Céline Badouard
email: celine.badouard@univ-reims.fr

Chadi Maalouf
email: chadi.maalouf@univ-reims.fr

Christophe Bliard
email: christophe.bliard@univ-reims.fr

Guillaume Polidori
email: guillaume.polidori@univ-reims.fr

Fabien Bogard
email: fabien.bogard@univ-reims.fr

Hygric Behavior of Viticulture By-Product Composites for Building Insulation

Keywords: bio-based composite, agromaterials, hygric properties, renewable raw sources, hygrothermal performance

One possible approach to reducing the environmental impacts associated with the building sector is the development and use of bio-based building materials. The objective of this study is to determine the water properties of bio-based insulation materials, derived from winegrowing coproducts, which promote energy efficiency. The water performance of these new bio-based materials is based on the measurement of the moisture buffer value, the sorption isotherm, and the water vapor permeability. Four by-products are analyzed: stalks, grape pomace, crushed stalks, and skins; they are combined with a potato starch binder. The performance of these composites is compared to two other bio-based composites (hemp/starch and beet pulp/starch). The stalk/starch composite can be classified as a hygroscopic and breathable material with excellent moisture retention capacity.

Introduction

The construction industry is the largest energy consumer in the European Union (about 31% of total energy consumption) and the main sector responsible for greenhouse gas emissions (about 23% of total EU carbon dioxide emissions) [START_REF]Capturing the Multiple Benefits of Energy Efficiency[END_REF]. The construction sector has a crucial role to play in helping to achieve the target of a 55% reduction in greenhouse gas emissions by 2030 compared to the level observed in 1990.

In 2015, France committed during the Paris agreements to drastically reduce its carbon emissions to achieve carbon neutrality in the second half of this century. According to Ürge-Vorsatz et al. [START_REF] Ürge-Vorsatz | Energy End-Use: Buildings[END_REF], the energy demand for heating and cooling could be reduced by almost half by 2050 compared to 2005 levels by applying today's best energy-efficient technologies. To best respect this commitment, France has put in place a new environmental regulation for energy transition for the building sector. At the end of 2021, this new environmental regulation (RE202) will propose requirements in this direction by significantly improving the insulation performance of new buildings; by promoting low-emissive construction methods, carbon-free energies, and bio-based building materials; and, finally, by integrating a summer comfort objective to adapt buildings to global warming [START_REF] Charlot-Valdieu | La Transition Énergétique des Bâtiments Publics[END_REF].

There is a growing interest in bio-based insulation materials because they are renewable, and often easily recyclable, and, during their growth, they have sequestrated large amounts of carbon from atmospheric carbon dioxide through photosynthesis. In general, the absorbed carbon dioxide is greater than the carbon dioxide produced during their manufacturing process. This means that their use in construction reduces the net amount of carbon dioxide incorporated into the building, which can lead, in some cases, to a "negative" carbon footprint [START_REF] Asdrubali | Life Cycle Analysis in the Construction Sector: Guiding the optimization of conventional Italian Buildings[END_REF][START_REF] Lawrence | Hygrothermal Performance of Bio-Based Insulation Materials[END_REF].

The thermal conductivity of bio-based insulation materials (λ ~ 0.03-0.08 W.m-1.K-1) [START_REF] Palumbo | Determination of Hygrothermal Parameters of Experimental and Commercial Bio-Based Insulation Materials[END_REF][START_REF] Fedorik | Hygrothermal Properties of Advanced Bio-Based Insulation Materials[END_REF] is generally slightly lower than that of mineral insulation products and in particular rigid foams. Bio-based insulation materials have the advantage over synthetic materials of having excellent hygrothermal performance [START_REF] Korjenic | Development and Performance Evaluation of Natural Thermal-Insulation Materials Composed of Renewable Resources[END_REF]. They have the ability to regulate indoor air humidity by absorbing and desorbing water vapor for extreme air relative humidities, reducing the need for ventilation (heating in winter and air conditioning in summer) and therefore electricity consumption. They do not contain pollutants such as COx, NOx, and SOx. They emit very little volatile organic compounds (VOCs); and their production is not energy intensive [START_REF] Liu | The Development History and Prospects of Biomass-Based Insulation Materials for Buildings[END_REF].

In this work, we have chosen to study the use of widely available co-products from vine production as a potential resource for new insulation materials. The grape pomace, also called "aignes" in the Champagne producing region (Champagne-Ardenne), corresponds to all the solid parts that remain at the end of the pressing process.

The objective of this study is to present the hydric properties of composites made from these aignes associated with potato starch. The formulations used and the thermomechanical and acoustic study of the composite thus obtained have already been reported by the authors [START_REF] Badouard | Development and Characterization of Viticulture By-Products for Building Applications[END_REF].

Materials and Methods

Materials and Samples

The wine co-products were recovered from a local plant during harvest. Four formulations were considered for trials with four different types of aggregates: grape pomace (GP), skins (P), stalks (S), and crushed stalks (CS). The binder chosen was potato starch (A), which was supplied by Roquette (Lestrem, France). Heating the starch powder at 95 °C in water leads to irreversible gelatinization caused by swelling of the grains. The obtained gel acts as a binder of the aggregates. The starch ratio in composites was set at 0.2, while the starch/water ratio was set at 0.1. The appropriate amounts of water and starch were heated at 95 °C under vigorous mechanical stirring until a translucent appearance was obtained along with a high viscosity. Wine by-products, grape pomace (GP), stalks (S), skins (P) and crushed stalks (CS) were mixed and kneaded with the starch gel for a few minutes in order to obtain a good homogeneity. The resulting mixtures were shaped in molds and then compacted under a pressure of 40 kPa for five minutes. The samples were frozen and then freeze-dried under a pressure of 3 mbar for seven days. Figure 1 shows the composites obtained. The material density is presented in Table 1. Water vapor permeability δv (kg.m-1.s-1.Pa-1) is an important property of a material as it characterizes the ability of the material to transfer moisture (diffusion, effusion, and transfer of liquid) under vapor pressure gradient. The measurement of water vapor permeability was determined by the dry cup method described in ISO 12572 [START_REF]Hygrothermal Performance of Building Materials and Products -Determination of Water Vapour Transmission Properties -Cup method[END_REF], under isothermal conditions at 23 °C. The samples (50 cm2 exposed and 4 cm thick) were conditioned at 23 °C and 50% relative humidity (RH) until weight stabilization. The test was performed on three samples of each formulation. The results presented are averaged over these three samples for each formulation.

To obtain the unidirectional moisture flow, the samples were sealed on the sides of the cups that contained a specific compound for moisture control (dry cup method, silica gel); Figure 2 illustrates the device used. This system kept the relative humidity of the air layer in the cup at 0%. The depth of the air layer between the sample and the silica gel was 3 cm. The sample-cup assembly was placed in a Binder MKF 720 climate chamber set at 50% RH and 23 °C. The mass of the assembly was measured daily until a variation lesser than ± 5% was obtained. The water vapor resistance factor, µ, and the water vapor permeability, δv, are given by Equations ( 1) and (2), respectively. G is the mass flow rate (kg.s -1 ), ΔPv is the water vapor pressure gradient, d is the thickness of the sample (m), A is the exposed area (m 2 ), and δa is the water vapor permeability of the air (kg.m -1 .s -1 .Pa -1 ). The equivalent air layer depth for water vapor diffusion Sd is given by Equation ( 3

δ v = G × d ∆P v × A (1) µ = δ a δ v (2)
S d = μ × d (3)

Sorption Isotherm

The hygroscopic curve describes the balance between the water content of the material studied and the relative humidity of the ambient air. The desiccator method described in ISO 12751 [START_REF]Hygrothermal Performance of Building Materials and Products -Determination of Hygroscopic Sorption Properties[END_REF] was used for this study. These results allowed us to draw a sorption curve representing the variation in the water content as a function of the relative humidity of the ambient air at a constant temperature of 20°C. The samples were dried for 24 h in an oven at 50°C to extract the residual moisture. The test was carried out on three cylindrical samples with a diameter of 10 cm and a thickness of 2 cm for each formulation. The results presented were averaged over these three samples for each formulation. To determine the adsorption isotherm, the samples were successively exposed to increasing humidity levels of 22, 33, 55, 75 and 93%.

For each RH level, samples were weighed periodically until they reached a constant mass (i.e. the mass change between three consecutive weighings, performed at least 24 h apart, was less than 0.1% of the total mass). The water content was calculated using Equation (4):

u = m i -m 0 m 0 = m w m 0 (4)
where m0 (g) is the dry mass of the sample, mi (g) is the mass of the sample at a given relative humidity, and mw (g) is the mass of the water absorbed by the sample.

The experimental results were then adjusted to three analytical models Merakeb [START_REF] Merakeb | Modeling of the sorption hysteresis for wood[END_REF], GAB [START_REF] Anderson | Modifications of the Brunauer, Emmett and Teller Equation[END_REF], and Van Genuchten [START_REF] Van | A Closed-form Equation for Predicting the Hydraulic Conductivity of Unsaturated Soils[END_REF]. The three models are given respectively in Equations ( 5)-( 7):

Merakeb: ln ( u u s ) = a × ln(φ) × e bφ (5)
where u is the moisture content by mass, us is the saturation moisture content by mass, φ is the relative humidity, and a and b are the Merakeb model constants.

GAB: W = W m × C G × K × φ (1-K × φ) (1-K × φ + C G ×K × φ) (6)
where W is the moisture content by mass, Wm is the saturation moisture content by mass, φ is the relative humidity, and K and CG are the GAB parameters.

where us is the saturation moisture content by mass, φ is the relative humidity, and αT and ηT are the Van Genuchten parameters.

Experimental data were correlated with the least squares method. To estimate the variability assigned to each model, the correlation coefficient (R 2 ) was calculated. Mean deviation E and mean quadratic error (RMSE) were also assessed. These criteria allowed us to assess how the model fitted the experimental results.

Moisture Buffer Value (MBV)

MBV represents the ability of the composite to regulate the relative humidity of a medium. The Nordtest protocol [START_REF] Rode | Moisture Buffering of Building Materials[END_REF] defines the cyclical variations in relative humidity after stabilization, between high (75%) and low (33%) values for 8 hours and 16 hours. The test was carried out on three cylindrical samples with a diameter of 10 cm and a thickness of 2 cm for each formulation. The results presented were averaged over these three samples for each formulation.

The edges and backsides of the samples were sealed with waterproof adhesive tape. The samples were stabilized at 23°C and 50% RH in a climate chamber and weighed five times during the absorption phase and two times during the desorption phase. This test was performed with an air velocity equal to 0.5 m/s. The water buffer capacity MBV was calculated using Equation ( 8):

where A (m 2 ) is the surface of the sample in contact with air. RHsup and RHinf represent, respectively, the high relative humidity (75% RH) and the low relative humidity (33% RH), and Δm represents the mass variation during the adsorption phase (g).

Results and Discussion

Permeability

The water vapor permeability results are presented in Table 2. The stabilization of the diffusion flow during the dry cup test was almost linear for all samples of each composition (see Figure 3). The mass flow rate G (kg.s -1 ) from Equation 1 is obtained by taking the slope of the regression line between the mass of the sample-cup assembly and the time shown in Figure 3. The resistance factor to water vapor diffusion μ was between 11.2 and 13.4. The water vapor permeability δv, was between 1.40 × 10 -11 kg.m -1 .s -1 .Pa -1 for the stalk composite (A/S) and 1.79 × 10 -11 kg.m -1 .s -1 .Pa -1 1 for the grape pomace composite (A/GP). The values obtained in this study are intermediate between the hemp-starch (H/S) composite [START_REF] Umurigirwa-Vasseur | Elaboration et Caractérisation d'un Agromatériau Chanvre-Amidon Pour le Bâtiment[END_REF] and the beet pulp-starch composites (BP/S) [START_REF] Karaky | Hygrothermal and Acoustical Performance of Starch-Beet Pulp Composites for Building Thermal Insulation[END_REF]. In comparison to the composite with the same polymer matrix (starch), the water vapor diffusion resistance factor μ is 25.7 and the water vapor permeability is 0.78 × 10 -11 kg.m -1 .s -1 .Pa -1 for BP/S while for H/S, δv, is equal to 4.74 × 10 -11 kg.m -1 .s -1 .Pa -1 and µ is 4.22. The nature of the aggregates seems to have an impact on the permeability and vapor resistance of the composites.

MBV = ∆m A × (RH sup -RH inf ) (8)
The water vapor permeability tended to increase with the increase in material density. The lower the Sd (water vapor diffusion) value, the higher the water vapor migration in the material. Materials with an Sd of less than 4 cm have a good water vapor permeability, and they are open to water vapor diffusion.

Sorption Isotherm

Figure 4 shows the isothermal sorption curves of the four formulations studied. These curves describe the balance between the relative humidity and the moisture content of the samples at a fixed temperature of 20°C. All isotherms have a "sigmoidal" look typical of cellulosic (and starch) materials [START_REF] Park | Transport Principles-Solution, Diffusion and Permeation in Polymer Membranes[END_REF][START_REF] Célino | The Hygroscopic Behavior of Plant Fibers: A Review[END_REF]. This isothermal appearance is observed when the interactions between the penetrant (water) and polymer (starch) are strong. The water molecules enter the network of the material and display three distinct sorption mechanisms depending on the relative humidity level. At low RH (<25%), monomolecular absorption prevails, water vapor molecules are adsorbed and gradually cover a layer on the surface of the pores where they are held by Van der Waals forces. When the relative humidity of the air increases, medium RH (between 25 and 40%), a second layer is adsorbed. Moisture transfer occurs simultaneously through the transfer of liquid water and vapor. Finally, at high RH (>40%), the multilayers join to form a liquid bridge separated from the gas phase by a meniscus. The water is retained on the surface of the pores by capillary forces and thus leads to the filling of the finest pores initially and then the largest pores by capillary condensation [START_REF] Collet | Caractérisation Hydrique et Thermique de Matériaux de Génie Civil a Faibles Impacts Environnementaux[END_REF]. 3 shows the model parameters used to adjust the sorption isotherm to 20°C for the different formulations. For the GAB and Merakeb models, the E values are less than 10 and the correlation coefficients for all the models used are close to 1. Thus, the GAB and Merakeb models are considered appropriate [START_REF] Zhang | Heat-insulating materials and sound-absorbing materials[END_REF]. As starch is very hydrophilic, it behaves like a sponge and is capable of absorbing water from the ambient atmosphere [START_REF] Monnet | Etude de l'Évolution Des Propriétés Mécaniques de Matériaux Amylacés Par Sélection et/ou Modifications Structurales Dirigées[END_REF], making starch-based materials highly hygroscopic. For example, beet pulp/starch materials [START_REF] Karaky | Hygrothermal and Acoustical Performance of Starch-Beet Pulp Composites for Building Thermal Insulation[END_REF] adsorb up to 20% of water and hemp/starch materials [START_REF] Maalouf | Study of the Hygric Behaviour and Moisture Buffering Performance of a Hemp-Starch Composite Panel for Buildings[END_REF] adsorb up to 17% water at 93% relative humidity. Under very high relative humidity (93% RH) and at room temperature (20 °C), the degradation of the composite along with the development of fungi on its surface are observed.

(

Table 3. Parameter values for sorption isotherm models.

Moisture Buffer Value (MBV)

This dynamic characterization of the water buffering capacities of materials simulate the daily climatic atmosphere change in a house in a realistic way and, thus, translates the relative humidity regulation capacities of the material. Figure 6 shows the moisture content, u, of the composites during changes in relative humidity between 33% and 75% at 23 °C where mw is the mass of water absorbed or released and m0 is the initial mass of the sample. Figure 6 shows the ability of the composites to absorb moisture at 75% RH and release moisture at 33% RH. For the last three cycles, the mass variation of the samples seems to stabilize, and the final MBV is calculated (Table .4). The performance classification of water buffer values according to the Nordtest project by Rode [START_REF] Rode | Moisture Buffer Value of Building Materials[END_REF] is divided into five classes: negligible between 0 and 0.25 g.m -2 . % RH -1 , limited between 0.25 and 0.5 g.m -2 . % RH -1 , moderate between 0.5 and 1 g.m -2 .% RH -1 , good between 1 and 2 g.m -2 .% RH -1 and excellent when the MBV value is higher than 2 g.m -2 .% RH -1 . The results presented in Table 4 clearly show that stalk, crushed stalk and grape pomace composites can be classified as excellent environmental relative humidity regulators according to this classification. The stalk composite shows an MBV value of 6.3 g.m -2 . % RH -1 which is well above the minimum of 2 g.m -2 . % RH -1 for this category. However, the skin composite is only classified as a good moisture regulator. In comparison with biobased materials with a starch binder, the samples of beet/starch pulp [START_REF] Karaky | Hygrothermal and Acoustical Performance of Starch-Beet Pulp Composites for Building Thermal Insulation[END_REF] have MBV values between 2.6 and 2.8 g.m -2 . % RH -1 . Hemp-starch composites [START_REF] Umurigirwa-Vasseur | Elaboration et Caractérisation d'un Agromatériau Chanvre-Amidon Pour le Bâtiment[END_REF] have similar MBV values of 2.5-2.7 g.m -2 . % RH -1 . The four composites are of a different composition and structure, which can explain the great difference between them, and the proportion of starch is identical. In addition, Brouard [START_REF] Brouard | Caractérisation et Optimisation d'un Composite Biosourcé pour l'Habitat[END_REF] has shown that the density of aggregates has an influence on MBV. Low-density aggregates have a better MBV. In this study, the stalk composite has a density of 227 kg.m -3 while the skin composite is at 433 kg.m -3 . For the A/P formulation, the material tends to crumble on the sides and can generate differences in density which somewhat explain the high standard deviations.

Models

Conclusions

The characterization tests carried out on the "aignes" (grape pomace)/starch gel composites allowed us to highlight the properties of water on the various composites studied. The water vapor diffusion resistance factor was found to be between 11.2 and 14.3, indicating good permeability for the stalk composite. The moisture storage isotherms revealed the hygroscopic nature of all composites. The moisture buffer capacity (MBV) values ranged from 1.9 to 6.3 g.m -2 . % RH -1 . The stalk, grape pomace and crushed stalk composites were above 2 g.m -2 . % RH -1 which makes them excellent water regulators, according to the NordTest project.

In general, these composites present interesting hydric properties. In comparison to other bio-based materials, our new composites have similar properties. They have the capacity to moderate the humidity of the interior air by absorbing and desorbing water vapor, which reduces the ventilation rate and therefore the need for heating in winter and air conditioning in summer. However, moisture is known to promote the growth of microorganisms, discomfort and also the degradation of the thermal stability and performance of materials. Current studies are being conducted on the durability of the composites (fungal evolution, water immersion and fire test). Furthermore, surface treatments based on linseed oil or grape seed oil are under study in order to create microbial degradation resistance and make these materials usable in practice in the building sector.

Figure 1 .

 1 Figure 1. Composites (a) A/S, (b)A/CS, (c) A/P and (d) A/GP.

Figure 2 .

 2 Figure 2. Dry cup device for measuring water vapor permeability.

  ), where d is the width of the sample in m.

  Van Genuchten: 𝑢 = 𝑢 𝑠 × (1 + | 𝛼 𝑇 ×8,314 ×296 × 𝑙𝑛(𝜑) 0.018 ×9.

Figure 3 .

 3 Figure 3. Example of diffusion flow stabilization in a dry cup test of an A/P sample to determine diffusion properties and the linear regression between the mass of the assembly and time with the obtained equation (dotted line).

Figure 4 .

 4 Figure 4. Sorption isotherms of the four composites.

Figure

  Figure 5a-d show the experimental values adjusted according to the GAB, Merakeb and Van Genuchten models. Of these models, the Van Genuchten model appears to be the least close to the experimental values. Table3shows the model parameters used to adjust the sorption isotherm to 20°C for the different formulations. For the GAB and Merakeb models, the E values are less than 10 and the correlation coefficients for all the models used are close to 1. Thus, the GAB and Merakeb models are considered appropriate[START_REF] Zhang | Heat-insulating materials and sound-absorbing materials[END_REF].

Figure 5 .

 5 Figure 5. Sorption isotherms of the four composites and comparison of experimental data with Merakeb, GAB and Van Genuchten models: (a) A/P, (b) A/S, (c) A/GP and (d) A/CS.

Figure 6 .

 6 Figure 6. Moisture absorption cycle and desorption of the four composites during the cyclic variation of the relative moisture.

Table 1 .

 1 Bulk density of composites with 20% starch.

	Composite	Abbreviations	ρbulk (kg.m -3 )
	Starch/grape skin	A/P	433 ± 78
	Starch/grape pomace	A/GP	308 ± 32
	Starch/stalk	A/S	227 ± 47
	Starch/crushed stalk	A/CS

Table 2 .

 2 Permeability and vapor resistance of the four composites (mean ± SD).

		δv × 10 -11		Sd
	Composite		µ
		(kg.m -1 .s -1 .Pa -1 )		(m)
	A/P	1.57 ± 0.16	12.83 ± 1.38	0.57 ± 0.06
	A/GP	1.79 ± 0.12	11.22 ± 0.70	0.51 ± 0.02
	A/S	1.40 ± 0.15	14.37 ± 1.59	0.66 ± 0.06
	A/CS	1.65 ± 0.21	12.30 ± 1.69	0.58 ± 0.09

Table 4 .

 4 Value of the average MBV over the last three cycles and classification according to the Nordtest project (mean ± SD).

	Parameters	A/P	A/S	A/GP	A/CS
	us	0.2771	0.2322	0.2519	0.2375
	a	0.8408	0.7298	0.8516	0.7297
	b	1.4326	1.2214	1.3056	1.4581
	Merakeb
	E (%)	7.7686	4.1947	5.3678	5.6578
	R 2	0.9961	0.9985	0.9983	0.9979
	RMSE	0.0062	0.0034	0.0037	0.0042
	Wm	0.0557	0.0664	0.0581	0.0539
	Cg	13.0356	12.3401	9.0035	22.285
	K	0.8099	0.7267	0.7825	0.7809
	GAB
	E (%)	7.5877	4.1004	5.4752	5.1060
	R 2	0.9960	0.9985	0.9983	0.9979
	RMSE	0.0063	0.0034	0.0038	0.0040
	Us	0.0015	0.0027	0.0016	0.0021
	αT	0.0000	0.0000	0.0000	0.0000
	ηT	1.4422	1.3722	1.4330	1.3947
	Van Genuchten
	E (%)	9.4271	9.3195	9.7917	7.1207
	R 2	0.9887	0.9883	0.9893	0.9913
	RMSE	0.0106	0.0097	0.0097	0.0081

Acknowledgments:

We acknowledge the EXPERI platform and the Pôle de Recherche Châlonnais for its material assistance.

Funding: This research was funded by the Communauté d'Agglomération de Châlons-en-Champagne (France) through a Ph.D grant.

Data availability statement:

The data presented in this study are available on request from the corresponding author.

Conflicts of Interest:

The authors declare no conflicts of interest.

Nomenclature


domain: sde sdv

text:
Julie Chenot-Lescure

Renaud Jaunatre

Elise Buisson
email: elise.buisson@univ-avignon.fr

Hervé Ramone

Thierry Dutoit

Using various artificial soil mixtures to restore dry grasslands in quarries

Keywords: Grassland, Raw substrate materials, Mediterranean pseudo-steppe, Artificial soil mixture, Soil restoration, Thero-Brachypodietea

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

Introduction

Ecological restoration in former quarries is often difficult because of the definitive loss of the original soil resource [START_REF] Castillejo | Influence of the application rate of an organic amendment (Municipal Solid Waste [MSW] Compost) on gypsum quarry rehabilitation in semiarid environments[END_REF][START_REF] Jarvis | So you have no soil for quarry restoration?[END_REF]. Its replacement by low quality substrates (e.g. rubble sometimes mixed with inert waste: low nutrient and organic contents, low mycorrhize, poor soil structure, low water storage, etc.) is often insufficient for successful revegetation because it limits the establishment and growth of plants, which are also exposed to recurrent drought stress in the Mediterranean region [START_REF] Oliveira | Effect of substrate treatments on survival and growth of Mediterranean shrubs in a revegetated quarry: An eight-year study[END_REF]. To date, very few studies have focused on the creation in integrum of a soil in ecological restoration projects, while this is known to be one of the key drivers of restoration success [START_REF] Mchergui | Use of dredged sediments for soil creation in the Seine estuary (France): Importance of a soil functioning survey to assess the success of wetland restoration in floodplains[END_REF][START_REF] Muñoz-Rojas | Soil quality indicators: critical tools in ecosystem restoration[END_REF].

When quarrying is performed, soils can be discarded or stockpiled, altering their quality [START_REF] Stahl | Topsoil stockpiling versus exposure to traffic: A case study on in situ uranium wellfields[END_REF]. If quarrying occurs in pristine / undamaged ecosystems, immediately transferring the soil to a restoration site (just-in-time soil transfer) is a good way to restore high species-diversity grasslands in Southeastern Mediterranean France [START_REF] Jaunatre | Can ecological engineering restore Mediterranean rangeland after intensive cultivation? A large-scale experiment in southern France[END_REF][START_REF] Bulot | Ecological restoration by soil transfer: impacts on restored soil profiles and topsoil functions[END_REF][START_REF] Buisson | Species transfer via topsoil translocation: lessons from two large Mediterranean restoration projects[END_REF]). However, this technique is hardly applied because it is costly and need to be performed concomitantly with undesirable soil extraction on undamaged well preserved ecosystems. It is thus limited to cases where a reference site is planned to be destroyed [START_REF] Bullock | Community translocation in Britain: Setting objectives and measuring consequences[END_REF].. Other sources of soils, such as from abandoned agricultural areas may also be available for restoration. However, fertilizers spread in the course of intensive exploitation (nitrogen, phosphorus and potassium) may have considerably increased the nutrient contents of these soils [START_REF] Römermann | Influence of former cultivation on the unique Mediterranean steppe of France and consequences for conservation management[END_REF]Wang et al. 2017;[START_REF] Helm | Recovery of Mediterranean steppe vegetation after cultivation: Legacy effects on plant composition, soil properties and functional traits[END_REF]. The use of the arable layer (i.e. topsoil) resulting from abandoned agricultural areas might therefore favor the establishment of undesirable species from the seedbank [START_REF] Buisson | Species transfer via topsoil translocation: lessons from two large Mediterranean restoration projects[END_REF], including ruderal and exotic invasive species, to the detriment of target stress-tolerant plant species [START_REF] Castillejo | Influence of the application rate of an organic amendment (Municipal Solid Waste [MSW] Compost) on gypsum quarry rehabilitation in semiarid environments[END_REF][START_REF] Ballesteros | Vegetation recovery of gypsum quarries: short-term sowing response to different soil treatments[END_REF][START_REF] Jaunatre | Can ecological engineering restore Mediterranean rangeland after intensive cultivation? A large-scale experiment in southern France[END_REF]. Thus, the use of such arable soil may not enable the restoration of nutrient poor grassland vegetation with high species-diversity, thus impeding the restoration of such ecosystems.

The selection of the materials at the outset of a project determines the success of the restoration process (Bradshaw 2000), and is particularly decisive for the recovery of the target vegetation associated with specific substrates [START_REF] Ballesteros | Central role of bedding materials for gypsum-quarry restoration: An experimental planting of gypsophile species[END_REF][START_REF] Ballesteros | Vegetation recovery of gypsum quarries: short-term sowing response to different soil treatments[END_REF]Whiting et al. 2004).

In order to recreate an adequate substrate starting with arable soil as a base, mixing it with natural materials (for example, originating from the geological substrate), not impacted by the chemical inputs of former agricultural practices, should allow approaching the oligotrophic characteristics of the soils of the reference communities.

The first aim of the present experimental setup was to test different mixtures of substrates in the context of a Mediterranean dry grassland (La Crau, Southern France) restoration. This will allow us to select the best substrate for initiating the successional trajectory of the vegetation towards the reference dry grassland (Asphodeletum fistulosi [START_REF] Molinier | La végétation de la Crau (Basse-Provence)[END_REF]. During the restoration process, species may not recolonize owing to a lack of seed dispersal. In that case, the recolonization process may be accelerated by sowing target species, or by sowing so-called 'nurse' species to encourage the establishment of other species [START_REF] Padilla | The role of nurse plants in the restoration of degraded environments[END_REF][START_REF] Ren | Nurse plant theory and its application in ecological restoration in lower subtropics of China[END_REF][START_REF] López | The role of nurse functional types in seedling recruitment dynamics of alternative states in rangelands[END_REF]. The second aim of this experimental setup is thus to test whether Brachypodium retusum (Poaceae) can act as a nurse species for grassland restoration in quarries. It is a perennial rhizomatous grass species which represents the most abundant species in biomass and cover in many north-western Mediterranean grasslands [START_REF] Molinier | La végétation de la Crau (Basse-Provence)[END_REF][START_REF] Luis | Fire and torrential rainfall: effects on the perennial grass Brachypodium retusum[END_REF][START_REF] Buisson | Key issues in Northwestern Mediterranean dry grassland restoration[END_REF]. It is common within its natural range [START_REF] Contu | Brachypodium retusum. The IUCN Red List of Threatened Species 2013[END_REF], where it plays an important role particularly in post-wildfire recovery [START_REF] Caturla | Early post-fire regeneration dynamics of Brachypodium retusum Pers. (Beauv.) in old fields of the Valencia region (eastern Spain)[END_REF]. B. retusum is one of the first species to reproduce after a fire [START_REF] Vidaller | Fire increases the reproduction of the dominant grass Brachypodium retusum and Mediterranean steppe diversity in a combined burning and grazing experiment[END_REF], and to rapidly recolonize the environment. It plays a key role in protecting the soil against erosion, favoring the establishment of target shrub species and preventing the establishment of undesirable species [START_REF] Caturla | Early post-fire regeneration dynamics of Brachypodium retusum Pers. (Beauv.) in old fields of the Valencia region (eastern Spain)[END_REF][START_REF] Larchevêque | Restoration of a Mediterranean postfire shrubland: Plant functional responses to organic soil amendment[END_REF][START_REF] Raventós | A resprouter herb reduces negative density-dependent effects among neighboring seeders after fire[END_REF]. Its rather tall and dense physiognomy can be expected to enable the capture of windborne seeds [START_REF] Bullock | Plants as seed traps: inter-specific interference with dispersal[END_REF][START_REF] Giladi | Shrubs and herbaceous seed flow in a semi-arid landscape: dual functioning of shrubs as trap and barrier[END_REF]) and the protection of seedlings from grazing. Consequently, B. retusum would be a good candidate to have an indirect positive impact on the establishment and survival of target species (defined here as the species found in the reference grassland).

The experimental setup was designed to test the effect of (1) the physical-chemical composition of the substrate, (2) B. retusum sowing and (3) their interaction, on the natural colonization of the regional species pool. We tested the following hypotheses: (1) The substrate mixtures, constituted exclusively of materials extracted from the quarry (pebbles of 0-30 mm with sandy matrix hereafter raw quarry material), are poor in nutrients and organic matter, and will limit the establishment of all species, i.e. undesirable ruderal species and target species; (2) Spontaneous colonization enables plant communities to tend towards the reference grassland, as long as i) they are not in competition with dense patches of ruderal species (like on the substrate mixtures with the highest proportion of arable soil), or ii) the abiotic conditions are not too harsh (like on the substrate mixtures with raw quarry material); and (3) Sowing Brachypodium retusum enables the rapid establishment of this species, and potentially facilitates the trapping of windborne seeds from the reference grassland. Sown plots will then have higher cover of B. retusum, increased richness of target species and greater similarity to the reference grassland.

Methods

Study area

Our study was carried out on a quarry in the La Crau plain, located in southeastern Mediterranean France (Bouches-du-Rhône). An area of the gravel quarry "La Ménudelle" was dedicated to this study. It was in operation from 2008 to 2011, impermeabilized in 2012 (using deposits of decantation sludgeclays and silt -presenting a strong water retention capability) and filled up in 2012-2013 (with inert materials that are non-fermentable, non-polluting and not likely to alter the physical and chemical properties of the soil down to 3.50m depth (BO-MEDDTL 2011; Figure 1). After compacting and levelling of the surface of the landfill, the site was then at an elevation of 40 cm below the original surface of the reference grassland and ready to receive the experimental setup.

The different substrate mixtures

Two types of substrates were used in the experiment for the different mixtures. 1) Arable soil from an orchard abandoned in 2015, composed of the topsoil (organo-mineral layer, 0-20 cm) and the subsoil (mineral layer, 20-40 cm) of cultivated Haplic Cambisol soil mixed together [START_REF] Chenot | Impact of quarry exploitation and disuse on pedogenesis[END_REF]. It was directly collected at the donor site at the same time as the different treatments were constituted to avoid any storage period of the soil and any enrichment in undesirable non-target species during storage (in particular windborne Asteraceae species) [START_REF] Bordez | Stratégies de revégétalisation des maquis miniers nickélifères de Nouvelle-Calédonie étude sur les potentiels biologiques des Topsoils en vue de leur utilisation pour la restauration écologique des milieux dégradés aplication au massif de Koniembo pour KNS. PhDthesis, Institut Agronomique Néo-calédonien, Nouvelle Calédonie Bradshaw A[END_REF]. 2) The raw quarry material was composed of sand and of alluvial gravel, sifted so as to keep only elements between 0 and 30 mm, also stored for less than 24h as in order to avoid enrichment with seeds of non-target species. Overall, five substrate mixtures with different proportions of each substrate were tested : 100% raw quarry material, 75% raw quarry material with 25% arable soil, 50% raw quarry material with 50% arable soil, 25% raw quarry material with 75% arable soil, and 100% arable soil (Table 1).

The various mixtures made it possible to obtain significant differences in substrate mixture physical-chemical properties (Supplement S1). The mixtures were spread in spring 2016 in the form of 30-40 cm thick 5m × 5m plots (similar thickness of soil to the reference ecosystem) using back hoes and hand tools. During the mixing of materials using backhoes, the soil was stirred, mixed and thus aired to ensure the growth of the plants [START_REF] Jarvis | So you have no soil for quarry restoration?[END_REF]. Overall, 50 plots were installed at the site in February 2016 (Supplement S2).

Sowing the dominant species

Two sowing treatments were tested: (1) Each substrate mixture without sowing of any species (natural colonization); (2) Each substrate mixture with sowing of Brachypodium spp.. Commercially available non-certified seeds of non-local origin (Spain) were sown (germination rate: 73%) in March 2016 over 625m² of experimental plots (25m² × 25 plots), with a ratio of 10g of seeds/m² (3000 seeds/m²). While we purchased Brachypodium retusum seeds only, our seed mix turned out to be only 32% B. retusum and 68% Brachypodium hybridum, the latter being an annual Brachypodium which seems to have been confused during seed collection by the seed company. However this species is also present in the reference grassland with a lower plant cover [START_REF] Pavon | Flore des Bouches-du-Rhône[END_REF]. Throughout the remainder of this article, only the term Brachypodium was used for the sown seed mix. The experimental setup thus includes five replicates of each treatment (5 substrate mixtures × 2 sowing treatments × 5 replicates).

Experimental implementation

The different treatments were spread randomly over the site (Supplement S2). No material was spread in the paths between the plots. Once a year, paths were mowed using a grass trimmer to limit their colonization by plants and avoid their seeding, which might have influenced the establishment of species on the plots by edge effects. As the reference grassland is grazed [START_REF] Saatkamp | Plant functional traits show non-linear response to grazing[END_REF][START_REF] Saatkamp | Vegetation and soil seed bank in a 23-year grazing exclusion chronosequence in a Mediterranean dry grassland[END_REF], grazing by an itinerant flock of sheep, connecting the reference grassland and all the plots, was reintroduced after the experiment was set up (for a total of 3 days a year between February and May). Finally, a drainage outlet was dug at the end of the experimental plot to avoid the stagnation of water during rainy episodes.

Annual vegetation surveys

Monitoring of the vegetation was carried out every year from 2016 to 2018 and in 2020 to assess plant recolonization dynamics and to compare the different treatments. For that purpose, permanent 4m² quadrats situated at the center of each 25m² plot (to avoid any edge effect) were monitored in May 2016, May 2017, May 2018 and May 2020. The abundance of each plant species was estimated on the basis of percent cover [START_REF] Gillet | La phytosociologie synusiale intégrée. Guide méthodologique[END_REF] and total plant cover was also estimated. The vegetation developing on the quadrats was compared with the reference ecosystem after a survey of randomly placed 4m² quadrats on the reference grassland: ten quadrats in 2018 and five quadrats in 2020. Reference plant communities contained 52.2±2.2 species per 4m², and 109 species overall in these 15 quadrats.

Data analyses

All the data analyses were performed using the packages vegan [START_REF] Oksanen | Package 'vegan': Community Ecology Package. R package version 2[END_REF], car [START_REF] Fox | car: Companion to Applied Regression[END_REF], multcomp [START_REF] Hothorn | multcomp: Simultaneous Inference in General Parametric Models[END_REF], emmeans [START_REF] Lenth | emmeans: Estimated Marginal Means, aka Least-Squares Means[END_REF]) and lme4 [START_REF] Bates | Package 'lme4': Linear Mixed-Effects Models using[END_REF]) in R 4.0.3. (R Core Team 2020).

We evaluated the effects of substrate mixtures, sowing and time on species composition, richness and cover of plant communities. We also evaluated the effects of substrate mixtures and sowing five years after the experiment was set up, in 2020. This was done on species composition, richness and cover of plant communities, as well as on Brachypodium retusum and Brachypodium hybridum covers. In 2020, we also assessed the effects of treatments on plant species richness and plant cover for target and non-target species separately (target species being the species found on the reference grassland plots in 2020). For species composition, we used the data of all species but Brachypodium spp. as the aim was to assess the effect on the plant community independently of Brachypodium cover. As the sum of species cover usually largely exceed total species cover, we therefore used as cover without Brachypodium the product of the sum of species cover excluding Brachypodium spp. cover by the estimated total plant cover, divided by the sum of all species cover, hereafter called plant cover without Brachypodium.

Two indices were used to assess the state of the plant communities compared to the reference ecosystem. 1) The CSIInorm Index (normalized Community Structure Integrity Index) measuring the proportion of the abundance of species of the reference community represented in the restored community (it shows the percentage of similarity in terms of composition and abundance of the communities studied compared to the reference community). 2) The HAI Index (Higher Abundance Index) measuring the proportion of the abundance of species in the restored community which is higher than in the reference community (it shows what is 'in excess', in terms of species and abundance in the studied communities studied compared to the reference community) [START_REF] Jaunatre | New synthetic indicators to assess community resilience and restoration success[END_REF].

In order to characterize the composition of the plant communities sampled on the different plots, two Non-Metric Multidimensional Scaling (NMDS) based on Bray-Curtis similarity were performed [START_REF] Borcard | Numerical Ecology with R[END_REF]. One NMDS was run on all years (200 quadrats (5 mixtures × 2 sowing treatments × 5 replicates × 4 years (2016,2017,2018,2020)) × 155 species) and one in 2020 (55 quadrats (5 mixtures × 2 treatments × 5 replicates + 5 quadrats in the reference grassland) × 135 species).

To test the effects of the substrate mixtures × Brachypodium sowing × time on plant species richness, plant cover, CSIInorm and HAI, one Generalized Linear Mixed Model (GLMM) was performed on each of these variables. For each, we used substrate mixtures, Brachypodium sowing and years as fixed factors and quadrats as a random factor to take repeated measures into account. They were followed by pairwise contrast comparisons with a Tukey adjustment when significant.

To test for possible effects of the substrate mixtures × Brachypodium sowing on plant species richness, plant cover CSIInorm and HAI in 2020, one Generalized Linear Model GLM was performed on each of these variables. They were followed by pairwise contrast comparisons with a Tukey adjustment when significant. All models were fitted with a poisson error distribution for plant species richness and a gamma error distribution with log link for the other variables. S3). Substrate mixtures with 100% or 75% of raw quarry material had significantly lower species richness and lower percent cover of unsown species than other substrate mixtures on all years.

Results

Effects of substrate mixtures, Brachypodium sowing and time on plant communities

Plots where Brachypodium was not sown had significantly higher species richness and higher percent cover of unsown species (Supplement S3).

CSIInorm increased by ten fold between 2016 and 2017 (especially on unsown plots and on sown plots with the highest proportion of arable soil) and then remained relatively stable or underwent a 20% decrease by 2020 (Supplement S3). HAI on unsown plots were always high (close to 1). HAI on sown plots first increased by 3 fold and then decrease by the same order to go back below 0.6 in 2020 (Supplement S3).

Effects of substrate mixtures on Brachypodium retusum cover in 2020

Brachypodium retusum had a significantly higher cover on sown plots (χ²=381.23, df=1 p<0.001***; Figure 2). It established very well on all sown plots (found on 25 plots out of 25 sown in 2020; average percent cover = 38.8%). It was found on two of the 25 unsown plots in 2020, but with a significantly lower percent cover on average (0.04%). Brachypodium hybridum had a significantly higher cover only on plots sown on the substrate mixture with 100% arable soil (χ²=23.97, df=4, p<0.001; Figure 2). Its percent cover (8.8%) was much lower than that of Brachypodium retusum (35%).

Effects of substrate mixtures and Brachypodium sowing on plant communities in 2020

Brachypodium sowing and the substrate mixtures influenced plant community composition in 2020 (Figure 3). Axis 1 of the NMDS on plant community data showed two major groups: the quadrats where Brachypodium was sown on the left and those where Brachypodium was not sown on the right. The sown quadrats were characterized by target species such as Andryala integrifolia L., Lobularia maritima (L.) Desv. and Medicago monspeliaca (L.) Trautv.. In contrast, those without sowing of Brachypodium were characterized by Dittrichia viscosa (L.) Greuter, Oloptum miliaceum (L.) Röser & Hamasha and Symphyotrichum squamatum (Spreng.) G.L.Nesom. Axis 2 of the NMDS showed a slight gradient in the structure of the plant communities in relation to substrate mixtures, and the reference grassland (Figure 3): mixtures with higher proportions of arable soil sown with Brachypodium were slightly more similar to the reference grassland than mixtures with higher proportions of raw quarry material.

Substrate mixtures with a higher proportion of arable soil had a significantly higher species richness of both target and non-target species (respectively: χ²=37.94, df=4, p<0.001 and χ²=30.94, df=4, p<0.001, Figure 4). Brachypodium sowing did not influence target plant species richness (χ²=0.05, df=1, p=0.825), and plots where Brachypodium was sown had lower richness of non-target species (χ²=13.10, df=1, p<0.001, Figure 4). Substrate mixtures with a higher proportion of arable soil also had a higher plant cover of target species, although this was significant only on plots sown with Brachypodium (χ²=38.57, df=4, p<0.001, Figure 5). The plant cover of non-target species was only significantly higher on unsown plots with a substrate mixture with 100% of arable soil compared with sown plots with the same substrate mixture (χ²=13.62, df=4, p=0.009, Figure 5).

Similarity of plant communities obtained in the different soil mixtures to those of the reference grassland

In 2020, 60 species, out of the 85 species inventoried in the five reference grassland plots, were recorded on the experimental substrate mixtures (50 plotstotal number of species in 2020 = 136). Among these 60 species, we found Anisantha madritensis (L.) Nevski, Anisantha rubens for substrates composed of 100% arable soil; χ²=31.08, df=4, p<0.001; Figure 6). The substrate mixtures with the poorest nutrient content (QM and QM_AS), presented the plant communities that were farthest from the reference grassland in terms of composition and abundance, in contrast to those with a high proportion of arable soil, such as AS and AS_QM (Figure 6). The CSIInorm restoration index also showed that plots where Brachypodium was not sown were more similar to the grassland than where Brachypodium was sown (χ²=11.89, df=1, p<0.001; Figure 6). ). Most plots also contained high abundances (>5%) of species that are common in the reference grasslands but usually recorded there with lower abundances (<0.5%) (A. madritensis, R. cristata, H. murinum, A. rubens, T. campestre, A. barbata, M. truncatula, C. foetida, Geranium molle, etc.). These three sets of species explain the relatively high HAI index (86.4%; Figure 6; Supplement S4, S5). The higher HAI restoration index on the unsown plots showed that sowing Brachypodium limited the establishment of non-target species, but this was significant only on substrate with 100% raw quarry material (χ²=11.89, df=1, p<0.001; Figure 6). There was no significant differences of HAI between substrate mixtures (χ²=2.42, df=4, p=0.660; Figure 6).

Discussion

Despite the fact that plant communities are still distant from the reference grassland after five years, the tested substrate mixtures allow the rapid establishment of a grassland-like vegetation with numerous Poaceae species. The total number of target species (defined here as the species found in the reference grassland) increased with the age of succession in the majority of substrate mixtures as already demonstrated in other restoration experiments undertaken in the La Crau grasslands [START_REF] Coiffait-Gombault | Are old Mediterranean grasslands resilient to human disturbances?[END_REF][START_REF] Bulot | Comparison of different soil transfer strategies for restoring a Mediterranean steppe after a pipeline leak (La Crau plain, South-Eastern France)[END_REF] or in other dry grasslands (Zobel et al. 1996). The first years after restoration are often characterized by weedy ruderal species [START_REF] Vida | Early vegetation development after grassland restoration by sowing low-diversity seed mixtures in former sunflower and cereal fields[END_REF]. Our results confirmed this pattern with a strong dominance of ruderal species, such as Diplotaxis tenuifolia, Polygonum aviculare, etc. which then become rare or are replaced by a mix of ruderal-competitive species sensu [START_REF] Grime | Evidence for the existence of three primary strategies in plants and its relevance to ecological and evolutionary theory[END_REF] and some target species all of which naturally colonize the site from the available regional pool of species. The most common reference grassland species found on the experimental plots after five years are i) wind-dispersed Asteraceae (Crepis foetida, Carduus pycnocephalus, Galactites tomentosa), ii) small Poaceae (Anisantha madritensis, Anisantha rubens, Catapodium rigidum) which are common in the shortterm seed bank and can easily be transported by wind over small distances as well as by sheep and ants, and iii) Fabaceae (Trifolium campestre, Trifolium glomeratum, Trifolium scabrum, Medicago truncatula) which are found in the short-term and long-term seed banks and are transported by ants [START_REF] Buisson | The implications of seed rain and seed bank patterns for plant succession at the edges of abandoned fields in Mediterranean landscapes[END_REF][START_REF] Almeida | Harvester ants as ecological engineers for Mediterranean grassland restoration: Impacts on soil and vegetation[END_REF]). This finding is similar to that of Alday et al. (2011), where species that exhibited zoochory and anemochory were most abundant in the early stages of post-mining succession. Monitoring over the longest term possible is recommended as recovery rates and patterns of change in the plant communities may be slow (Jones et al. 2018). Recovery is particularly slow in the La Crau grasslands [START_REF] Coiffait-Gombault | Are old Mediterranean grasslands resilient to human disturbances?[END_REF][START_REF] Bulot | Comparison of different soil transfer strategies for restoring a Mediterranean steppe after a pipeline leak (La Crau plain, South-Eastern France)[END_REF]). In the long term, it is expected that the plant communities on the different substrate mixtures will keep developing in different directions and will never achieve the entire restoration of the reference grassland because of highly different starting conditions (substrate mixtures) [START_REF] Prach | Vegetation succession in restoration of disturbed sites in Central Europe: the direction of succession and species richness across 19 seres[END_REF]). Such results have been already demonstrated for La Crau grasslands with former cultivation [START_REF] Jaunatre | Recovery of arbuscular mycorrhizal fungi root colonization after severe anthropogenic disturbance: four species assessed in old-growth Mediterranean grassland[END_REF]) and sheep paddocks [START_REF] Saatkamp | Romans Shape Today's Vegetation and Soils: Two Millennia of Land-Use Legacy Dynamics in Mediterranean Grasslands[END_REF]) which still show different plant composition and diversity to the reference grassland several centuries or millennia after their abandonment [START_REF] Römermann | Influence of former cultivation on the unique Mediterranean steppe of France and consequences for conservation management[END_REF]Helm et al. 2018).

While some target species colonized the restored areas, the high Higher Abundance Indices (HAI) show that some target species over develop (compared to their abundance on the reference grassland) and that non-target species are common. The latter may be due to the fact that the site is not directly surrounded by reference grassland areas, which impede possibilities of target species recolonization [START_REF] Lanta | Restoring diversity of thermophilous oak forests: connectivity and proximity to existing habitats matter[END_REF]. The neighboring areas are strongly impacted by quarry exploitation, former quarries, or former orchards where ruderal species predominate.

Non-target species may thus easily find their way to the experimental plots, carried in the seed bank of the arable soil used for the experiment, by the wind or by itinerant grazing, sheep transporting indistinctively target and non-target species (Albert et al. 2015). The pool of plant species, that is, the source of seeds, of diaspores and the potential for colonization of species plays a major role in the restoration, by influencing the process of spontaneous succession [START_REF] Řehounková | Spontaneous vegetation succession in gravel-sand pits: a potential for restoration[END_REF][START_REF] Strykstra | Assessment of dispersule availability: its practical use in restoration management[END_REF]Zobel et al. 1998). Therefore, the characteristics of the landscape should be properly taken into account for any restoration initiatives [START_REF] Strykstra | Assessment of dispersule availability: its practical use in restoration management[END_REF][START_REF] Prach | Spontaneous vegetation succession in human-disturbed habitats: A pattern across seres[END_REF][START_REF] Son | Plant species colonization in newly created road habitats of South Korea: Insights for more effective restoration[END_REF], and in our case, may have a higher success if adjacent to patches of the reference ecosystem [START_REF] Buisson | The implications of seed rain and seed bank patterns for plant succession at the edges of abandoned fields in Mediterranean landscapes[END_REF]).

The substrates represent major variables determining the rhythm and direction of plant successions and should unavoidably be taken into account in restoration programs [START_REF] Prach | Spontaneous vegetation succession in human-disturbed habitats: A pattern across seres[END_REF]. The substrate mixtures poor in nutrients, i.e. with a higher percentage of raw quarry material, may not be the best as they have lower target species plant covers and lower species richness of both target and non-target plant species than the richer soils (with a higher percentage of arable soil). Survival of target species is indeed severely impeded by harsh abiotic conditions [START_REF] Pueyo | Comparing direct abiotic amelioration and facilitation as tools for restoration of semiarid grasslands[END_REF]. Moreover, as they generally have a lower plant cover, these substrate mixtures may lead to higher soil erosion, the region having very strong winds blowing 334 days/year [START_REF] Buisson | Colonisation by native species of abandoned farmland adjacent to a remnant patch of Mediterranean steppe[END_REF]).

In the present study, fertilizers (N, P, K) applied during the phase of exploitation of the orchards and thus found in the arable soil have certainly contributed to increasing plant cover on richer substrate mixtures, as it has already been demonstrated elsewhere [START_REF] Norman | Vegetation succession after bauxite mining in Western Australia[END_REF]. Higher plant species richness on nutrient-richer soils is likely due to the fact that arable soils contain a seed bank while raw material does not [START_REF] Bulot | Comparison of different soil transfer strategies for restoring a Mediterranean steppe after a pipeline leak (La Crau plain, South-Eastern France)[END_REF]). Substrate mixtures with 50% or less of arable soils have significantly less non-target species richness and substrate mixtures with 50% or more of arable soils have significantly more target species richness or cover. Therefore, in order to favor target species richness and cover and maintain non-target cover as low as possible, the best compromise would be the substrate mixture with 50% arable soil and 50% raw quarry material. This substrate mixture also has a similarity to the reference grassland plant community which is amongst the highest.

Sowing Brachypodium seeds allowed Brachypodium retusum to establish on all plots, although its cover was lower on the raw quarry material. In 2020, sown plots have a lower richness of non-target species, a lower cover of target species, and a lower similarity to the reference grassland (as well as a lower cover of non-target species on arable soils only). These results contrast with other studies where seeding increased the establishment of target species (Baasch et al. 2012;[START_REF] Norman | Vegetation succession after bauxite mining in Western Australia[END_REF]. These experiments were however greatly different from this one: we sowed one dominant grassland species and they sowed species-rich mixtures or hay collected from a reference grassland. B. retusum therefore seems to compete with non-target species establishment and with target species growth: its clonal growth and ability to cover the ground, and its rhizome and root system make it a quite competitive species [START_REF] Bonet | Secondary succession of semi-arid Mediterranean old-field in south-eastern Spain: insights for conservation and restoration of degraded lands[END_REF][START_REF] Clary | Water relations in competitive interactions of Mediterranean grasses and shrubs[END_REF][START_REF] Saatkamp | Vegetation and soil seed bank in a 23-year grazing exclusion chronosequence in a Mediterranean dry grassland[END_REF]. This seems to contradict [START_REF] Raventós | A resprouter herb reduces negative density-dependent effects among neighboring seeders after fire[END_REF] study which showed a facilitative effect of B. retusum during the establishment phase of target species after fire. However, that study was carried out on shrubby chamaephyte species (Ulex parviflorus Pourr., Cistus albidus L., Helianthemum marifolium Mill. and Ononis fruticosa L.) and not on grassland plants as it is the case here. The reason for a greater competitive effect of B. retusum on target species than on non-target species cover most probably lays in the fact that target grassland species are stress tolerant and non-target species rather ruderal (e.g. D. tenuifolia) and competitive (e.g. O. miliaceum) species.

There was no significant effect of B. retusum on target species richness. We can therefore conclude that B. retusum impacts target species cover rather than target species establishment. In addition, these data suggest that B. retusum may not facilitate target species arrival by capturing windborne seeds as we initially hypothesized, although this could also be due to the fact that few target species seeds were wind-blown onto the experimental plots as there is no adjacent reference grassland nearby. While we show that B. retusum cover is much higher than B. hybridum, it is not possible to fully disentangle the specific effect of B. retusum from that of B. hybridum. However, so far, it is still not possible to obtain pure and certified seeds of B. retusum in Southern France. Future restoration projects in Southern France will therefore still use this mixture of B. retusum + B. hybridum from Spain, until a better option is available for purchase.

While plots with a substrate composed of 100% of arable soil and not sown with Brachypodium had the highest richness of target species and highest similarity of the plant communities to the reference grassland community, they also had the highest cover of non-target species. Moreover, using a substrate composed of 100% arable soil may limit opportunities for restoration activities due to insufficient substrate being available to restore more surface area than the area from which it was excavated. In order to increase the volume of substrate produced to restore wider areas than solely that of abandoned orchards (but also quarries), arable soil should be mixed / diluted with raw quarry material. Therefore, the next best option would be the substrate mixture with 50% arable soil and 50% quarry material. This substrate mixture does not differ significantly from the 100% arable soil mixtures in similarity to the reference grassland community and target species richness and cover. It is then a good compromise for increasing target and decreasing non-target species richness and cover.

Not sowing Brachypodium allows better growth and thus higher cover of target species; but also leads to higher non-target species richness and cover and some over-abundance of target species (A. madritensis, R. cristata, H. murinum, A. rubens, T. campestre, A. barbata, M. truncatula, C. foetida, Geranium molle, etc.). However, sowing Brachypodium, while not preventing the colonization of non-target species, does reduce their cover and richness and creates a physiognomy similar to that of the reference grassland with B. retusum as a dominant grass. B. retusum is known to be extremely slow at recolonizing areas with disturbed soils [START_REF] Coiffait-Gombault | Are old Mediterranean grasslands resilient to human disturbances?[END_REF]. Hence, sowing B. retusum is a major step towards reintroducing it.

Further studies should look at enriching sown and unsown plots with a few target species to identify the potential key roles of B. retusum in interacting with grassland species establishment. A new experiment could be about sowing a more diverse seed mixture of target species (which is still a problem as most seeds of the target species are not available for purchase) and whether sowing of B. retusum and this seed mix should be simultaneous or sequential.

Longer monitoring of these experimental plots may allow us to refine the best treatment to be applied, i.e. where non-target species decrease the most and where target species increase. Material and 25% of Arable Soil; HALF: 50% of each; AS_QM: 75% of Arable Soil and 25% of raw Quarry Material; AS: 100% of Arable Soil (see Table 1 for mixture codes). Supplement S1: Physical-chemical properties of mixtures tested at the Ménudelle quarry in the Crau plain

Soil parameter sampling

The physical and chemical analyses of the soil were performed twice: 1) in 2016 before sowing (35 samples, 6 replicates on each of the 5 substrate mixtures + 5 on the reference grassland) and 2) in 2018 (50 samples, 5 replicates on each of the 5 substrate mixtures * sowing/no sowing). Each 200-g sample of soil was collected by extracting the first ten centimeters of the soil layer outside the vegetation survey quadrats. Each sample was dried and sieved with a 2 mm mesh sieve. The physical and chemical analyses were performed by the soil analysis laboratory at INRA (Institut National de la Recherche Agronomique) in Arras, France. The reference(s) for the method used for each parameter is detailed here: pH water ratio 1:5 [START_REF] Thomas | Methods of Soil Analysis Part 3 -Chemical Methods[END_REF], CaCO3 using a Bernard calcimètre (Sparks et al. 1996), organic C [START_REF] Allison | Organic carbon[END_REF], total N by dry combustion [START_REF] Bremner | Nitrogen-Total[END_REF][START_REF] Dumas | Procédés de l'analyse organique[END_REF], C:N ratio, Cation Exchange Capacity (CEC) and exchangeable K + by Metson [START_REF] Metson | Methods of chemical analysis for soil survey samples[END_REF][START_REF] Ciesielski | A comparison between three methods for the determination of cation exchange capacity and exchangeable cations in soils[END_REF], available P [START_REF] Olsen | Estimation of available phosphorus in soils by extraction with sodium bicarbonate[END_REF]. Particle-size distribution was studied only in 2016 in 5 fractions following the Robinson method without prior decarbonisation (clay (<0.002 mm), fine silt (0.002-0.02 mm), coarse silt (0.2-2 mm), fine sand (0.05-0.2 mm) and coarse sand (0.2-2 mm)).

Data analyses of physical-chemical properties of soils

In order to compare 2016 soil physical and chemical parameter values between substrate mixtures, univariate analyses were performed. When the parametric conditions were met, an ANOVA test, followed by a post-hoc Tukey Honestly Significant Difference test, were performed whenever significant differences were encountered [START_REF] Stoll | Post Hoc Tests: Tukey Honestly Significant Difference Test[END_REF]. When the parametric conditions were not met, Generalized Linear Models (GLM) under gamma distribution were run. These analyses were followed by pairwise contrast comparisons with a Tukey adjustment. To study the changes in the chemical parameters over years (comparing the 2016 analyses with those of 2018), a principal component analysis [START_REF] Dray | ade4: Analysis of Ecological Data: Exploratory and Euclidean Methods in Environmental Sciences[END_REF] was run on the chemical data of both years, including that of the reference grassland, to show potentially differences between years and mixtures.

Patterns of change in the physical and chemical parameters of the soils The mixture of arable soil with raw quarry material reduced the fertility of the soil (Figure S1). The concentrations of nitrogen, phosphorus and potassium were reduced by a factor of five between the substrates composed entirely of arable soil (Figure S1) and those composed exclusively of raw quarry material. The proportion of sand (fine and coarse) was much greater in the raw quarry material. In contrast, clay was found in greater quantities in the mixtures with arable soil (Figure S1). The raw quarry material was characterized by higher CaCO3 and Ca content, whereas the arable soil contained significantly more organic matter and organic carbon (Figure S1). Finally, a gradient in the Cationic Exchange Capacity was observed, with greater quantities for the arable soil compared to the raw quarry material (Figure S1). The PCA (Figure S2) opposed the reference grassland from all experimental plots. Substrate mixtures with higher levels of arable soils had higher phosphorus, nitrogen, potassium and Cationic Exchange Capacity, while substrate mixtures with higher levels of raw quarry materials had higher CaCO3 and Ca content and higher pH.

  All plant communities changed over time (Supplement S3). They all started in 2016 with arable weeds, such as Diplotaxis tenuifolia (L.) DC., Polygonum aviculare L., Solanum nigrum L. and Veronica persica Poir.. With time, they gained target species of the reference grassland, such as Avena barbata Pott ex Link, Catapodium rigidum (L.) C.E.Hubb., Hordeum murinum L., Medicago truncatula Gaertn., Rostraria cristata (L.) Tzvelev, Trifolium campestre Schreb., Trifolium glomeratum L. and Trifolium scabrum L.. Overall, species richness increased with time on all plots. It increased by 5 fold between 2016 and 2017 and only by 10% from 2017 to 2020 (Supplement S3). Percent covers of unsown species increased by two fold from 2016 to 2018, then decreased by 10% in 2020 (Supplement

  (L.) Nevski, Catapodium rigidum (L.) C.E.Hubb., Crepis foetida L., Galactites tomentosus Moench, Medicago monspeliaca (L.) Trautv., Rostraria cristata (L.) Tzvelev, Sonchus oleraceus L., Trifolium campestre Schreb., Trifolium scabrum L. and Vulpia ciliata Dumort. (Supplement S4, S5). The plant communities developing on newly created substrates remained highly different from the reference grassland five years after implementation (the best CSIInorm reached 18.15%

  Unsown plots contained species not found in the reference grassland nor on sown plots, such as Artemisia verlotiorum Lamotte, Clinopodium nepeta (L.) Kuntze and Bituminaria bituminosa (L.) C.H.Stirt.. Sown plots contained species not found in the reference grassland nor on unsown plots, such as Hirschfeldia incana (L.) Lagr.-Foss. and Medicago orbicularis (L.) Bartal. (Supplement S4, S5). Unsown plots contained 10 reference grassland species not found on sown plots, such as Carduus nigrescens Vill., Eryngium campestre L., Linum strictum L., Neatostema apulum (L.) I.M.Johnst., Sideritis romana L. and Urospermum dalechampii (L.) Scop. ex F.W.Schmidt. Sown plots contained 6 reference grassland species not found on unsown plots, such as Aira cupaniana Guss., Logfia gallica (L.) Coss. & Germ., Petrorhagia prolifera (L.) P.W.Ball & Heywood and Plantago berlardii All. (Supplement S4, S5

Figure 1 .

 1 Figure 1. Diagram of the exploitation and restoration of the Ménudelle quarry in Southeastern France.

Figure 2 .

 2 Figure 2. Brachypodium cover on experimental plots in 2020 (mean cover ± standard error). Plots were sown (dark grey) or not (light grey) with Brachypodium. Substrate mixtures included QM -Quarry raw Material or AS -Arable Soil (see Table 1 for mixture codes). A. Brachypodium retusum (mean cover = 38.8%): Substrate mixtures χ²=4.98, df=4, p=0.290 n.s.; Brachypodium sowing χ²=381.23, df=1, p<0.001*** (Substrate mixtures × Brachypodium sowing χ²=5.05, df=4, p=0.282 n.s.). B. Brachypodium hybridum (mean cover = 8.2%): Substrate mixtures × Brachypodium sowing χ²=23.97, df=4, p<0.001*** (Substrate mixtures χ²=25.07, df=4, p<0.001***; Brachypodium sowing χ²=17.44, df=1, p<0.001***).

Figure 3 .

 3 Figure 3. Plant species composition in 2020 using NMDS. Polygons indicate of plots with the same treatment (NMDS stress: 0.21). Plots were sown (sown) or not (unsown) with Brachypodium. Substrate mixtures included QM: 100% of raw Quarry Material; QM_AS: 75% of raw Quarry

Figure 4 .

 4 Figure 4. Mean species richness (± standard error) of A. target species and B. non-target species on experimental plots in 2020. Plots were sown (dark grey) or not (light grey) with Brachypodium. Substrate mixtures included QM -Quarry raw Material or AS -Arable Soil (see Table 1 for mixture codes). A. Substrate mixtures χ²=37.94, df=4, p<0.001***; Brachypodium sowing χ²=0.05, df=1, p=0.825 n.s. (Substrate mixtures × Brachypodium sowing χ²=3.09, df=4, p=0.543 n.s.). B. Substrate mixtures χ²=30.94, df=4, p<0.001***; Brachypodium sowing χ²=13.10, df=1, p<0.001*** (Substrate mixtures × Brachypodium sowing χ²=2.06, df=4, p=0.726 n.s.).

Figure 5 .

 5 Figure 5. Mean plant cover (± standard error) (without Brachypodium) of A. target species and B. non-target species on experimental plots in 2020. Plots were sown (dark grey) or not (light grey) with Brachypodium. Substrate mixtures included QM -Quarry raw Material or AS -Arable Soil (seeTable 1 for mixture codes). A. Substrate mixtures × Brachypodium sowing

Figure 6 .

 6 Figure 6. Mean CSII and HAI (± standard error) on experimental plots in 2020. A. CSII: Substrate mixtures χ²=31.08, df=4, p<0.001***; Brachypodium sowing χ²=11.89, df=1, p<0.001*** (Substrate mixtures × Brachypodium sowing χ²=0.815, df=4, p=0. 936 n.s.). B. HAI: Substrate mixtures χ²=2.42, df=4, p=0.660; Brachypodium sowing χ²=19.98, df=1, p<0.001*** (Substrate mixtures × Brachypodium sowing χ²=4.14, df=4, p=0.387 n.s.).

Figure A .

 A Figure A. The bars represent the mean ± standard error (QM: 100% of raw Quarry Material; QM_AS: 75% of raw Quarry Material and 25% of Arable Soil; HALF: 50% of each; AS_QM: 75% of Arable Soil and 25% of raw Quarry Material; AS: 100% of Arable Soil). These analyses were run on 2016 data

Table 1 :

 1 Composition of the different mixtures used for the experiment.

	Code for	raw Quarry Material	Arable Soil	Color code
	figures	(QM)	(AS)	for figures
	QM	100%	0%
	QM_AS	75%	25%
	HALF	50%	50%
	AS_QM	25%	75%
	AS	0%	100%

  Table 1 for mixture codes). A. Substrate mixtures × Brachypodium sowing χ²=38.57, df=4, p<0.001*** (Substrate mixtures χ²=61.00, df=4, p<0.001***; Brachypodium

	sowing χ²=174.19, df=1, p<0.001***). B. Substrate mixtures × Brachypodium sowing
	χ²=13.62, df=4, p=0.009

** (Substrate mixtures χ²=2.01, df=4, p=0.735 n.s.; Brachypodium sowing χ²=17.81, df=1, p<0.001***).

  Table 1 for mixture codes). Substrate mixtures × Brachypodium sowing χ²=9.40, p=0.052; Substrate mixtures × Years χ²=27.49, p=0.007**; Brachypodium sowing × Years χ²=34.75, p<0.001***. QM: 100% of raw Quarry Material; QM_AS: 75% of raw Quarry Material and 25% of Arable Soil; HALF: 50% of each; Species recorded in 2020 on the different substrate mixtures for the two sowing treatments (with or without sowing of Brachypodium) and the reference grassland. QM: 100% of raw Quarry Material; QM_AS: 75% of raw Quarry Material and 25% of Arable Soil;

		Carlina Erodium Linum Poa Torilis	hispanica moschatum strictum bulbosa nodosa	x	x	x	x x x	x	x x x
		Carlina Eryngium Linum Podospermum Tragopogon HALF: 50% of each; AS_QM: 75% of Arable Soil and 25% of raw Quarry Material; AS: 100% of Arable Soil lanata x x x x campestre x trigynum laciniatum x x x x x x x porrifolius x x x x Carthamus lanatus x x x x x x x x Euphorbia cyparissias x Lobularia maritima x x x x x Polygonum aviculare x Trifolium angustifolium x x x x x x x x x x	x x x x x
	5	Catapodium Euphorbia Logfia Polypogon Trifolium Genus Centaurium Euphorbia Lolium Polycarpon Trifolium Aegilops Centaurea Euphorbia Lysimachia Poterium Trifolium Aira Cerastium Euphorbia Lysimachia Prospero Trifolium Ajuga Cerastium Euphorbia Lysimachia Psilurus Trifolium Anacyclus Chondrilla Filago Malva Reichardia Trifolium Andryala Cichorium Filago Marrubium Rostraria Trifolium Anisantha Clinopodium Filago Medicago Rumex Urospermum Anisantha Convolvulus Foeniculum Medicago Sagina Urospermum Anisantha Convolvulus Galactites Medicago Scabiosa Valantia Arenaria Conyza Galium Medicago Scolymus Verbascum Artemisia Crepis Galium Medicago Scorpiurus Veronica Artemisia Crepis Geranium Medicago Senecio Veronica Asphodelus Crepis Geranium Melilotus Sherardia Veronica Avena Crepis Hedypnois Misopates Sideritis Vicia Bellis Crepis Hippocrepis Neatostema Silene Vicia Bituminaria Cynodon Hirschfeldia Oloptum Silene Vulpia Bothriochloa Cynosurus Hordeum Pallenis Silybum Vulpia Brachypodium Brachypodium Brachypodium Bromus Bupleurum Carduus Carduus Carduus Erodium Linaria Plantago Tolpis Erodium Limonium Plantago Thymus Echium Leontodon Plantago Taeniatherum Dittrichia Lathyrus Plantago Symphyotrichum squamatum rigidum exigua gallica maritimus campestre species erythraea falcata rigidum tetraphyllum cherleri geniculata melitensis helioscopia arvensis sanguisorba glomeratum cupaniana glomeratum segetalis foemina autumnale scabrum iva pumilum serrata linum-stellatum incurvus stellatum clavatus juncea germanica sylvestris picroides suffocatum integrifolia intybus pygmaea vulgare cristata tomentosum diandra nepeta pyramidata minima pulcher dalechampii madritensis arvensis vulgare monspeliaca apetala picroides rubens cantabrica tomentosus orbicularis atropurpurea muralis leptoclados sp. murale polymorpha hispanicus sinuatum annua bursifolia parisiense rigidula muricatus arvensis verlotiorum foetida molle truncatula vulgaris persica ayardii micrantha rotundifolium indicus arvensis polita barbata sancta rhagadioloides orontium romana lathyroides sylvestris vesicaria ciliata apulum gallica sativa bituminosa dactylon incana miliaceum nocturna ciliata ischaemum echinatus murinum spinosa marianum myuros distachyon hybridum retusum hordeaceus semicompositum nigrescens pycnocephalus tenuiflorus malacoides arvensis lanceolata umbellata cicutarium echioides lagopus vulgaris vulgare tuberosus coronopus caput-medusae viscosa cicera bellardii Dittrichia graveolens Lagurus ovatus Plantago afra Stipa capillata Diplotaxis tenuifolia Lactuca serriola Petrorhagia prolifera Sonchus tenerrimus Daucus carota Hypochaeris glabra Parapholis incurva Sonchus asper Dactylis glomerata Hypericum perfoliatum Papaver rhoeas Sonchus oleraceus	QM sown unsown sown unsown sown unsown sown unsown sown unsown QM_AS HALF AS_QM x x x x x x x x x x x x x x x x x x x x x x AS x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x	x x x x Grassland x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x
									44

AS_QM: 75% of Arable Soil and 25% of raw Quarry Material; AS: 100% of Arable Soil Figure F. Mean plant cover (without Brachypodium) on experimental plots in 2016, 2017, 2018 and 2020. Plots were sown (solid lines) or not (dashed lines) with Brachypodium. Substrate mixtures included QMraw Quarry Material or AS -Arable Soil (see Table 1 for mixture codes). Substrate mixtures × Brachypodium sowing χ²=152.13, p<0.001***; Substrate mixtures × Years χ²=49.96, p<0.001***; Brachypodium sowing × Years χ²=47.98, p<0.001***. QM: 100% raw quarry material; QM: 100% of raw Quarry Material; QM_AS: 75% of raw Quarry Material and 25% of Arable Soil; HALF: 50% of each; AS_QM: 75% of Arable Soil and 25% of raw Quarry Material; AS: 100% of Arable Soil Figure G. Mean CSII on experimental plots in 2016, 2017, 2018 and 2020. Plots were sown (solid lines) or not (dashed lines) with Brachypodium. Substrate mixtures included QM -rawQuarry Material or AS -Arable Soil (see

Table 1 for mixture codes). Substrate mixtures × Brachypodium sowing × Years χ²=26.24, p=0.010*. QM: 100% of raw Quarry Material; QM_AS: 75% of raw Quarry Material and 25% of Arable Soil; HALF: 50% of each; AS_QM: 75% of Arable Soil and 25% of raw Quarry Material; AS: 100% of Arable Soil

Figure H. Mean HAI on experimental plots in 2016, 2017, 2018 and 2020. Plots were sown (solid lines) or not (dashed lines) with Brachypodium. Substrate mixtures included QM -rawQuarry Material or AS -Arable Soil (see

Table 1 for mixture codes). Substrate mixtures × Brachypodium sowing χ²=152.13, p<0.001***; Substrate mixtures × Brachypodium sowing × Years χ²=105.95, p<0.001***. QM: 100% raw quarry material; QM: 100% of raw Quarry Material; QM_AS: 75% of raw Quarry Material and 25% of Arable Soil; HALF: 50% of each; AS_QM: 75% of Arable Soil and 25% of raw Quarry Material; AS: 100% of Arable Soil Supplement S5:

Acknowledgements

This study was supported by Gagneraud construction funding. We thank Pierre Bourguet (Société des Carrières de la Ménudelle) for his collaboration. We thank Jean-Marc Arnal for the preparation and implementation of the plots, Florian and Pascal for substrate mixtures. We are also grateful to students, research assistants and field ecologists for help with fieldwork: Anne Aurière, Cannelle Moinardeau, Christel Vidaller, Chloé Malik and Daniel Pavon.

 [START_REF] Stoll | Post Hoc Tests: Tukey Honestly Significant Difference Test[END_REF][START_REF] Muñoz-Rojas | Soil quality indicators: critical tools in ecosystem restoration[END_REF]and 2020 (NMDS stress: 0.21) (NMDS stress: 0.21). Plots were sown (sown) or not (unsown) with Brachypodium. Substrate mixtures included QM: 100% of raw Quarry Material; QM_AS: 75% of raw Quarry Material and 25% of Arable Soil; HALF: 50% of each; AS_QM: 75% of Arable Soil and 25% of raw Quarry Material; AS: 100% of Arable Soil Supplement S4: Structures of plant communities recorded on the different substrate mixtures tested against the reference grassland plant community (grey: mean abundance of species recorded in the reference; white: abundance lacking in relation to the reference; orange: abundance of target species present in the community assessed; red: excess abundance of species present in the communities assessed and not in the reference). (QM: 100% of raw Quarry Material; QM_AS: 75% of raw Quarry Material and 25% of Arable Soil; HALF: 50% of each; AS_QM: 75% of Arable Soil and 25% of raw Quarry Material; AS: 100% of Arable Soil)