the 45 cm depth PWT level, no significant differences were observed between C and T treatments.

Correlations between anions (DOC, F -, Cl -, NO3 -, SO4 2-) and cations were used to identify the general impact of compaction on the geochemical control of elemental chemistry in the PWT at both sites.

At AZ, in the upper level (10 cm) of the T plot, the DOC controlled Fe and Al concentrations, but also secondarily Mg, Ca and K. Nitrate had little influence, and SO4 --and Cl -ensure the control of alkaline and alkaline-earths cations. At 25 cm depth in the T, the same geochemical control was observed, but nitrate influence increased. The impact of compaction was only statistically analysed at 45 cm depth, where C and T showed no great differences in terms of relative geochemical control: the DOC effect became negligible, nitrate, sulphate and chloride controlled the cation mobility. The compaction effect led on concentration changes of the anion drivers (see table 6), especially for SO4 2-, which could be an expression of Scompounds reduction, sulphate still being in equilibrium in a moderately reductive environment (White, 1998).

At CA, the compaction resulted in an increase in DOC control on Fe and Al for all levels of the PWT, a decrease in NO3 -, SO4 2-and Cl -controls on cations at the upper levels, but in the reinforcement of the role of these anions for the deepest level. PCA was also very helpful for highlighting the site effect: 49.2% of explanation of the variance was obtained with only 3 axis. Most variables were involved in the site discrimination. The different types of soil bedrocks easily explained both anion and cation differences. The similar constraint from compaction led to site dependant responses. The site effect is very well discriminated on all the combinations of the 3 first axis (see figure 2 of the supplementary material section, presenting data on the combination of axis 1 and 2). Its indicated that the single soil type in the two sites, encompassed rather different behaviours, illustrated by not a unidirectional but a centrifugal translation of C and T centroids along the axis 1.

Time changes on element concentration in the PWT

Before presenting the results, it is necessary to underline the difficulties occurring, first because of the sampling frequency for geochemistry, which was done once a month in the present study. Second, the changes in PWT geochemistry integrate several effects already presented, namely: i-the clear-cutting effect which was considered as real if present in both C and T treatments, but considering a possible delayed effect at 45 cm depth, ii-the compaction effect that gave significant differences between C and T treatments, iii-the year-to-year changes in rainfall that increased the variability with a possible confounding effect in case of gradient, and iv-the soil porosity restoration effect which tended to reverse or at least decrease the initial differences between treatments.

At AZ, where sampling concerned more or less exclusively the deeper soil layer in the control, the clear-cutting effect appeared for some elements DOC, Cl -, SO4 2-and NH4 + , but was delayed for the three last ones. The compaction effect was significant for numerous elements like Cl -, Si, Ca 2+ (<0 impact) and for SO4 2-, DOC, Mg 2+ , Na + , NH4 + , Fe 2+ , Mn 2+ (>0 impact) (table 7). The year-to-year variability was high for almost all elements. The most general trend was a decrease in the initial effect of both clear-cutting and compaction, and then a stabilisation of the compaction effect (figure 7 figure 5; case of Fe2 + ). Only in two situations, the dampening of the compaction effect was observed: the effect tended to disappear during the very last years of monitoring, when the concentrations became the same in C and T (case of mineral-N; see figure 8 figure 6 for NH4 + ) or when they converged towards non-significant differences (SO4 2-). The compaction impact and its duration can be estimated on the upper soil layers for some elements, but the risk of a confounding effect between compaction and clear-cutting is real, as no sample was collected in the control. It was possible to rule in the situation of convergence of concentrations towards a single value: this was the case for DOC and mineral-N at 10 and 25 cm, and for Al and Fe 2+ at 10 cm depth.

At CA, the clear-cutting effect appeared for Si, SO4 2-, NO3 -, DOC, Mg 2+ and Ca 2+ . The compaction effect was significant for all elements except for Na + , Ca 2+ and Mg 2+ for all levels (table 7). The year-to-year variability was high for Fe 2+ , NH4 + , DOC and Mn 2+ . Significant decreasing trends were observed for numerous elements like Si, Al 3+ , Fe 2+ , Mg 2+ , Ca 2+ , Mn 2+ , Na + , NH4 + , Cl -, and DOC. Finally, a dampening of the initial effect of compaction appeared for Fe 2+ , Mn 2+ , Mg 2+ , Ca 2+ , Al 3+ , DOC, NH4 + , Cl -and NO3 -(upper level) but not for SO4 2-, Si and NO3 -(lower level) (Figure 9 figure 7presents the case of SO4 2-where no dampening effect was observed).

Effect of residence time on PWT geochemistry

Chemistry of the PWT was related to its residence time using the mean concentrations and mean-residence times for the specific levels (10, 20 or 45 cm) and for the period considered (wet season or whole year). Three types of situations were observed at AZ for the relations calculated for the 45 cm level i.e. nil (NO3 -, DOC, NH4 + , Cl -), positive (Fe 2+ , Mn 2+ , Mg 2+ , Al 3+ , Na + , SO4 2-) (the example of Fe 2+ is presented in figure 10 figure 8), or negative (Ca 2+ , Si) relations. At CA, these relations calculated for the 25 and 45 cm levels showed that the concentrations of only three elements were related to MRT (DOC, NH4 + and Fe2 + ). More significant relations were observed for the upper (significant at 5%) than in the deeper (significant at 10%) PWT level. For all other elements no relation appeared between MRT and PWT chemical composition.

Discussion

Soil compaction drastically changed the PWT behaviour

At both sites, compaction led to a decrease in soil porosity. Macro-porosity was the most affected as it has been commonly observed (de Paul and Bailly, 2005). Consequently, for the same rainfall input, the soil moisture tended to increase more in the T than in the C treatment, because the size of the reservoir is smaller, and because during the wetter period of the year the soil bottom is sealed. Vertical transfer of rainfall input was more limited in the T treatment than in the control C thus increasing the number of occurrences (x 4 at AZ and by 2 at CA), the height and mean residence time (x by 5 at AZ and by 2 at CA) of a perched water table in the T treatment. Though the soil physical characteristics (a silty soil laying on a clayey subsoil) at the two experimental sites are similar, PWT dynamics, although showing the same relative trends, were notably different in terms of absolute values.

What environmental characteristics are able to explain the specific behaviour of PWT in each site? Mean total annual rainfall was exactly the same during the study period, so was the decrease in total porosity due to compaction in both sites (from 45 to 50 dm 3 per m 3 ). Soil characteristics like clay content (25 at AZ vs 15 % at CA) and total porosity (530 at AZ vs 500 dm 3 per m 3 at CA), and climatic parameters like rainfall in autumn (+6,5 mm) and in winter (+65 mm) in the CA site, may explain the higher PWT occurrence in the control (C) at CA than in AZ (41 days vs 26). But all these parameters failed to explain why the mean number of days with PWT in the T treatment was lower at CA when compared to AZ (78 vs 136). The soil texture and mineralogy, and more particularly its clay fraction, on the one hand, and the soil Ca-Mg saturation on the other hand, were found to play a major role in the stability of the soil structure in the two sites [START_REF] Bedel | Soil aggregation is a relevant indicator of soil mineral fertility: the case study of soils in the plateau lorrain[END_REF].

We hypothesised a complex and somewhat antagonistic role of the clay fraction, which would interact with the soil richness, higher at AZ (mean soil "base" cation saturation value of 37) than at CA (mean value of 19):

i-The higher clay content at AZ favoured a relatively more stable structure than at CA.

After compaction, which destroyed the structure and increased the soil physical resistance [START_REF] Goutal | Soil compaction due to heavy forest traffic: measurements and simulations using an analytical soil compaction model[END_REF], this higher clay content would play a major role in the loss of soil permeability; the "base cation" rate being not enough high to compensate for the loss of structure,

ii-The occurrence of a swelling beidellite-Fe clay type at CA (dominant in the subsoil, and significant in the soil) [START_REF] Bedel | Soil aggregation is a relevant indicator of soil mineral fertility: the case study of soils in the plateau lorrain[END_REF] was shown to be negative for the soil structural stability at CA, but would be efficient for a rapid cracking of the compacted soil when soil moisture decreased.

Compaction therefore drastically changed the geochemical functioning of the soils, and two parameters had strong consequences on it: i-the level reached by the PWT in the soil, which mean value was multiplied by 5 in winter at AZ and by 2 at CA, because of the soil horizonation, and, ii-its duration, as the mean annual number of days of occurrence was multiplied by 4 at AZ and by 2 at CA, and as its mean residence time (MRT) was multiplied by 4 at AZ and only by 1.1 at CA.

One major effect of compaction was the fact that PWT invaded upper soil layers, which were never or very rarely affected by waterlogging processes. It is very well known that upper soil layers contain most of the organic C, the organic forms of many other elements, and the biological populations and activity. Compaction led to new soil forming-processes, which strongly impacted both mineral (ion exchange, dissolution/precipitation, weathering rate) and biological (organic C, N, P, S mineralization) processes. These two soils, classified as sensitive to physical degradation, shifted towards typical hydromorphic soils, only a few months after the compaction stress. The question of the reversibility of the processes is strongly relevant, but difficult to investigate, just because no control situation is available for the dynamics of changes in the upper soil layers of the compacted treatment. However, whether restoration occurred or not, element redistribution clearly marked soil morphology (unpublished information of the site database) with hydromorphic traits e.g. thin iron pans, Fe/Mn stains or concretions, or drainage losses (Fe, Mn, C and nutrients), bleached areas, and decreased the soil quality for all its functions.

Changing the MRT strongly impacted the processes leading to the geochemistry of the PWT.

When looking at common specific soil layers temporally waterlogged in both the C and T treatments we found three cases:

1-Though trends were observed between C and T, these differences were not statistically significant suggesting that MRT was not long enough to mobilize more than the immediately available reserve of compounds, by ion exchange, by dissolution reactions, or by mixing with tightly bound water, 2-Significant negative relation between MRT and the concentration of a limited amount of very soluble compounds suggesting a simple dilution effect, and, 3-Significant positive relation between elemental concentrations (e.g. Fe, Mn and S) and MRT indicating that the duration of waterlogging changed a physical parameter which led to the development of specific processes affecting these sensitive elements to redox. This PWT duration effect promoted the development of slower processes like dissolution of meta-stable compounds, exchange with more tightly bound water, or even with the subsoil compartment.

Indirect effects of changes in the environment led for example to the mobilization of elements that are not directly sensitive to redox processes like Al of mix-hydroxides. The mobilization of Al and sulphur in turn may mobilize compounds such as available cations or anions after ion-exchange or dissolution, and/or, change biological processes affecting directly C and N compound stability.

At AZ, the rather long MRT (1 day in the C but 4 days in the T) led to the three situations aforementioned while at CA, the shorter MRT (less than half a day in both C and T) led to only types 1 and 3. Paradoxically, it was at CA that the highest Fe 2+ concentrations were observed, suggesting that the redox conditions in solution for iron reduction were reached the most rapidly after waterlogging (figure 11 figure 9). This was not explained by more labile Fe-bearing compounds at CA compared to AZ: the FeDCB: FeTot ratios suggested a higher lability at AZ. From a previous study, we hypothesized that the massive structure of the acidic CA soil when wet [START_REF] Bedel | Soil aggregation is a relevant indicator of soil mineral fertility: the case study of soils in the plateau lorrain[END_REF], would rapidly lead to anoxic conditions.

PWT time changes used as an indicator of the dynamics of soil restoration after compaction

In the present experimental designs, changes occurring after compaction integrated several effects which had consequences on both physical and chemical characteristics of PWT e.g. i-

the clear-cutting effect, ii-the changes in vegetation including both understory and oak developing plantation, iii-the year-to-year variability of the climate, and finally iii-the hypothetical restoration of soil porosity.

The change in soil porosity and its consequences on PWT were easy to characterize. The deconvolution on a relatively short time series of the global signals to identify the effects of individual parameters on porosity dynamics, was far more complex. It is known that clearcutting and vegetation development have opposing effects on the soil water regime and soil water chemistry: the former usually increases soil moisture and elemental concentrations in soil solutions, while the latter does the reverse (Dyck et al., 1994). Year-to-year changes in the rainfall amount were able to disturb these general effects, especially when a systematic gradient occurred.

At AZ no changes were recorded in the rain amount along the study period. The mid-term trend was a reduction of the PWT in the control (attested by a significant decrease in mean level, duration in days, duration of individual events) but to an increase of the PWT in the compacted treatment (significant at 10% for the mean level and 5% for the duration in days).

At CA, where the winter-autumn rainfall significantly increased during the period of monitoring, the trend was close to a decrease of the difference of PWT physical characteristics between C (significant mean level increase in winter, and a individual event duration decrease) and T (significant decrease of the maximum level and of the duration of individual events).

Physical traits of the PWT led to the conclusion that no restoration of the soil porosity occurred 7 years after compaction at AZ, but that some restoration occurred at CA.

We hypothesize that the mean level of PWT, which integrates all the PWT episodes, is a more robust indicator of soil restoration than the maximum level, which could be the result of few events.

The aforementioned confusing effects and the fact that at AZ no significant sampling was possible in the upper soil layers, made it more difficult to use the PWT geochemistry traits as indicators for soil restoration after compaction. Similarly to clear-cutting effects for example, some compaction effects could be mitigated and/or delayed in the deep soil layers. The vertical distribution in the soil profile of numerous elements in the T treatment, positively (DOC, NH4 + , NO3 -, Fe 2+ , Mn 2+ , K + , Al 3+ ) or negatively (Mg 2+ , Si, SO4 2-) correlated with soil depth, consolidated this point.

Taking all these parameters into account led to the conclusion that indexes of soil restoration using PWT geochemistry showed very limited changes in AZ where only mineral-N indicated some restoration. At 45 cm depth, sensitive element like Fe2 + or Mn 2+ did not show any changes with time, excepted the decrease in the strong initial effect of compaction. The behaviour Na + was peculiar and seemed to indicate a degradation of the situation! There was probably a more pronounced restoration rate in the upper soil layers, but we already presented the difficulty to estimate it.

On the contrary, at CA, all elements but Si and SO4 2-, for both 20 and 45 cm levels and NO3 - at 45 cm, showed a significant dampening of the initial effect of compaction. As previously explained, we hypothesized that clay content and nature, through the soil structure stability was a major parameter controlling the physical characteristics of the PWT, and indirectly its geochemistry.

The PWT physical and geochemical indicators were in rather good agreement, and both suggest the restoration of soil porosity in the specific situation of each experimental site. This was clearer at CA in a situation where the PWT flooded the medium and lower soil layers of both the C and T treatments, than at AZ, where only the lower layer could be investigated with both physical and chemical indicators, limiting the relevance of the information collected from the geochemical investigation.

Our experience leads to the conclusion that physical traits of the PWT, far easier to monitor than chemical ones, could be investigated alone for a satisfactory diagnosis of the restoration of soil porosity. Nevertheless, to characterize the short and long terms effects on all the components of soil fertility, the geochemical traits add strongly relevant information.

Consequences for forest management?

Using the PWT as an indicator of forest soil recovery after application of a limited compaction stress showed its relevance and its ability to sort between two relatively similar situations inside an identical soil type.

We hypothesized that the richer soil would recover more rapidly than the poorer one, because recovery should be related to soil quality, including physical (better structure stability), chemical (richness in 'base cations') and biological (flora indication, earthworms activity).

This hypothesis was not verified.

At AZ, because limited or no soil recovery occurred during the 7 years after compaction, and because the complete recovery would not happen suddenly, the probability that an additional mechanized silviculture operation would take place before the complete restoration of the first disturbance is very high (in France rotation lengths are about 8 to 10 years for coniferous and 12 to 15 years for broadleaved species). The effects of a second compaction event would be more dramatic and virtually impossible to predict. In such conditions, mechanized forest operations must be strictly regulated to ensure the sustainable management of the forest: extraction tracks are recommended. This practice is already applied by forest managers in State-owned forests in France [START_REF] Pischedda | Pour une exploitation forestière respectueuse des sols et de la forêt[END_REF] but its evaluation is still on-going because the trafficability of the tracks must be maintained. Concerning the consequences of the disturbance, an unknown parameter is the mechanical behaviour of forest soils that have never been impacted by strong and repeated mechanical constraints: their pre-consolidation point (threshold pressure separating an elastic and recoverable soil deformation from a plastic and non recoverable soil deformation) should change, modifying the reversibility of the compaction (Dias Junior and Pierce, 1995).

The consequences on vegetation appeared to be site-dependent. On the short-term time scale, tree mortality increased (strongly at AZ and less at CA) and tree growth was reduced in T treatments compared to C (at both sites) [START_REF] Ranger | Effet de la mécanisation des travaux sylvicoles sur la qualité des sols forestiers : dynamique de la restauration naturelle ou assistée de leurs propriétés physiques[END_REF]. In both cases, cleaning operations for eliminating the strong competition of understory vegetation in the compacted plots increased the costs for ensuring the development of young oak stands. Compaction directly affects the tree root system by increasing the soil bulk density and the soil physical resistance (Goutal et al., 2017). The resulting hydromorphy, drastically changing the functioning of the soil, represented a strong constraint for vegetation in terms of root respiration, water and nutrient uptake. The limited but real soil restoration at the low fertility site of CA was fortunate: [START_REF] Bedel | Unexpected calcium sources in deep soil layers in low-fertility forest soils identified by strontium isotopes (Lorraine plateau, eastern France)[END_REF] demonstrated that trees mobilised the sub-soil water and nutrient reserves during the dry periods. Nevertheless, it is necessary to demonstrate that the restoration of the deepest layers of the soil is real by investigating the soil solid phase (volume mass, physical resistance, morphology…). Any degradation of soil quality represents a real constraint for the durability of such ecosystems in the long term.

Conclusions

1-The results demonstrated that the limited controlled compaction of two sensitive silty soils belonging to the same ruptic neo-luvisols type, immediately and drastically changed the soil water regime, as shown by the physical and geochemical characteristics of the perched water table. Both soils shifted towards a hydromorphic type attested by an increase in the number of occurrences of a PWT and its duration, which flooded the soil upper layers and lead to characteristic mobility of Fe, Mn and S. Stability of organic C and N compounds was also changed: our first hypothesis is validated.

2-Even within the same soil type, a polycyclic soil composed of a 50 cm silty stratum laying on a clayey subsoil, the PWT characteristics notably varied. The mean residence time of the PWT was shown to be a major driver of its geochemistry, but with strong interaction with soil characteristics. A previous study made on both sites [START_REF] Bedel | Soil aggregation is a relevant indicator of soil mineral fertility: the case study of soils in the plateau lorrain[END_REF] suggested that soil clay content and clay mineralogy controlled the PWT behaviour through aggregation.

3-Seven years after the application of the constraint were not enough to observed significant recovery, judged from the PWT, in the richer soil of AZ, but led to partial recovery of the poorer one at CA: our second hypothesis is not validated.

4-Short-term negative consequences on soil and vegetation were easily observable.

Long-term consequences were more complex to simulate, most especially in the richer soil of AZ where little recovery occurred after seven years. This means that compaction durably impacted the soils and that the probability of a new compaction before the complete recovery of the first disturbance, has to be considered. Contrarily to agriculture soils that have been subject to compaction for years, forest soils have not, and their reaction to successive disturbances needs to be reliably investigated, particularly for changes in their intrinsic mechanical characteristics.

  3.3.2 PCA for identifying the main effects of compaction PCA was carried out only for PWT levels where treatments can be compared e.g. 45 cm depth level at AZ, and 25 and 45 cm depth at CA.At each site, the three first axis explained more than 40 % of the total variance. The compaction effect was strong on PWT geochemistry, with explanatory variables mostly significantly different between the C and T treatments (in perfect agreement with the Anova results in tables 6 and 7). The spreading out of individual observations did not alter the significant difference in the position of the centroids of C and T populations in the plane of the axis 1&2 (figure1Aand 1B; supplementary material section).

Figure 1 :Figure 2 :

 12 Figure 1: Design for PWT monitoring, physical characteristics (A), and chemistry (B)

Figure 3 :Figure 4 :Figure 5 :

 345 Figure 3: Dynamics of the duration of occurrence of the perched water table in winter at both

Figure 6 :

 6 Figure 6: Recovery after compacting; example given by the dynamics of N-NH4 +

Figure 7 :Figure 8 :Figure 9 :

 789 Figure 7: Non recovery after compaction; example given by the dynamics of SO4 2+

  Figure1

  3.2.2 Duration of the PWT: time changes during the 7 years of observationIn the control C treatment, a PWT occurred during some events at both sites (table 4): on average over the 7 years of monitoring, the PWT lasted 26 days per year in AZ and 41 days in CA. The PWT occurred mainly during the winter period, e.g. 13 days in AZ and 23 days in CA. The compaction strongly increased the frequency of occurrence of the PWT at both sites,

at AZ in particular with 136 days per year (comparatively at CA, 78 days per year). The increase in frequency mainly occurred during the winter period e.g. + 45 days in AZ and + 12

Table 1 :

 1 Brussaard, L., and van Faassen, H.G., 1994. Effects of compaction on soil biota and soil biological processes. In Stone B.D. and van Ouverkerk C. (eds) Soil compaction and crop Main soil characteristics for both sites

	production. Chapter 10: 215-235
	Carignan, J., Hild, P., Mevelle, G., Morel, J., Yeghicheyan, D. 2001. Routine analyses of
	trace elements in geological samples using flow injection and low pressure on-line liquid
	chromatography coupled to ICP-MS: A study of geochemical reference materials BR, DR-N,
	UB-N, AN-G and GH. Geostandards Newsletter, Vol. 25 No. 2-3 : 187-198
	Centre D'expertise En Analyse Environnementale Du Québec, 2010. Détermination des
	sulfures : méthode colorimétrique avec le chlorure ferrique et l'oxalate du diméthyl-p-
	phénylène diamine, MA. 300 -S 1.1, Rév. 4, Ministère du Développement durable, de
	l'Environnement et des Parcs du Québec, 18 p.
	Ciesielski, H., Sterckeman, T., Santerne, M., Willery, J.P., 1997. Determination of cation
	exchange capacity and exchangeable cations in soils by means of cobalt hexamine
	trichloride. Effects of experimental conditions, 17. EDP Sciences, Les Ulis, France.
	Core Team R, 2013. R: a language and environment for statistical computing. Austria,
	Vienna
	Dias Junior, M.S. and Pierce, F.J., 1995. A simple procedure for estimating pre-consolidation
	pressure from soil compression curves. Soil Technology, 8: 139-151
	Doran, J.W. and Power, J.F., 1983.The effets of tillage on the nitrogen cycle in corn and
	wheat. In Lowrance, R.R., Told, R.L., Asmussen, L.E., Leonard, R.A. (eds) Nutrient cycling
	in agricultural ecosystems. Univ. Georgia Athens, GA, USA Special pub 23: 441-455
	Dyck W.J., Cole, D.W., Comerford, N.B., 1994. Impacts of forest harvesting on long-term
	site productivity. Chapamn and Hall London.
	Fortune, W.B. Melon, M.G., 1938. Determination of ion whith o-phénantroline, a
	spectrophotometric study. Ind. Eng. Chem. Anal. : 10, P.60.

Table 2 :

 2 Changes in soil bulk density and porosity due to compaction at both sites

Table 3 :

 3 Mean seasonal level (A) and thickness (B) of the Perched Water Table at the two sites

Table 4 :

 4 Mean duration of periods with or without perched water table according to seasons at both sites

Table 5 :

 5 Impact of treatments (control C vs compacted T) on the mean annual number and duration of the perched water table events, for fixed levels, at the two sites

Table 6 :

 6 Mean chemical characteristics of the perched water table at Azerailles during the observation period (mean values for concentration, results of the Anova test when possible).

	Table 7: Mean chemical characteristics of the perched water table at Clermont-en-Argonne
	during the observation period (mean values for concentration, results of the Anova test when
	possible).

  45/50 cm) 915

	site	Depth	treatment T	C org soil depth (cm) N org 15-20	particle size distibution (g.kg -1 ) mean bulk density density of solid 1.50 2.62	CEC total porosity Ca exch 42.8	Ca+Mg+K+Na saturation macroporosity 7.5	Fe DCB	DCB Al	CEC clays		Total elements %
			pHH2O pHKCl C T		0-10 20-25		0.97 1.51			2.62 2.64			62.8 42.8		19.7
		cm		C T			g kg -1 10-20 25-30	Clay	fine silt 1.23 1.50	coarse silt	fine sands 2.62 coarse sands 2.64	cmol+ kg -1 53.2 45.1	% 25.4	%	%	cmolc+ kg -1	Ca	Mg	Fe	Al
		0-10	4.8	C T	3.9	26.7	1.8 20-30 30-40	222	356 1.29 1.51	201	58	2.64 2.65	165	5.7	51.0 42.9	2.2	63 24.0 11.0	1.8	0.3	24.0	0.13 0.27 2.49	4.00
		10-20	4.6	C T	3.7	15.0	1.0 33-43 40-50	216	363 1.34 1.50	208	59	2.66 2.66	154	4.3	49.5 43.7	0.45	24 16.3	1.9	0.3	22.0	0.14	0.27	2.57	4.03
		20-30	4.6	C T	3.7	10.8	0.8 50-60 50-60	235	363 1.34 1.51	204	59	2.69 2.66	140	4.5	50.2 43.3	0.46	24	1.5	0.3	18.0	0.13 0.30 2.60	4.28
	Azerailles Azerailles 30-45 C control; T compacted	4.6	T	3.7	5.5	0-5	0.5	323	328 1.17	173	47	2.62	129	7.0	55.4	1.23	29 6,3	2.2	0.4	20.0	0.13 0.44 3.27	5.34
	(AZ)	45-60	4.7	T	3.7	3.6	0.4 06-11	455	289 1.31	139	33	2.62	84	12.0	50.1	3.38	43	2.7	0.5	25.0	0.15 0.66 4.21	6.94
		60-80	4.9	T	3.6	2.0	0.3 12-17	501	273 1.36	137	30	2.62	58	15.3	48.2	4.07	47 6,3	2.3	0.5	29.0	0.16 0.64 4.08	7.28
		80-100	5.2	T	3.5	1.5	0.3 18-23	590	233 1.44	93	26	2.62	59	14.2	45.1	5.95	70	2.4	0.4	27.0	0.16 0.77 4.38	8.14
				T			25-33		1.41			2.64			46.7
		> 100	5.1		3.4	1.5		0.3	631	240	77	17		35	17.9		5.56	54	2.5	0.4	26.0	0.16 0.88 4.47	8.43
				T			35-45		1.43			2.66			46.4		6,3
		0-10	4.4		3.5	26.1		1.4	128	357	365	140		10	4.3		0.65	29	0.6	0.2	31.0	0.17 0.14 1.11	2.63
				T			50-60		1.38			2.69			48.6
		10-20	4.5		3.8	9.6		0.5	128	357	362	141		13	3.4		0.19	16	0.6	0.2	23.0	0.16 0.16 1.19	2.84
				C			0-10			1.12			2.62			57.4		16.0
		20-30	4.5		3.8	4.5		0.3	155	345	348	134		18	4.5		0.20	12	0.7	0.2	24.0	0.16 0.21 1.49	3.26
				C			10-20		1.29			2.62			50.8		30.3
		30-45	4.6		3.7	2.6		0.3	212	328	321	124		15	7.3		0.39	12	0.8	0.3	27.0	0.14 0.30 1.94	3.91
	Clermont en			C			20-30		1.36			2.64			48.3
	Argonne (CA)	45-60	4.8	C	3.5	10.6	0.3 30-40	285	305 1.42	284	113	2.62	13	12.7	46.6	1.73	26 26.7	1.0	0.3	35.0	0.15 0.42 2.60	4.65
	60-75 Clermont-en-Argonne	5.0	C	3.4	13.4	0.3 40-50	330	277 1.44	251	124	2.62	18	16.7	45.7	4.00	42	1.0	0.3	41.0	0.18 0.48 2.98	4.94
		75-90	5.0	C	3.4	1.4	0.3 50-60	336	297 1.46	241	120	2.66	6	16.9	45.0	5.38	53	1.0	0.3	44.0	0.21 0.48 2.99	4.88
		90-110	5.1	T	3.3	1.2	0-5	0.2	334	281 1.23	287	89	2.62	10	17.8	53.1	6.30	55 11.2	1.0	0.3	46.0	0.26 0.48 2.98	4.83
		> 110	5.1	T	3.3	1.2	0.2 5-10	329	264 1.38	246	137	2.62	24	19.5	47.3	7.77	60	1.0	0.2	51.0	0.27 0.47 2.90	4.78
	all data refered to soil fine earth dried at 105°C except CECclays refering to the clay fraction itself T 10-15 1.44 2.62 44.9
	Table 1

Table 2

 2

	AZERAILLES		control C			compacted T		control C	compacted T	∆ (T-C)
			PWT level			PWT level		PWT thickness	PWT thickness	PWT thickness
							cm
		base	maxi	mean	base	maxi	mean	mean	maxi	mean	maxi	mean	maxi
	Spring	-44.0	-34.0	-42.5	-43.6	-15.2	-36.2	1.5	9.9	7.4	28.4	5.9	18.5
	Summer	-44.0	-39.2	-43.3	-43.9	-21.8	-40.2	0.7	4.7	3.7	22.1	3.0	17.4
	Autumn	-44.0	-33.4	-42.8	-43.9	-12.4	-36.0	1.2	10.6	7.9	31.6	6.7	21.0
	Winter	-44.0	-25.2	-41.8	-43.0	-10.0	-30.4	2.2	18.8	12.6	33.1	10.5	14.2
	CLERMONT
	en ARGONNE		control C			compacted T		control C	compacted T	∆ (T-C)
			PWT level			PWT level		PWT thickness	PWT thickness	PWT thickness
							cm
		base	maxi	mean	base	maxi	mean	mean	maxi	mean	maxi	mean	maxi
	Spring	-44.5	-27.8	-41.8	-44.6	-15.4	-39.2	1.3	12.4	2.8	23.9	1.5	11.5
	Summer	-44.5	-37.2	-43.8	-44.6	-27.2	-43.3	0.7	7.3	1.4	17.4	0.6	10.1
	Autumn	-44.5	-27.4	-42.1	-44.6	-12.6	-39.1	2.4	17.1	5.6	32.0	3.2	15.0
	Winter	-44.5	-18.9	-39.6	-44.6	-6.4	-35.1	5.0	25.6	9.5	38.2	4.5	12.7

base, maximum and mean level of the PWT represents the level integrated for the whole season relatively to the soil surface (level 0)

Table 3

 3

	period				AZERAILLES		CLERMONT en ARGONNE
		Perched Water Table	C	T	∆ (T-C)	statistics	C	T	∆ (T-C) statistics
	Spring	with	5	28	23		5	16	11
	Summer	with	1	13	12		2	6	4
	Autumn	with	7	37	30		11	21	10
	Winter	with	13	58	45		23	35	12
	year (mean
	value)	with	26	136	110	S	41	78	37	S
	year (mean
	value)	without	339 229	-110	S	324	287	-37	S

S = significant, here for the whole experiment and for individual blocks (except for the block II at CA) Unit = number of days

Table 4

 4

			control C			compacted T		T:C ratio	T:C ratio
	level from the PWT floor	mean number of events	mean duration of events (hours)	mean number of events	mean duration of events (hours)	number of events duration of events
		AZ	CA	AZ	CA	AZ	CA	AZ	CA	AZ	CA	AZ	CA
	+ 5 cm	12	12	38	7	21	23	135	8	1.8	1.9	3.6	1.1
	+ 10 cm	8	9	31	7	19	23	118	7	2.4	2.6	3.8	1.0
	+ 15 cm	5	8	25	6	20	20	98	6	4.0	2.5	3.9	1.0
	+ 20 cm	3	7	21	5	20	18	71	6	6.7	2.6	3.4	1.2
	AZ: Azerailles
	CA: Clermont-en-Argonne

Table 5

 5

	traitement		depth	sampling points	sample size		Fe 2+ F -Cl -	NO3 -SO4 2-H2PO4 -	S	P	Fe	Si Mn Mg Al Ca Na	K	N-NH4 + TC TN Norg H +
																	mg L -1
	Control		15 cm	6	0
	compacted		10 cm	6	82	mean 0.17	0.02	2.09	0.32	6.40	0.07	2.27	0.08	1.10	4.37	0.87	0.66	1.13	2.79	1.21	2.36	0.12	20.97 1.35	1.16	0.004
						SD	0.16	0.01	0.49	0.29	1.49	0.08	0.7	0.07	0.62	0.56	0.86	0.16	0.71	0.68	0.25	1.04	0.14	10.88 0.76	0.76	0.001
	treatment effect t	(1)
	year effect y	(1)
	interaction txy	(1)
	Control		30 cm	6	1		0.04	0.00	1.09	2.66	4.58	0.00	1.64	0.04	0.86	5.79	0.14	0.29	1.07	1.47	0.88	1.12	0.29	10.45 0.96	0.07	0.01
	compacted		25 cm	6	175	mean 0.11	0.03	1.74	0.43	8.05	0.02	2.82	0.04	0.76	4.46	1.69	0.54	0.74	2.24	1.30	1.07	0.15	13.17 0.77	0.51	0.009
						SD	0.05	0.01	0.69	0.40	2.55	0.02	0.85	0.02	0.36	0.46	1.20	0.09	0.36	0.48	0.35	0.26	0.10	3.52	0.29	0.27	0.003
	treatment effect t	(1)
	year effect y	(1)
	interaction txy	(1)
	Control		50 cm	6	181	mean 0.02	0.06	2.23	2.26	9.84	0.01	3.24	0.01	0.29	5.72	0.12	0.86	0.32	2.83	1.47	0.48	0.24	8.45	1.13	0.35	0.009
						SD	0.01	0.01	0.88	1.95	0.96	0.01	0.43	0.01	0.05	0.48	0.08	0.16	0.08	0.35	0.14	0.06	0.18	3.35	0.63	0.39	0.002
	compacted		45 cm	6	295	mean 0.07	0.09	2.06	2.56	12.98	0.01	4.15	0.02	0.48	5.10	1.44	1.11	0.44	2.50	2.17	0.57	0.23	11.07 0.99	0.34	0.055
						SD	0.08	0.03	1.01	3.93	1.93	0.01	0.60	0.01	0.18	0.34	1.05	0.25	0.16	0.59	0.18	0.08	0.19	2.72	0.93	0.27	0.129
	treatment effect t						***	***	***		***		***	***		***	***	***		***	***		***	*	***	***
	year effect y							***	***	***	***	***	***	***	***		*	***	*	***	***		***	***	***	*
	interaction txy								***	***	**										***				***	***
	Control	(2)	70 cm	3	158	mean 0,01	0,04	7,49	0,66	10,63	0,02	3,58	0,01	0,16	7,33	0,04	1,35	0,16	3,95	3,15	0,38	0,33	7,06	0,76	0,30	0.008

Table 7 B

 7

-Piezometer for water sampling A-Piezometer for measuring water level Diver device for measuring the water table pressure

Acknowledgements

Financial supports were provided by i-the DST project of the French Ministry of Ecology and Sustainable Development (MEDD -Gessol), ii-the Ministry of Agriculture and Fishery (MAP), iii-the National Research Agency (ANR) through DST project (ANR-05-PADD-013), LABEX Arbre, Investissements d'Avenir Program (ANR-11-LABX-0002-01) and infrastructure ANAEE-S (ANR-11-INBS-0001), iv-Europe through Feder (12000266), v-the French National Office of Forestry (O.N.F.), vi-the Region Lorraine, and vii-the GIP Ecofor (Allenvi-Soere). We thank Dominique Gelhaye and Yves Lefevre for their work at the initial phase of the experiment.

Site effect on PWT chemistry shown by PCA