Lorène Siegwart

Isabelle Bertrand
email: isabelle.bertrand@inrae.fr

Olivier Roupsard

Maxime Duthoit

Christophe Jourdan

Siegwart Lorène

Bertrand Isabelle

Roupsard Olivier

Duthoit Maxime

Jourdan Christophe

Root litter decomposition in a sub-Sahelian agroforestry parkland dominated by Faidherbia albida

Keywords: Soil organic carbon, soil nutrients, root litter quality, soil depth, Vigna unguiculata, Pennisetum glaucum

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

Introduction

In the current context of global warming, soil carbon (C) sequestration can contribute to mitigating the greenhouse effect (Nair et al. 2009a;Nair et al. 2009b;[START_REF] Chenu | Increasing organic stocks in agricultural soils: Knowledge gaps and potential innovations[END_REF]). In the tropics, C sequestration can more specifically contribute to the improvement of food security and to climate change adaptation [START_REF] Paustian | Climate-smart soils[END_REF]. Tropical soils are characterized by lower nutrient contents [START_REF] Feller | Physical control of soil organic matter dynamics in the tropics[END_REF] and more rapid C turnover than those in temperate systems [START_REF] Six | Soil organic matter, biota and aggregation in temperate and tropical soils -Effects of no-tillage[END_REF]. A recent synthesis based on 48 studies performed on tropical soils from 13 countries demonstrated that the main determinants of soil organic carbon (SOC) accumulation were C inputs, duration of the experiments and management practices [START_REF] Fujisaki | Soil carbon stock changes in tropical croplands are mainly driven by carbon inputs: A synthesis[END_REF]). However, this synthesis did not consider agroforestry practices due to the lack of references, although agroforestry is assumed to enhance C storage in soils [START_REF] Smith | Climate Change 2014 Mitigation of Climate Change: Working Group III Contribution to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change[END_REF]. Increasing soil C sequestration is a current challenge in highly weathered tropical soils with low C contents, and agroforestry practices may contribute to overcoming this challenge.

In agroforestry systems, the diversity of the plant species and new ecological niches for biodiversity [START_REF] Leaky | Definition of agroforestry revisited[END_REF] lead to an enrichment of aerial, root and microbial biomasses (Nair et al. 2009b;[START_REF] Kuzyakov | Land-use intensification and agroforestry in the Kenyan highland: Impacts on soil microbial community composition and functional capacity[END_REF]) with a tradeoff between soil fertility improvement and competition for growth resources [START_REF] Rao | Biophysical interactions in tropical agroforestry systems[END_REF]. C inputs in agroforestry systems are mostly related to the decomposition of aboveground biomass (tree litterfall and crop residues) and belowground biomass originating from tree and crop root turnover and/or mortality and rhizodeposition [START_REF] Kuzyakov | Land-use intensification and agroforestry in the Kenyan highland: Impacts on soil microbial community composition and functional capacity[END_REF]. [START_REF] Cardinael | Stockage de carbone et dynamique des matières organiques des sols en agroforesterie sous climat méditerranéen et tempéré[END_REF] estimated that tree and crop fine roots each contribute 30% to organic matter input in agroforestry systems. Fine roots are generally more recalcitrant than aerial aboveground biomass to soil microbial decomposition [START_REF] Rasse | Is soil carbon mostly root carbon? Mechanisms for a specific stabilisation[END_REF][START_REF] Bertrand | Can the Biochemical Features and Histology of Wheat Residues Explain their Decomposition in Soil?[END_REF][START_REF] Freschet | Linking litter decomposition of above-and below-ground organs to plant-soil feedbacks worldwide[END_REF], and they have the potential to increase soil C stocks. While several studies have demonstrated the chemical characteristics responsible for slow root decomposition rates [START_REF] Machinet | Decomposition in soil and chemical changes of maize roots with genetic variations affecting cell wall quality[END_REF][START_REF] Cotrufo | The Microbial Efficiency-Matrix Stabilization (MEMS) framework integrates plant litter decomposition with soil organic matter stabilization: do labile plant inputs form stable soil organic matter?[END_REF][START_REF] Prieto | Root functional parameters predict fine root decomposability at the community level[END_REF], the impact of soil depth has been less studied, although roots occur at different depths in the soil profile. This is particularly true for agroforestry systems where tree, herbaceous and crop roots colonize different soil layers, especially at depth [START_REF] Cardinael | Competition with winter crops induces deeper rooting of walnut trees in a Mediterranean alley cropping agroforestry system[END_REF][START_REF] Germon | Unexpected phenology and lifespan of shallow and deep fine roots of walnut trees grown in a silvoarable Mediterranean agroforestry system[END_REF][START_REF] Battie-Laclau | Role of trees and herbaceous vegetation beneath trees in maintaining arbuscular mycorrhizal communities in temperate alley cropping systems[END_REF].

Root litter decomposition depends not only on litter quality but also on pedoclimatic conditions [START_REF] Makkonen | Highly consistent effects of plant litter identity and functional traits on decomposition across a latitudinal gradient[END_REF]) and soil microbial communities and activity [START_REF] Herman | Interactions between an arbuscular mycorrhizal fungus and a soil microbial community mediating litter decomposition[END_REF]. These biotic and abiotic soil characteristics are strongly impacted by the introduction of trees in arable lands. The introduction of trees causes spatial heterogeneity in soil temperature and humidity [START_REF] Monteith | Microclimatic interactions in agroforestry systems[END_REF][START_REF] Rao | Biophysical interactions in tropical agroforestry systems[END_REF][START_REF] Lin | Agroforestry management as an adaptive strategy against potential microclimate extremes in coffee agriculture[END_REF] as well as soil microbial biomass abundance and composition [START_REF] Chander | Soil organic matter, microbial biomass and enzyme activities in a tropical agroforestry system[END_REF][START_REF] Liu | Drivers of soil bacterial community structure and diversity in tropical agroforestry systems[END_REF], Guillot et al. 2021) and soil C stocks [START_REF] Cardinael | Stockage de carbone et dynamique des matières organiques des sols en agroforesterie sous climat méditerranéen et tempéré[END_REF]. In a recent study performed in the same area as our study site, [START_REF] Roupsard | How far does the tree affect the crop in agroforestry? New spatial analysis methods in a Faidherbia parkland[END_REF] demonstrated that the whole pearl millet plant dry mass was 2.2 times higher under the Faidherbia tree crown than far from the tree. As a consequence, biomass inputs may be more important near trees, which could induce a modification of the soil chemical and physical properties. While the impact of trees on crop yield, climatic conditions and soil C stocks at a local scale was previously investigated in shallow soil horizons [START_REF] Oelbermann | Carbon sequestration in tropical and temperate agroforestry systems: a review with examples from Costa Rica and southern Canada[END_REF][START_REF] Oelbermann | Carbon and nitrogen in a temperate agroforestry system: Using stable isotopes as a tool to understand soil dynamics[END_REF][START_REF] Lin | Agroforestry management as an adaptive strategy against potential microclimate extremes in coffee agriculture[END_REF][START_REF] Roupsard | How far does the tree affect the crop in agroforestry? New spatial analysis methods in a Faidherbia parkland[END_REF], to our knowledge, no studies have investigated the impact of trees on deep soil characteristics or on tree and crop root decomposition.

Soil properties may vary with soil depth given that the total organic C content and microbial biomass decrease with depth (Hicks [START_REF] Pries | Root litter decomposition slows with soil depth[END_REF]. Soil temperature and moisture tend to be less subject to variations in deeper soil layers than in topsoil. Hicks [START_REF] Pries | Root litter decomposition slows with soil depth[END_REF] showed that slower root decomposition could be responsible for higher stable C stocks at soil depth. A recent meta-analysis by Balesdent et al. (2018) performed on 112 grassland, forest and cropland sites demonstrated that the subsoil (30-100 cm depth) stored 47% of the C in the first metre of the soil profile. This deep C storage despite a lower litter input is related to root mortality and rhizodeposition and to the reduced decomposition rates at depth (Guenet et al. 2013). Data are lacking on root litter dynamics and C stocks in deep soil horizons, especially for tropical areas.

The aim of our study was thus to measure soil characteristics, including soil C stocks and the root decomposition rate, according to soil depth in a sub-Sahelian agroforestry park dominated by Faidherbia albida trees and to account for the tree effect.

We hypothesized that (i) soil fertility, indicated by the C and nutrient contents, would be higher in the topsoil than in deeper soil layers and under trees than far from the trees due to the presence of leguminous tree species;(ii) the root litter decomposition rate would mainly depend on the plant species (i.e., root tissue quality), roots would decompose faster under trees and (iii) root litter would decompose more slowly in deep soil layers than in topsoil because of the stable pedoclimatic conditions.

Materials and methods

Study site

The "Faidherbia-Flux" collaborative observatory for greenhouse gas balance and ecosystem services (https://lped.info/wikiObsSN/?Faidherbia-Flux) is located in the natural agro-silvo-pastoral parkland of Sob (14°29'45N, 16°27'13W), 135 km East of Dakar, on the Bambey-Fatick transect, West Senegal, [START_REF] Roupsard | How far does the tree affect the crop in agroforestry? New spatial analysis methods in a Faidherbia parkland[END_REF]). The climate is sub-Sahelian, with an average annual rainfall of 500 mm [START_REF] Lalou | Does climate opportunity facilitate smallholder farmers' adaptive capacity in the Sahel?[END_REF]) and an average temperature of 29.6°C [START_REF] Ndiaye | Variations climatiques et mortalité attribuée au paludisme dans zone de Niakhar, Sénégal, de 1984 à 1996[END_REF]. The soil temperature (°C) was measured with thermocouples buried at 0, 2, 5, 15, 30, 60, 100, 150 and 200 cm. The soil volumetric water content (m 3 H2O m 3 soil) was measured with TDR (time domain reflectometry) moisture sensors buried at 15, 30, 50, 75, 100, 125, 150, 175 and 200 cm in an open area of the plot (far from the trees and close to the weather station). The rainfall was measured on site with an automatic tipping bucket (Texas Electronics, model TE525 mm). Data were recorded every 30 minutes over the entire study period. The average daily temperature and soil moisture and sum of rainfall were calculated (Fig. 1). The soil is a sandy tropical ferralitic soil [START_REF] Maignien | Notice explicative : carte pédologique du Sénégal au 1/1[END_REF]; it is classified as an Arenosol (IUSS Working group WRB 2014). The water table is located at approximately 5-6 m depending on the season. The studied agroforestry system was composed mainly of Faidherbia albida trees (85% occurrence), with a density of 6.8 trees/ha, which represents an average canopy cover of 5.14% measured over an area of 15 ha (Roupsard et al. 2020;[START_REF] Rahimi | Modelling Gas Exchange and Biomass Production in West African Sahelian and Sudanian Ecological Zones[END_REF]. Faidherbia trees were associated with groundnut (Arachis hypogaea) or pearl millet (Pennisetum glaucum) according to annual rotations. In June 2018, pearl millet was manually sown in the studied plot at a distance of 80 cm between each sowing pocket. Cowpea (Vigna unguiculata) was sown at the same time in a neighbouring plot with the same soil type and climatic conditions. There was no amendment applied to these plots, and harvesting was conducted in October 2018.

Above-and belowground biomass sampling

The biomass sampling campaign was conducted in October 2018, immediately before the pearl millet crop harvest.

According to the large volume of soil to excavate and sieve (each pit was 8 m 3 ), only 2 pits could be prepared, one under and one far from a tree. We sampled 3 walls in each pit, thereby assuming independence of the results. The pit under the tree was chosen under a Faidherbia individual representative of the tree population [START_REF] Diatta | Estimation du stock et du stockage annuel de carbone dans la biomasse aérienne de Faidherbia albida du parc agroforestier de Sob (Observatoire de Niakhar, Sénégal) : approches par inventaires et dendrochronologie[END_REF], with a height of 13.5 m and a circumference at breast height of 2.84 m.

The aboveground parts of pearl millet were collected in two subplots, each measuring 2 m × 2 m. One subplot was located under the selected Faidherbia tree crown (1.5 m from the trunk, crown radius of 5 m), whereas the second subplot was located far from any tree and at a minimum distance of 30 m from the first subplot. The subplots used for biomass quantification were at the same location as the pits. Each subplot included four pearl millet pockets.

The vegetative biomass was split into ears, stems, leaves and stumps. All samples were oven-dried for 48 hours at 65°C before weighing.

After the aboveground biomass was sampled, two pits of 2 m × 2 m × 2 m were dug at the same locations. For each pit, roots were sorted by manually sieving the soil at 2 mm from a total soil volume of 8 m 3 and split according to the plant species (pearl millet and Faidherbia tree) and the corresponding soil layer (0 -40 cm, 40 -100 cm, 100 -150 cm and 150 -200 cm). Given the small quantity of pearl millet roots found at great depth, the root biomasses of pearl millet in soil layers 100 -150 and 150 -200 cm were summed for each profile. Then, Faidherbia roots were sorted manually, and their diameter (D) was measured with a digital calliper to separate fine roots (D < 2 mm) from medium roots (10 mm > D ≥ 2 mm). All samples were washed on a 0.5 mm sieve and oven-dried for 48 hours at 65°C before weighing. The belowground biomass was assessed for 2 subplots × 2 plant species × 4 soil layers (× 2 root diameter categories for Faidherbia) after correction for the ash content. To this end, a subsample of 1 g of the washed root sample was burned at 500°C for 4 hours to remove organic matter, and the remaining mineral ash was weighed and deducted from the dry root mass. Supplementary roots were collected between 0 and 40 cm depth in the neighbouring plot planted with cowpea and prepared as described above for millet and Faidherbia roots.

Litterbag experiment

We performed a 464-day root litter decomposition experiment with fine roots of Faidherbia tree, cowpea and pearl millet. A subsample of 1.5 g root litter was inserted in 10 × 20 cm nylon mesh screens of 1 mm (Diatex), hereafter referred to as root litterbags. The mesh size of 1 mm allowed all decomposer communities, including small invertebrates, to penetrate the nylon mesh and establish themselves on the decomposing roots (Handa et al. 2014).On October 15 th , 2018, corresponding to the harvest period, three litterbag replicates per plant species (Faidherbia tree, pearl millet or cowpea) were buried at four soil depths (20, 40, 90 and 180 cm) on 3 different walls (east, north and west walls) in each subplot (located under and far from the tree). The litterbags were buried at approximately 50 cm perpendicular to the pit walls to prevent desiccation or temperature fluctuations as much as possible. Each hole made to insert the litterbags perpendicular to the pit wall was filled with soil from the same hole. . Each litterbag was replicated five times to allow five sampling campaigns (d1 to d5), which were scheduled after 1.5, 3, 6, 9 and 15 months of root decomposition. The first months of decomposition corresponded to the dry season (d1 to d3), while the wet season started immediately before the fourth litterbag sampling (see Fig. 1). The last sampling occurred during the next dry season (d5).

In total, 3 plant species × 2 locations (subplots) × 4 soil depths × 3 pit walls × 5 sampling dates = 360 litterbags were buried. However, due to a shortage in the initial sampling of root biomass encountered in the pits, cowpea and Faidherbia litter samples were not buried at 40 and 90 cm and thus were not collected on all dates (see Fig. 2).

After litterbag collection, the remaining root litter was carefully retrieved, and the soil adhering to the decomposed roots was carefully removed by shaking by hand before being oven-dried for 48 hours at 65°C. Ash corrections were made on a subsample to remove soil particle contamination as previously described. The relative humidity of the soil around the litterbags was measured from the oven-dried soil samples. The remaining dry mass in each litterbag was calculated as

= × 100
where is the remaining dry mass (%), is the initial litter dry mass (g) and is the final litter dry mass (g).

The remaining root dry mass according to a time axis for each species at each location and each soil depth gave the decomposition kinetics, where the Y intercept was named d0. The time axis was expressed on standardized days depending on the soil temperature at each soil depth. The time was normalized by temperature using the method published by [START_REF] Mary | Calculation of nitrogen mineralization and leaching in fallow soil using a simple dynamic model[END_REF] at a reference temperature of 25°C, arbitrarily chosen as commonly used by [START_REF] Balesdent | Les temps de résidence du carbone et le potentiel de stockage de carbone dans quelques sols cultivés français[END_REF]:

= ×( )
where (days) is the time normalized at , (°C) is the reference temperature (25°C), is the measured time (days), (°C) is the average soil temperature of each day, and is the thermal coefficient ( = 0.115 for kinetics of SOC decomposition at 25°C [START_REF] Balesdent | Les temps de résidence du carbone et le potentiel de stockage de carbone dans quelques sols cultivés français[END_REF]). Then, for each root species at each location and each soil depth, the decomposition kinetics were determined by a regression between the remaining dry mass and standardized time. To better fit our data, two linear regressions were applied for individual decomposition kinetics: the first regression with a k1 coefficient was based on the first sampling date (from d0 to d1), and the second regression had a k2 coefficient (from d1 to d5). Two linear regressions × 3 root species × 2 locations × 4 soil depths = 48 coefficients were obtained. Regressions with an R-squared value lower than 50%

were removed from the dataset.

Initial litter quality

Initial root chemical qualities were determined for the three plant species (pearl millet, cowpea and Faidherbia tree). C fractions (soluble compounds, cellulose, hemicellulose and lignin) were assessed with a fibre analyser (Fibretherm®, Gerhardt) on a 500 mg root litter subsample following the Van Soest protocol [START_REF] Goering | Forage Fiber Analyses: Apparatus, Reagents, Procedures, and Some Applications[END_REF]. Root C and N elemental composition was determined with an automatic elemental analyser (Flash 2000, ThermoFisher Scientific) on 3 mg subsamples of root litter. For the total root P content, 50 mg of litter powder was mixed with 65% HNO3 and mineralized for 15 min at 200°C in a Milestone Ethos Easy microwave under standard and blank conditions. The total P content was quantified colorimetrically with the yellow vanadomolybdate assay [START_REF] Koenig | Colorimetric Determination of Phosphorus in Biological Materials[END_REF].

The proportion of C originating from roots and remaining in the soil after 15 months of decomposition was calculated for 2 species (pearl millet and Faidherbia fine roots) at both locations (under and far from the tree) and at 3 depths (0 -40, 40 -100 and 100 -200 cm, which matched the root biomass sampling and litterbag experimental setup) by multiplying the root carbon content (%) and the remaining mass at d5 (%). Decomposition data were missing at 90 cm depth for Faidherbia, and an average proportion of C at 20 and 180 cm was thus used.

Then, this calculated proportion was multiplied by the living root carbon stocks (gC m -3 ) to give the amount of remaining C originating from roots and remaining in the soil after 15 months of decomposition for each species and at each depth. For pearl millet as an annual crop, the totality of the root carbon entered the soil at each harvest and thus at each year. For Faidherbia as a perennial tree, we considered that 0.56% of the root carbon was entering the soil each year according to the acacia root turnover [START_REF] Jha | Leaf litterfall, fine root production and turnover in four major tree species of the semi-arid region of India[END_REF]. This calculation was not performed for cowpea because the root biomass in the soil profile was not assessed for pearl millet or for Faidherbia.

Soil sampling and analyses

The soil sampling campaign was conducted in late October 2018 immediately after the pits were dug. In each pit (under and far from the tree), in three out of four faces (taken as replicates), soil samples were collected at different depths (0 -10 cm, 10 -20 cm, 20 -40 cm, 40 -70 cm, 70 -100 cm, 100 -130 cm, 130 -160 cm, 160 -200 cm). The soil sampling was more detailed than the experimental design of the litterbags to obtain a precise characterization of the soil profile. Soil was sampled where the litterbags were buried. Each sample was analysed by the LAMA laboratory (IRD-US Imago, Dakar, Senegal) for total soil C and N contents by dry combustion [START_REF] Matejovic | Determination of carbon and nitrogen in samples of various soils by the dry combustion[END_REF]). The mineral C content was assumed to be insignificant, and the measured total soil C was thus associated with soil organic C. Soil pH was measured in a 1:2.5 soil-water suspension. Available phosphorus was determined according to the Olsen method and was measured by the malachite green method [START_REF] Ohno | Determination of Low Concentrations of Phosphorus in Soil Extracts Using Malachite Green[END_REF]. Soil mineral N was extracted with a 1:4 soil-1 M KCl solution, NO3 and NH4 were determined by continuous flow colorimetry (SKALARSA 3000 flow analyser), and the sum of NO3 and NH4 represented the mineral soil N content. Soil texture was determined based on five fractions (clay, silt (fine + coarse), sand (fine + coarse)).

The soil bulk density was assessed according to the cylinder method [START_REF] Blake | Bulk Density[END_REF] in each pit (under and far from the tree) on two out of four faces (as replicates) at ten soil depths (10,20,40,60,80,100,120,140,160 and 180 cm).

SOC stocks were calculated at each location (under and far from the tree) and each soil depth following the 'M1' method described by [START_REF] Poeplau | Soil organic carbon stocks are systematically overestimated by misuse of the parameters bulk density and rock fragment content[END_REF] as follows:

! "_ ,% = & ' × ! ! × (
where ! "_ ,% is the soil C stock at location ) in soil layer * (g m -2 ), ( is the width of soil layer * (m), & ' is the mean bulk density of soil layer * (g m -3 ) and ! ! is the amount of total soil C measured in soil layer * at location ) (g g -1 soil). To compare the surface soil layers with the deep layers while the compaction was different due to ploughing of the topsoil layers, we also calculated the C stock at an equivalent soil mass following the method presented by Ellert and Bettany (1995).

The total SOC stock in the whole soil profile was calculated for each location as the sum of the SOC stock in each layer.

Statistical analyses

For each measurement, data are presented as the mean values ± standard deviation of 3 replicates. Whenever the location (far from and under the tree) had no significant effect according to the methods described below, the average value of 6 replicates was calculated instead. All statistical analyses were processed with R Software (version 4.0.2) (R Core Team 2020).

To analyse the effect of depth and location on soil characteristics, linear mixed models were applied to each soil variable, with soil depth and location as fixed factors and the 3 replicated profiles as random factors. Data from the same soil profile were considered dependent on each other. Post hoc Tukey tests allowed us to determine the significance of the differences between each category of soil depth and location. C stocks in both locations were compared for each soil layer with Wilcoxon rank sum tests, as required for comparisons between 2 populations with 3 individuals each.

The initial difference in the quality of the root litter from the three plant species was analysed with one-way analysis of variance for each variable (soluble fraction, hemicellulose, cellulose, lignin, total C, total N, and total P contents and C:N). To analyse the variations in the humidity of the soil in contact with the litterbags, a linear mixed model was applied to the relative humidity, with location, soil depth, plant root species and sampling date as fixed factors and the 3 replicated profiles as random factors. To analyse the effect of location, soil depth and plant species on root litter decomposition, linear mixed models were applied to the remaining litter dry mass on each sampling date and to the k1 and k2 decomposition rates, with soil depth, location and plant species as fixed factors and the 3 replicated profiles as random factors.

To analyse the carbon inputs from the roots (Fig. 10), linear mixed models were applied to the soil C stocks, to the tree living fine root C stocks, to the pearl millet living root C stocks and to the remaining C in the soil after 15 months of decomposition (all data in gC m -3 ), with location, soil depth and plant root species as fixed factors and the 3 replicated profiles as random factors. For all the linear mixed models and analyses of variance, lme4 and car packages were used. The normality of the residues was always verified with a Shapiro-Wilk test, and the homogeneity of the variances was verified with a Bartlett test. When necessary (p-values < 5%), Box-Cox (boxcox) or Yeo Johnson (jtrans) transformations were applied.

A simple ordination of all the variables was conducted for a principal component analysis with the "vegan" and "factoextra" packages. Among the soil depths that were analysed for the initial soil characterization, only 4 depths were selected for this analysis (10 -20, 20 -40, 70 -100 and 100 -130 cm) to match the experimental design of the litterbags. Wilk's tests allowed the identification of qualitative variables (location, depth and plant species)

that significantly separated the individuals with the "FactoInvestigate" package.

Results

Effects of depth and location on soil characteristics

The soil texture was globally very sandy, with more than 70% sand in every sample (Fig. 3), but the texture was significantly impacted by soil depth (Supplementary Table 1), with soils richer in clay and lower in coarse sand in the deeper layers (Fig. 3a). Location impacted only fine sand, with a higher content far from the tree (p-value = 1.94 ×10 -2 ), while an interaction between soil depth and location was observed for the silt content (p-value = 7.63 ×10 -5 combined with soil depth).

The total C and N contents were not significantly impacted by location (Supplementary Table 1). However, the soil total C and total N contents tended to be higher under the tree than far from the tree (Fig. 4a and4b). In this poor Arenosol, the total soil C did not exceed 0.45% in the surface layer. At both locations, soil depth strongly affected the total C (F = 30.17, p-value = 3.0 ×10 -11 ) and N contents (F = 11.30, p-value = 1.2 ×10 -6 ) with a strong decrease from a depth of 30 cm. The C:N ratio, soil pH, and soil available phosphorus and mineral N contents were impacted by the interaction of depth and location, while only the mineral N and C:N ratios were significantly affected by soil depth (Supplementary Table 1). In the first 20 cm, the C:N ratios increased from 12.7 to 14.0 far from the tree and then decreased to 8.7 at 180 cm, while under the tree, the C:N ratios increased from 11.0 at the surface to 14.3 at a depth of 1 m (Fig. 4c). Soil pH presented values ranging between 6 and 7 in the topsoil. Below 40 cm, soil under the tree presented higher pH values (6.9 ± 0.6 between 40 and 180 cm) than those far from the tree (5.7 ± 0.3) (Fig. 4d). As often occurs in tropical soils, available phosphorus was very low (less than 3 mg kg - 1 ) and significantly higher under than that far from the tree (F = 3.77, p-value = 5.6 ×10 -3 , Supplementary Table 1). The available phosphorus decreased with depth to less than 1 mg kg -1 at 180 cm for both locations (Fig. 4f).

Mineral N presented similar patterns, with average values of 5.5 ± 2.8 and 9.4 ± 3.1 mg kg -1 in the topsoil far from and under the tree and decreasing to 5.0 ± 3.6 and 3.3 ± 0.1 mg kg -1 at 180 cm, respectively (Fig. 4e).

Despite important differences in total C stocks within the whole profile under the tree (7761 ± 346 g m -2 , n = 3) compared to far from the tree (5425 ± 558 g m -2 , n = 3), the samples at each soil depth did not differ significantly between locations under and far from the tree (Table 1).

Above-and belowground biomass

Pearl millet biomass was higher under the tree than far from the tree (Fig. 5). The difference was mainly noteworthy for the aboveground parts, resulting in a lower R:S ratio (0.03 compared to 0.05 far from the tree). At both locations, millet roots were concentrated in the first 40 cm depth whereas under the tree, Faidherbia fine roots were concentrated below 40 cm depth. Far from the tree, tree roots were rare between 0 and 200 cm depth (Fig. 6).

Root litter quality, soil moisture and decomposition rates Faidherbia litter was significantly enriched in lignin compared to cowpea and pearl millet litter (Table 2). Pearl millet roots presented a similar amount of lignin as in cowpea, while their soluble fraction was lower. However, the cellulose content was higher in pearl millet than in cowpea, while hemicellulose was not significantly different between the two crops. Large differences in the N content explained the important variations in C:N ratios, which varied from 13.0 for Faidherbia fine roots to 30.2 and 32.5 for cowpea and pearl millet roots, respectively.

The relative humidity of the soil in contact with the litterbags significantly increased with soil depth (F =337.9, pvalue < 2.2 ×10 -16 , Table 3), and it was higher under the tree than far from the tree (F = 24.9, p-value = 7.3 ×10 -3 , Table 3). The soil humidity was still high on d1 (9.0 ± 5.9 m 3 H2O m -3 soil) from the previous wet season and decreased significantly from d1 to d3 (F = 100.5, p-value = < 2.2 ×10 -16 , Table 3). The wet season that started immediately before d4 increased the humidity of the soil in contact with the litterbags on d4 and d5.

Regarding root litter decomposition, no significant effect of location was observed on any date (Supplementary Table 2); thus, data were compiled for both locations.

After 15 months of the experiment, neither the crop nor the tree fine roots reached an asymptote; therefore, we described decomposition with 2 slopes k1 and k2 (linear fitting) rather than with one extinction coefficient (exponential fitting). After 1.5 months of fine root decomposition, i.e., d1, the root litterbags had lost almost half of their initial dry mass; then, with the dry season, the remaining fine root mass decreased more slowly from d1 to d5 and reached approximately 25% of the initial mass at the end of the experiment (Fig. 7). The remaining fine root mass on d2 (pearl millet only) was significantly impacted by depth (F = 3.8, p-value = 4.8 × 10 -2 ), with a lower fine root remaining mass at a depth of 20 cm than at 40 cm and a lower fine root remaining mass at a depth of 90 cm than at 180 cm (Fig. 8a). On d5, the remaining mass was significantly higher for Faidherbia than for cowpea fine roots (F = 3.9, p-value = 3.5 × 10 -2 , Fig. 8b).

The k1 coefficient of the first decomposition stage was significantly impacted by the plant species (F = 3.9, pvalue = 3.5 × 10 -2 , data not shown), with higher coefficients for cowpea and lower coefficients for Faidherbia. The rate of fine root decomposition was also significantly impacted by soil depth in the case of pearl millet (F = 7.4, p-value = 4.54 × 10 -3 , Table 4), with lower values at 180 cm than at 20 cm depth. The cowpea fine root decomposition rate also decreased with soil depth but to a lesser extent than that of pearl millet (F = 7.7, p-value = 2.13 × 10 -2 , Table 4), while the fine root decomposition rate of the Faidherbia tree was only slightly impacted by depth (Table 4).

Relationships between fine root decomposition, soil characteristics and litter quality

The contribution of the main soil variables and the fine root decomposition rate to differences among soil depths is represented by the PCA (Fig. 9), which explained 50.5% of the dataset's variability. Individuals at each soil depth were well separated with no overlap between 95% confidence ellipses of three distinguished groups: 0-40 cm, 90 cm and 180 cm (Fig. 9, p-value = 2.20 × 10 -9 for Wilk's test). The variables that best explained the separation between soil depths were C:N, sand, Olsen P and clay. The k1 coefficient increased with these variables.

These variables were not correlated (orthogonal) with k2, the soil pH or silt content (Fig. 9). Therefore, the first axis of the PCA best described variables that correlated with k1, and the second axis variables correlated with k2.

Importantly, k1 and k2 were not correlated.

Discussion

Impact of Faidherbia albida trees on soil characteristics

As expected for this type of soil, the total C and N contents were quite low (less than 0.5 and 0.05%, respectively), as previously described [START_REF] Barthès | Determination of Total Carbon and Nitrogen Content in a Range of Tropical Soils Using near Infrared Spectroscopy: Influence of Replication and Sample Grinding and Drying[END_REF]Tounkara et al. 2020). The C and N contents decreased with soil depth and were higher under than far from the tree, as expected according to other agroforestry studies (Felix et al. 2018;Nair et al. 2009b), especially with Faidherbia albida [START_REF] Dilla | Preliminary estimate of carbon sequestration potential of Faidherbia albida (Delile) A.Chev in an agroforestry parkland in the Central Rift Valley of Ethiopia[END_REF], but these differences were surprisingly not significant (considering p-value > 0.05). In the 0 -40 cm soil layer, the soil C:N ratio was higher far from than that under the tree, whereas in the deeper layers, the opposite was true. These changes were associated with a large standard deviation, probably due to the low N concentration. Because Faidherbia leaf litter was shown to release high amounts of nutrients, especially N, during decomposition [START_REF] Mubarak | Decomposition and Nutrient Release from Litter Fall in the Semi-arid Tropics of Sudan[END_REF], the long-term effects of this litter may have contributed to a decrease in the surface soil C:N ratio, likely by increasing the bacterial pathway of decomposition [START_REF] Rousk | Fungal and bacterial growth in soil with plant materials of different C/N ratios[END_REF].

At a depth of 40 -180 cm, the higher C:N ratio under the tree than far from it was also related to a lower soil mineral N content, while the yield of the pearl millet was almost 3 times higher under tree [START_REF] Roupsard | How far does the tree affect the crop in agroforestry? New spatial analysis methods in a Faidherbia parkland[END_REF][START_REF] Leroux | Using remote sensing to assess the effect of trees on millet yield in complex parklands of Central Senegal[END_REF]. Due to higher pearl millet above-and belowground production, more mineral N could be taken up by the crop under the tree. However, with respect to pearl millet root distribution, the main difference between the locations under and far from the tree occurred in the topsoil (0 -40 cm), and millet did not invest biomass at great depth under the tree, which is in agreement with the higher root:total biomass ratio far from the tree. Another possible explanation is that microorganisms may immobilize soil mineral N following an N-mining strategy [START_REF] Chen | Soil C and N availability determine the priming effect: microbial N mining and stoichiometric decomposition theories[END_REF] to mineralize soil organic matter or plant litter with a high C:N ratio. The total amounts of soil C and N were not influenced by tree presence, suggesting that the nature of the litter entering the soil instead of the soil organic matter (C and N) differed under and far from the tree and would be responsible for the hypothetical Nmining strategy. We did not separate roots or aboveground plant parts according to their location (under or far from the tree) before assessing their C and N contents. However, the fine and medium roots of Faidherbia were particularly abundant under the tree below a depth of 40 cm and had a low C:N ratio of 13. The low root C:N ratio can be explained by the high N availability in this N-fixing species, which would prevent a lack of N and thus hamper the N-mining strategy. However, the presence of N-binding materials such as lignin and polyphenols could restrict N accessibility and lead to a microbial N immobilization phase, as described during the leaf decomposition of a N-fixing tree by [START_REF] Teklay | Decomposition of leaves from two indigenous trees of contrasting qualities under shaded-coffee and agricultural land-uses during the dry season at Wondo Genet, Ethiopia[END_REF]. Furthermore, the slow decomposition of Faidherbia roots due to the high lignin content could favour the development of K-strategy microorganisms dominated by fungi [START_REF] Chen | Soil C and N availability determine the priming effect: microbial N mining and stoichiometric decomposition theories[END_REF]. However, without more information on the importance and nature of the soil microbial communities in comparison to total soil C, we cannot conclude the origin of the soil C/N changes.

Several soil fertility indicators, such as mineral N and Olsen P, were higher in the topsoil (0 -40 cm) than at depth (40 -200 cm) under the tree. The enrichment of nutrients in the topsoil under the Faidherbia albida tree was in agreement with the results found by [START_REF] Yengwe | Effects of Faidherbia albida canopy and leaf litter on soil microbial communities and nitrogen mineralization in selected Zambian soils[END_REF] and explained the higher crop yield under this tree. No remaining detritus of Faidherbia leaves was observed on the soil surface during the sampling period. This was due to the active livestock in this silvo-agro-pastoral system removing the leaves, twigs and fruits from the ground during the litterfall season (April to July) due to the reverse phenology of this tree [START_REF] Roupsard | Reverse phenology and dry-season water uptake by Faidherbia albida (Del.) A. Chev. in an agroforestry parkland of Sudanese west Africa[END_REF]. However, ruminants tend to stand under trees, where excrement is deposited, which enriches the topsoil nutrient content under trees. At a depth of 50 cm, the lack of nutrients under trees compared to that far from trees could come from the increase in Faidherbia root biomass at the same depth and thus the increase in nutrient uptake at depth compared to the topsoil.

A significant interaction between the soil depth and location impacted the soil pH. Indeed, the higher soil pH under the tree compared with that far from the tree occurred mostly below a depth of 40 cm, while no significant differences were observed in the topsoil, as previously reported by [START_REF] Félix | Ramial wood amendments ( Piliostigma reticulatum ) mitigate degradation of tropical soils but do not replenish nutrient exports[END_REF] for Piliostigma shrubs in Burkina Faso. In the 40 -90 cm horizon, soil pH tended to increase under the tree (from 6.7 to 7.3), as found by [START_REF] Rao | Biophysical interactions in tropical agroforestry systems[END_REF], while acidification (from 6.5 to 5.7) was recorded far from the tree. Sandy soils are poorly buffered [START_REF] Wezel | Influence of shrubs on soil characteristics and their function in Sahelian agro-ecosystems in semi-arid Niger[END_REF], and pH is sensitive to small variations in acid-basic reactions. Although our study did not allow us to conclude the mechanisms to explain the increase in pH under the tree, acidification of the soil profile far from the tree is an indicator of fertility degradation. Acidic soils are indeed known for their relatively low microbial abundance and diversity and low cation exchange capacity (Robson 2012) and could affect millet productivity.

Impact of soil depth on root litter decomposition

Due to the climatic conditions in the study area, root decomposition occurred rapidly after crop harvest (end of October 2018), while the soil was still moist from the previous wet season, and lasted for two months thereafter (January 2019). Then, the soil dried progressively from 9.0 ± 5.9 m 3 H2O m -3 soil on d1 to 2.6 ± 2.8 m 3 H2O m -3 soil on d3, as no rain occurred until the next wet season, which started in July 2019. Faster decomposition in wetter soils confirmed a previous report by [START_REF] Duthoit | Conception d'un dispositif automatisé de chambres de mesures d'échanges gazeux du sol à fermeture horizontale. Cahier des Techniques de l'INRA Ellert BH, Bettany JR[END_REF] regarding soil respiration. This moisture regime leads to two contrasting kinetics of decomposition, with a relatively rapid first phase (k1) and a slower second phase (k2), following the same time scale, similar to the few other studies conducted under similar environmental conditions [START_REF] Mubarak | Decomposition and Nutrient Release from Litter Fall in the Semi-arid Tropics of Sudan[END_REF][START_REF] Mubarak | Millet (Pennisetum typhoides) yield and selected soil attributes as influenced by some tree types of the semi-arid tropics of Sudan[END_REF]. This result suggested that the labile part of the root litter decomposed quickly during the first phase of decomposition (k1) when the soil was very wet. Then, the decomposition slowed (k2) as the soil dried.

Soil moisture is a key factor controlling root decomposition and seems to be the main driver of decomposition kinetics after litter species, i.e., quality [START_REF] Arrouays | Contribution à la lutte contre l'effet de serre[END_REF][START_REF] Butenschoen | Interactive effects of warming, soil humidity and plant diversity on litter decomposition and microbial activity[END_REF]. Because the humidity of the root litterbags was significantly higher for the individuals located under the tree due to tree shading, which reduced soil evaporation [START_REF] Hasselquist | Canopy cover effects on local soil water dynamics in a tropical agroforestry system: Evaporation drives soil water isotopic enrichment[END_REF], greater soil water infiltration (Faye et al. 2020), the reduction of water runoff under the tree crown [START_REF] Lal | Agroforestry systems and soil surface management of a tropical alfisol: I: Soil moisture and crop yields[END_REF]) and the potential benefit of hydraulic redistribution through the Faidherbia root system (Bayala and Prieto 2020), we expected a slower fine root decomposition rate far from the tree than under the tree. This was not confirmed here. However, the lack of tree replicates may bias our results, and the study would need to be extended to a wider area of the park, including different tree sizes representing the local diversity of the parkland.

Root litter quality was the main factor controlling the rate of decomposition. Faidherbia albida roots decomposed more slowly than cowpea roots due to less soluble compounds and high lignin contents, as reported in [START_REF] Mubarak | Millet (Pennisetum typhoides) yield and selected soil attributes as influenced by some tree types of the semi-arid tropics of Sudan[END_REF], while the root N content (higher in Faidherbia fine roots) did not seem to influence k1. Over a short period of time, soluble C drives the decomposition of plant residues [START_REF] Bertrand | Can the Biochemical Features and Histology of Wheat Residues Explain their Decomposition in Soil?[END_REF][START_REF] Bertrand | Soil decomposition of wheat internodes of different maturity stages: Relative impact of the soluble and structural fractions[END_REF][START_REF] Moorhead | Vector analysis of ecoenzyme activities reveal constraints on coupled C, N and P dynamics[END_REF][START_REF] Liang | Carbon mineralization and microbial activity in agricultural topsoil and subsoil as regulated by root nitrogen and recalcitrant carbon concentrations[END_REF], while the litter N content (C:N ratio) has no impact unless N limits decomposition [START_REF] Recous | Soil inorganic N availability: Effect on maize residue decomposition[END_REF][START_REF] Bertrand | Can the Biochemical Features and Histology of Wheat Residues Explain their Decomposition in Soil?[END_REF], which does not seem to be the case here.

The remaining C after 15 months of decomposition accounted for root C inputs (Fig. 10) for 2 plant species (Faidherbia fine roots and pearl millet), at both locations (under and far from the tree) and at 3 soil layers (0 -40, 40 -100 and 100 -200 cm of depth). The effect of all combined factors was significant (F = 10.3, p-value = 5.4

× 10 -3 , Supplementary Table 2). Under the tree, Faidherbia root biomass was higher than far from the tree, and low decomposition rates of this perennial root litter were observed in the litterbags. Both of these factors resulted in higher C inputs from Faidherbia root litter under (6.2 gC m -2 between 0 and 200 cm of depth, Fig. 10) than far from the tree (0.2 gC m -2 ), which could explain the tendency of higher soil C stocks under than far from the tree (Fig. 10, Table 1). Furthermore, the root C input was higher at depth than at the surface; between 100 and 200 cm depths, the amount of remaining C after 15 months of decomposition originating from Faidherbia root litter under the tree was 7 times higher than that at 20 cm. No significant C inputs from the Faidherbia root litter were noteworthy far from the tree. Due to a different root distribution, pearl millet presented the opposite trend. Pearl millet root C inputs were significantly higher at the soil surface than at depth, with no difference between the 2 locations (Fig. 10). The pearl millet crop provided 5.7 gC m -3 at 0 -40 cm of depth through its roots. This amount is very low compared to the soil C stocks at the same depth (4708 gC m -3 far from the tree and 6429 gC m -3 under the tree), but it is repeated every growing season. The role in the soil carbon stocks of pearl millet in topsoil and of Faidherbia fine roots at depth was in agreement with that described by [START_REF] Jackson | The Ecology of Soil Carbon: Pools, Vulnerabilities, and Biotic and Abiotic Controls[END_REF], attesting that fine roots contribute substantially to soil organic carbon storage. Future studies should prospect deeper soil depths to take into account a more representative cross-section of the tree root system. We hypothesized that soil depth would slow the fine root decomposition rate due to reduced microbial activity and moisture and temperature buffering, which was confirmed for the first phase of decomposition (k1 was higher at 20 cm than at soil depths of 40, 90 and 180 cm for the three species). We did not measure microbial biomass C; however, several studies have reported its close relationships with the organic C content in soils [START_REF] Insam | Relationship between soil organic carbon and microbial biomass on chronosequences of reclamation sites[END_REF][START_REF] Webster | The Relationship between Microbial Carbon and the Resource Quality of Soil Carbon[END_REF][START_REF] Ng | Does the chemical nature of soil carbon drive the structure and functioning of soil microbial communities?[END_REF]). In the topsoil, more abundant microbial biomass and activity as well as drying/rewetting cycles that create a flush of C and microbial activity may explain the quicker decomposition rates [START_REF] Miller | Episodic rewetting enhances carbon and nitrogen release from chaparral soils[END_REF][START_REF] Sun | Drying/rewetting cycles of the soil under alternate partial root-zone drying irrigation reduce carbon and nitrogen retention in the soil-plant systems of potato[END_REF]. According to the PCA, the soil characteristics that best explained k1 were sand, the Olsen P content and the soil C:N ratio, suggesting that the very low amount of P may have decreased the microbial activity at depth.

Conclusion

Root litter decomposition varied mostly according to soil depth, with litter quality and soil moisture being the main factors related to the decomposition coefficient k1 in the first 1.5 months. Organic C originating from roots would be stored for a longer time period at depth than in the topsoil. Furthermore, tree root litter tended to be more recalcitrant than annual crop root litter and was more abundant below 40 cm, while annual roots were concentrated in the topsoil. Therefore, slow tree root decomposition at depth could play a role in increasing belowground C inputs and sequestration. In contrast, pearl millet induced root C inputs mainly in the topsoil and it did not depend on the location. The root decomposition rate was not affected by the location, but the tree fine root biomass and pearl millet vegetative production were higher under the tree than far from the tree. This difference resulted in higher soil carbon stocks under the tree than far from it.

In agroforestry systems, the diversity of plant species induces a great diversity of root qualities and thus various decomposition kinetics. Introducing trees in arable lands would globally increase root litter inputs while slowing root decomposition, especially at depth, and would thus increase the soil carbon storage potential of the system.

Further research should focus on this aspect with replicated trees and different distances from the trees according to a gradient to confirm the influence of tree presence on root decomposition kinetics. 4 The k1 coefficient for each plant species (Faidherbia tree, pearl millet and cowpea) according to soil depth (20, 40, 90, 180 cm). Data are mean values (n = 6). The different lowercase letters indicate significant differences between the soil depths accompanied by their p-values for each plant species, and ns indicates the absence of a significant effect of soil depth.

Soil depths (cm) Statistics

Fig. 1

 1 Fig. 1 Dynamics of rainfall (a), volumetric soil water content (b) and soil temperature (c) over time according to soil depth (from the topsoil to 200 cm deep) from the beginning (d0:-10/15/18) to the end of the experiment (d5: 01/22/20). On the x-axis, d0 to d5 correspond to the sampling dates after 1.5 (d1), 3 (d2), 6 (d3), 9 (d4) and 15 (d5) months of decomposition. Data are presented as daily averages. The wet season is represented in blue, and the dry season is represented in yellow.

Fig. 2

 2 Fig.2Sampling strategy in the two pits (far from and under the tree), for each root litter type (pearl millet, cowpea and Faidherbia), at four depths (20, 40, 90 and 180 cm) and for five sampling dates (after 1.5 (d1), 3 (d2), 6 (d3), 9 (d4) and 15 (d5) months). Each litterbag was replicated on three pit walls (northern (N), eastern (E) and western (W) soil profiles). Missing treatments are due to root sample shortages.

Fig. 3

 3 Fig. 3 Comparison of soil texture (%) variations in clay (a), silt (b), fine sand (c) and coarse sand (d) in the soil profile from topsoil to a depth of 180 cm in the pits under (dark) and far from the Faidherbia tree (white). Data are mean values from 3 pit walls, and error bars represent the standard deviation (n = 3).

Fig. 4

 4 Fig. 4 Total C content (a), total N content (b), C:N ratio (c), soil pH (d), mineral N content (e) and available phosphorus content (f) in the soil profile from topsoil to a depth of 180 cm in the pits under (dark) and far from the tree (white). Data are mean values from 3 pit walls, and error bars represent the standard deviation (n = 3).

Fig. 5

 5 Fig. 5 Above-(a) and belowground (b) biomasses of pearl millet under (right) and far (left) from the Faidherbia tree according to organs (ears and grains, stems and leaves, stump) and soil depths (0 -40, 40 -100 and 100 -200 cm). For each location, R:S ratios are indicated in italics.

Fig. 6

 6 Fig. 6 Comparison of fine (a) and medium (b) root biomasses of Faidherbia under (right) and far (left) from the tree according to soil depth (0 -40, 40 -100, 100 -150 and 150 -200 cm).

Fig. 7

 7 Fig. 7 Dynamics of root litter decomposition (after 1.5, 3, 6, 9 and 15 months) for the three plant species (Faidherbia tree (a), pearl millet (b) and cowpea (c)) at four soil depths (20, 40, 90, 180 cm). The wet season is represented in blue, and the dry season is represented in yellow. Data are mean values, and error bars are standard deviations (n = 6). Coefficients k1 and k2 are shown only on the left plot but were calculated for each regression.

Fig. 8

 8 Fig. 8 Final root litter remaining mass (a) on d2 (01/17/2019) for pearl millet at four soil depths (20, 40, 90 and 180 cm) and (b) on d5 (01/22/2020) for three plant species (Faidherbia tree, pearl millet and cowpea) at all soil depths. Data are mean values, and error bars are standard deviations (n=3). The different letters indicate significant differences in remaining dry mass for each soil depth (A) or for each plant species (B).

Fig. 9

 9 Fig. 9 Relationships between soil characteristics (clay, silt, sand, available P (as POlsen) and mineral N (as Nmin) contents, pH and the C:N ratio) and root decomposition (k1 and k2), according to the soil depth (20, 40, 90, 180 cm).

Fig. 10

 10 Fig. 10 Potential root C contribution to soil C stocks in one cultural season for Faidherbia and pearl millet according to the soil depth and at two locations: under (left) and far (right) from the tree. For each location, the different letters indicate significant differences in soil C stocks and in remaining C between the soil depths.

Table 1

 1 Total soil carbon stocks (g m -2 ) of equivalent soil mass according to location (under or far from the tree) at different soil depths down to 200 cm. Data are mean values ± standard deviation (n = 3). Significant differences between both locations for each soil layer were tested with Wilcoxon tests.

		Carbon stocks on equivalent soil mass (g m -2 )	Results of the tests of Wilcoxon
	Soil depth	Under tree	Far from tree	W	p-value
	0 -10 cm	883 ± 295	634 ± 44	6	0.66
	10 -20 cm	712 ± 164	543 ± 145	8	0.2
	20 -40 cm	907 ± 73	634 ± 25	6	0.2
	40 -70 cm	1272 ± 147	1064 ± 30	9	0.1
	70 -100 cm	1083 ± 353	684 ± 52	9	0.1
	100 -130 cm	769 ± 23	536 ± 88	9	0.1
	130 -160 cm	920 ± 57	623 ± 34	9	0.1
	160 -200 cm	1214 ± 101	919 ± 97	9	0.1
	Total stock	7761 ± 346	5425 ± 558	9	0.1

Table 2

 2 Initial values of biochemical qualities of the fine root litter added to the litterbags. Data are mean values ± standard deviation (n = 3). Significant differences between root litter types were tested with one-way analyses of variance. ***, ** and * indicate the significance of the impact of the studied effects on litter quality with pvalues < 0.001, 0.01, and 0.05, respectively. Letters indicate differences between the 3 types of litter.Table3ADifferences in the volumetric humidity (m 3 H2O m -3 soil) of the soil in contact with the litterbags among soil depths(20, 40, 90 and 180 cm), plant species (pearl millet, Faidherbia tree, cowpea), locations (far from and under the tree) and sampling dates (d1 to d5). Data are mean values ± standard deviation. The different lowercase letters indicate significant differences between the modalities, and ns indicates the absence of a significant effect.

			Initial values			Statistics
		Faidherbia	Pearl millet	Cowpea	F-value	p-value
	Carbon fractions
	(% DM)
	Soluble fraction	14.5 ± 2.7 a	13.9 ± 2.2 a	27.1 ± 2.2 b	29.3	8.1 ×10 -4 ***
	Cellulose	19.4 ± 2.4 a	37.9 ± 2.4 b	21.3 ± 4.4 a	29.9	7.6 ×10 -4 ***
	Hemicellulose	14.2 ± 1.9 a	27.4 ± 2.2 ab	34.3 ± 9.8 b	8.9	1.6 ×10 -2 *
	Lignine	51.9 ± 4.1 b	20.8 ± 2.1 a	17.3 ± 4.4 a	82.6	4.3 ×10 -5 ***
	Elemental
	composition (% DM)
	C	45.4 ± 0.1 c	40.9 ± 0.7 a	42.9 ± 0.8 b	37.9	4.0 ×10 -4 ***
	N	3.5 ± 0.1 c	1.3 ± 0.0 a	1.4 ± 0.0 b	1779	4.8 ×10 -9 ***
	P	0.09 ± 0.0 ab	0.07 ± 0.01 a	0.11 ± 0.01 b	12.0	8 .0 ×10 -3 **
	C :N	13.0 ± 0.3 a	32.5 ± 0.9 c	30.2 ± 0.3 b	981	2.8 ×10 -8 ***

Table 3B

 3B Differences in the volumetric humidity (m 3 H2O m -3 soil) of the soil in contact with the litterbags between each location (far from and under the tree) on each sampling date (d1 to d5). Data are mean values ± standard deviation. The different lowercase letters indicate significant differences between the modalities, and ns indicates the absence of a significant effect.

	Table
	d1		d2		d3		d4		d5
	Far	Under	Far	Under	Far	Under	Far	Under	Far	Under
	0.069 ±	0.113 ±	0.043 ±	0.070 ±	0.018 ±	0.035 ±	0.030 ±	0.051 ±	0.032 ±	0.072 ±
	0.039 a	0.069 b	0.029 a	0.048 b	0.021 a	0.032 b	0.019 a	0.049 b	0.033	0.063
	F = 16.9 p-value = 1.41 × 10 -2	F = 12.6 10 -2 p-value = 2.22 ×	F = 15.2 10 -2 p-value = 1.72 ×	F = 14.6 10 -2 p-value = 1.68 ×	ns

Acknowledgements

We would like to thank both the EU-LEAP-Agri RAMSES II and Agropolis/TOTAL Foundations DSCATT projects for the funding of the experimental setup at the "Faidherbia-Flux" platform of Sob, Niakhar district, Senegal (https://lped.info/wikiObsSN/?Faidherbia-Flux). Among the technical staff from Senegal, we are extremely indebted to Ibou Diouf from Sob village for extensive help in the field and Patricia Moulin from LAMA/IESOL for conducting all soil analyses.