Loreta Cornacchia
email: loreta.cornacchia@nioz.nl

Andrew Folkard
email: a.folkard@lancaster.ac.uk

Grieg Davies
email: grieg.davies@southernwater.co.uk

Robert C Grabowski
email: r.c.grabowski@cranfield.ac.uk

Johan Van De Koppel
email: johan.van.de.koppel@nioz.nl

Daphne Van Der Wal
email: daphne.van.der.wal@nioz.nl

Sara Puijalon
email: sara.puijalon@univ-lyon1.fr

Tjeerd J Bouma
email: tjeerd.bouma@nioz.nl

Plants face the flow in V-formation: a study of plant patch alignment in streams

Keywords: submerged aquatic macrophytes, spatial patterning, eco-hydrodynamics, bio-physical feedbacks

Interactions between biological and physical processes, so-called bio-physical feedbacks, are important for landscape evolution. While these feedbacks have been quantified for isolated patches of vegetation in aquatic ecosystems, we still lack knowledge of how the location of one patch affects the occurrence of others. To test for patterns in the spatial distribution of vegetation patches in streams, we first measured the distance between Callitriche platycarpa patches using aerial images. Then, we measured the effects of varying patch separation distance on flow velocity, turbulence, and drag on plants in a field manipulation experiment. Lastly, we investigated whether these patterns of patch alignment developed over time following locations of reduced hydrodynamic forces, using two-year field observations of the temporal patch dynamics of Ranunculus penicillatus in a lowland chalk stream. Our results suggest that vegetation patches in streams organize themselves in V-like shapes to reduce drag forces, creating an optimal configuration that decreases hydrodynamic forces and may therefore encourage patch growth. Downstream patches are more frequently found at the rear and slightly overlapping the upstream patch, in locations that are partially sheltered by the established upstream vegetation while ensuring exposure to incoming flow (important for nutrient availability). Observations of macrophyte patch dynamics over time indicated that neighbouring patches tend to grow in a slightly angled line, producing a spatial pattern resembling the V-formation in migratory birds. These findings point to the general role of bio-physical interactions in shaping how organisms align themselves spatially to aero-and hydrodynamic flows at a range of scales.

Introduction

Biogeomorphic landscapes, such as rivers, mangroves and salt marshes, are characterized by strong interactions between biological and physical processes. These reciprocal interactions, also referred to as bio-physical feedbacks, are fundamental for landscape formation, adjustment, and evolution [START_REF] Corenblit | Reciprocal interactions and adjustments between fluvial landforms and vegetation dynamics in river corridors: a review of complementary approaches[END_REF][START_REF] Murray | Biomorphodynamics: Physical-biological feedbacks that shape landscapes[END_REF][START_REF] Corenblit | Engineer pioneer plants respond to and affect geomorphic constraints similarly along water-terrestrial interfaces world-wide[END_REF]. By obstructing the flow, vegetation stimulates channel formation in tidal marsh landscapes [START_REF] Temmerman | Vegetation causes channel erosion in a tidal landscape[END_REF]; [START_REF] Kearney | Salt marsh vegetation promotes efficient tidal channel networks[END_REF]. In fluvial environments, riparian and floodplain plants affect the processes and morphology of alluvial rivers [START_REF] Tal | Dynamic single-thread channels maintained by the interaction of flow and vegetation[END_REF][START_REF] Gurnell | Plants as river system engineers[END_REF]. Such environments are characterized by the presence of ecosystem engineers [START_REF] Jones | Organisms as ecosystem engineers[END_REF][START_REF] Gurnell | Plants as river system engineers[END_REF]), organisms that are able to modify their habitat through their action or their own physical structure or actions. To understand these biogeomorphic systems, many studies have focused on interactions between vegetation, hydrodynamics, and sedimentation processes [START_REF] Leonard | Flow hydrodynamics in tidal marsh canopies[END_REF][START_REF] Madsen | The interaction between water movement, sediment dynamics and submersed macrophytes[END_REF][START_REF] Bouma | Spatial flow and sedimentation patterns within patches of epibenthic structures: Combining field, flume and modelling experiments[END_REF]). These landscapes are often characterised by patchy vegetation, at least during the establishment phase. However, despite many plants being the keystone species in these environments, understanding of how flow modification at the patch scale may affect the processes and mechanisms controlling vegetation establishment and the hydrodynamics of these systems remains limited.

The interactions between flowing water and plants have been studied across different ecosystems, over a variety of spatial scales and vegetation configurations. Such configurations include homogeneous fields of vegetation [START_REF] Kouwen | Flexible roughness in open channels[END_REF][START_REF] Nepf | Flow structure in depth-limited, vegetated flow[END_REF][START_REF] Chen | Flow adjustment at the leading edge of a submerged aquatic canopy[END_REF] as well as isolated plant patches [START_REF] Sand-Jensen | Patch dynamics of the stream macrophyte, Callitriche cophocarpa[END_REF][START_REF] Bouma | Density-dependent linkage of scale-dependent feedbacks: A flume study on the intertidal macrophyte Spartina anglica[END_REF][START_REF] Chen | The wake structure behind a porous obstruction and its implications for deposition near a finite patch of emergent vegetation[END_REF]. The impact of a vegetation patch on hydrodynamics and sediment dynamics is location and scale-dependent [START_REF] Rietkerk | Regular pattern formation in real ecosystems[END_REF][START_REF] Van Wesenbeeck | Does scaledependent feedback explain spatial complexity in salt-marsh ecosystems?[END_REF][START_REF] Schoelynck | Selforganised patchiness and scale-dependent bio-geomorphic feedbacks in aquatic river vegetation[END_REF], for instance changing from reduced flow velocities within the vegetation to increased velocities around it. Many more studies have been carried out on individual patches of submerged aquatic macrophytes (for example, [START_REF] Sand-Jensen | Fine-scale patterns of water velocity within macrophyte patches in streams[END_REF][START_REF] Sand-Jensen | Influence of submerged macrophytes on sediment composition and near-bed flow in lowland streams[END_REF]Sukhodolov and Sukhodolova, 2009), compared to studies with multiple macrophyte stands [START_REF] Cotton | The effects of seasonal changes to in-stream vegetation cover on patterns of flow and accumulation of sediment[END_REF][START_REF] Wharton | Macrophytes and suspension-feeding invertebrates modify flows and fine sediments in the Frome and Piddle catchments, Dorset (UK)[END_REF][START_REF] Marjoribanks | Patch-scale representation of vegetation within hydraulic models[END_REF]. As patches in a landscape rarely grow in isolation but rather in mosaics [START_REF] Temmerman | Vegetation causes channel erosion in a tidal landscape[END_REF]; [START_REF] Van Der Wal | Spatial patterns, rates and mechanisms of saltmarsh cycles (Westerschelde, The Netherlands)[END_REF], including a pseudo-braided pattern in rivers (Dawson 1989), one patch may affect other patches by altering its local environment. The size of the gap between vegetation patches can be influenced by current velocity [START_REF] Fonseca | Influence of physical setting on seagrass landscapes near Beaufort, North Carolina, USA[END_REF] and turbulence, and has implications for physical and ecological processes (e.g. sedimentation, nutrient availability) [START_REF] Folkard | Hydrodynamics of model Posidonia oceanica patches in shallow water[END_REF]Folkard 2011). Recent attention has been focused on the larger-scale impact of multiple patches, and how their size and/or alignment affects flow patterns [START_REF] Folkard | Hydrodynamics of model Posidonia oceanica patches in shallow water[END_REF][START_REF] Vandenbruwaene | Flow interaction with dynamic vegetation patches: Implications for biogeomorphic evolution of a tidal landscape[END_REF][START_REF] Adhitya | Comparison of the influence of patch-scale and meadow-scale characteristics on flow within seagrass meadows: a flume study[END_REF]) and sediment deposition [START_REF] Meire | Interaction between neighboring vegetation patches: Impact on flow and deposition[END_REF], and the implications for landscape adjustments and evolution [START_REF] Kondziolka | Vegetation wakes and wake interaction shaping aquatic landscape evolution[END_REF][START_REF] De Lima | Flow patterns around two neighboring patches of emergent vegetation and possible implications for deposition and vegetation growth[END_REF][START_REF] Gurnell | Vegetation-hydrogeomorphology interactions in a low-energy, human-impacted river[END_REF]. However, knowledge is still lacking on how the location of one patch may affect the occurrence of another patch, potentially leading to optimal spatial configurations due to hydrodynamic force reduction.

Several studies have revealed the importance of facilitation, i.e. positive interactions between species that promote establishment by mediation of physical stress [START_REF] Bruno | Inclusion of facilitation into ecological theory[END_REF][START_REF] Callaway | Direct Mechanisms for Facilitation[END_REF]). Thus, positive feedbacks created by one patch may extend beyond the patch itself [START_REF] Bruno | Patch-size dependent habitat modification and facilitation on New England cobble beaches by Spartina alterniflora[END_REF], leading to a facilitative effect on the establishment or growth of other species. Such interactions between vegetation patches are likely to be relevant for plant establishment in lotic environments, where primary colonization is challenging due to forces that act to dislodge seedlings and fragments [START_REF] Riis | Dispersal and colonisation of plants in lowland streams: success rates and bottlenecks[END_REF][START_REF] Balke | Critical transitions in disturbance-driven ecosystems: identifying Windows of Opportunity for recovery[END_REF]. However, studies of facilitation mostly focus on interactions between individuals of different species or interspecific interactions [START_REF] Bruno | Inclusion of facilitation into ecological theory[END_REF][START_REF] Callaway | Direct Mechanisms for Facilitation[END_REF]. Consequently, we know relatively little about intraspecific facilitation mediated by existing vegetation patches of the same species and its effects on distribution patterns in the landscape. It is important to address this gap as intraspecific facilitation is likely to be a key process in flow-dominated systems, where currents and drag forces may impose a stress that limits growth and seedling establishment [START_REF] Schutten | Root anchorage and its significance for submerged plants in shallow lakes[END_REF][START_REF] Puijalon | Phenotypic plasticity in response to mechanical stress: hydrodynamic performance and fitness of four aquatic plant species[END_REF][START_REF] Balke | Windows of opportunity: thresholds to mangrove seedling establishment on tidal flats[END_REF]. It is known that vegetation patches may increase flow velocity in some adjacent areas, while reducing it directly downstream of the patch [START_REF] Bouma | Spatial flow and sedimentation patterns within patches of epibenthic structures: Combining field, flume and modelling experiments[END_REF][START_REF] Chen | The wake structure behind a porous obstruction and its implications for deposition near a finite patch of emergent vegetation[END_REF][START_REF] Schoelynck | Selforganised patchiness and scale-dependent bio-geomorphic feedbacks in aquatic river vegetation[END_REF]. As a consequence, optimal spatial configurations of vegetation patches might be expected to emerge due to patterns of hydrodynamic force reduction, specifically in terms of drag force reduction.

Plant-flow interactions have been studied intensively in vegetated streams because of their ecological and geomorphological importance [START_REF] Gurnell | Plants as river system engineers[END_REF][START_REF] Bertoldi | Physical modelling of the combined effect of vegetation and wood on river morphology[END_REF][START_REF] Grabowski | Hydrogeomorphology-Ecology interactions in river systems[END_REF], and the presence of unidirectional flow makes them an ideal model system. In this study, we investigated the spatial distribution of submerged aquatic vegetation patches and the implications of this for in-stream landscape adjustments over a two-year timescale. There were three components to the study. First, naturally occurring macrophyte patches were identified from aerial images to determine the average patch separation distances. Then, a field manipulation experiment was conducted to measure the effects of varying patch separation distance on flow velocity, turbulence, and drag on the submerged plants. We considered drag reduction as a proxy for the benefits derived by plants from their location in relation to other patches. Previous studies indicate that, on a short temporal scale, the survival and establishment of individual plants depend on successful root development (in the order of days; [START_REF] Barrat-Segretain | Comparative abilities of vegetative regeneration among aquatic plants growing in disturbed habitats[END_REF]; [START_REF] Barrat-Segretain | Regeneration and colonization of aquatic plant fragments in relation to the disturbance frequency of their habitats[END_REF]) and protection from scouring or dislodgement due to currents and drag.

Most of this primary colonization phase derives from drifting vegetative fragments, and rarely from seeds [START_REF] Sand-Jensen | Dynamic properties of recruitment, expansion and mortality of macrophyte patches in streams[END_REF][START_REF] Riis | Dispersal and colonisation of plants in lowland streams: success rates and bottlenecks[END_REF]. To test whether the most frequent patch distributions corresponded to the locations with the lowest drag forces, we related patterns of drag reduction to the observed probability of patch occurrence identified from aerial images. After colonization, single shoots develop into patches on intra-annual time scales through clonal expansion (over the course of months; [START_REF] Cotton | The effects of seasonal changes to in-stream vegetation cover on patterns of flow and accumulation of sediment[END_REF]; [START_REF] Wharton | Macrophytes and suspension-feeding invertebrates modify flows and fine sediments in the Frome and Piddle catchments, Dorset (UK)[END_REF]). Therefore, finally we tested whether such preferential patch distributions obtained from aerial images were supported by field observations of temporal patch dynamics in a lowland chalk stream over a period of two years.

Materials and methods

Measuring inter-patch distance from in-stream aerial images

To investigate the existence of preferential distributions of plant patches, we collected aerial images of an artificial drainage channel with natural colonization by aquatic vegetation. The channel is located along the Rhône River (France), near Serrières- 5.4274 ° E). The channel, selected for its uniform cross-sectional and planform geometry allowing a focus on plant configuration, had an average channel width of 8.0 m, an average depth of 0.8 m, rarely exceeding 1.3 m, with relatively straight banks. Aerial images of the streambed were taken with a digital camera mounted on a pole at a height of c. 2 m. We identified 22 pairs of neighbouring patches for the dominant aquatic macrophyte Callitriche platycarpa. This species has long, flexible shoots that are pushed in a downstream direction by the flow, generating an overhanging canopy that is rooted only at the upstream edge [START_REF] Haslam | River plants: the macrophyte vegetation of watercourses[END_REF]. The pairs could clearly be distinguished as separate patches through the presence of an unvegetated area between their rooting parts. In these streams, neighbouring patches were defined as those within 1.5 m from each other, because the influence of an upstream patch can be observed for a distance equal to its length [START_REF] Sand-Jensen | Fine-scale patterns of water velocity within macrophyte patches in streams[END_REF][START_REF] Schoelynck | Selforganised patchiness and scale-dependent bio-geomorphic feedbacks in aquatic river vegetation[END_REF], and 1.5 m is representative of the average length of C. platycarpa patches (Sand-Jensen 1998). We measured the absolute longitudinal inter-patch distance (distance between their upstream edges in the streamwise direction, Ld in m) and transversal inter-patch distance (distance between their leftmost edges in the spanwise direction, Td in m) between the pairs (Figure 1). To account for differences in absolute distances due to the variability in patch sizes, we converted them into relative distances. To obtain relative longitudinal distances (L), we divided the absolute distance Ld by the length of the upstream patch Lu. To obtain relative transversal distances (T), we divided the absolute distance Td by the width of the upstream patch Tu (Figure 1). The frequency distributions of relative longitudinal and transversal distances were first converted into probability distributions. Then, the probability distributions in the two directions were multiplied by each other to obtain the probability of naturally-observed occurrences of vegetation patches for each combination of L and T distances. This point grid was imported into GIS software and interpolated to obtain a two-dimensional probability map of naturally-observed patch occurrence (%) at different distances from an existing patch, using kriging interpolation.

Quantifying the effects of inter-patch distance on flow velocity and drag using a field manipulation experiment

Flow velocity measurements

To assess the effects of different patch configurations on flow reduction and acceleration, we measured the changes in flow velocity with varying patch separation distance through a field manipulation. Plants were detached from existing patches, transplanted on perforated metal plates and fixed through cable ties at the roots, to recreate two C. platycarpa patches (1.2 m in length, 0.6 m in width) that could be moved and arranged at different distances in the river bed. The two patches were arranged into 10 different configurations, representing a combination of longitudinal and transversal distances (Figure 2). The patch located upstream ("patch U") was kept fixed, while the other one ("patch D") was moved downstream and/or laterally to create the configurations. The two patches were partially overlapping in one configuration (T = 0.5, L = 0.46), as the leading edge of patch D started at the end of the rooted area of patch U. In this case, the overhanging canopy of patch U was located in the upper water layer, while the leading edge of patch D was located close to the bed, which still allowed water to flow in between the two patches. The patch characteristics (width, length and density) were kept constant between the fixed and mobile patches. Patch density was fixed by fitting the plants into the perforated metal plates, with an array of 9408 holes per m 2 .

The condition of the plant patches did not deteriorate during the course of the experiment, thus maintaining a similar morphological function within the river. Vertical profiles of flow velocity were measured with a 3D acoustic Doppler velocimeter (ADV, Nortek) over 2 min at 10 Hz. Hydrodynamic profiles were measured at five vertical locations of 5, 10, 20, 40 and 90% of the depth above the river bed. Around the pair of vegetation patches, vertical profiles were located at distances of 0.2 m and 0.1 m respectively from the upstream edges, and 0.2 m on both sides of each patch (at 0.35 m along their length), i.e. in the gap between the patches. For each point measurement in the profile, mean values of the velocity components u, v and w were calculated (corresponding to velocities in the x, y and z directions; m s - 1 ). Depth-averaged flow velocities u (in the streamwise direction) are expressed relative to incoming flow velocity, which was recorded at a fixed measurement point located 0.5 m upstream of patch U.

Turbulent kinetic energy

To determine the effects of different patch configurations on turbulence, we measured the changes in turbulent kinetic energy (TKE, m 2 s -2 ) with different patch separation distances. TKE is a measure of hydrodynamic turbulence that can negatively affect plants through direct effects on their growth [START_REF] Jaffe | Thigmomorphogenesis: the effect of mechanical perturbation on plants[END_REF]. Also, by governing processes of sediment trapping and resuspension [START_REF] Hendriks | Experimental assessment and modeling evaluation of the effects of the seagrass Posidonia oceanica on flow and particle trapping[END_REF], it can potentially affect plant establishment by reducing sediment stability. TKE was therefore calculated for the profile located at 0.1 m from the upstream edge of patch D, to investigate its potential implications for establishment. We first calculated the turbulent fluctuations " # (%) = "(%) -" where "(%) is the time series of flow measurements and " is the time-averaged velocity (m s -1 ) in the streamwise direction at each vertical position. The corresponding spanwise and vertical turbulent velocity components * # and + # were calculated in the same way. For each point measurement in the profile, turbulent kinetic energy (per unit mass) was then calculated as ,-. = / 0 1" # 0 + * # 0 + + # 0 3.

Drag force measurements

To investigate the benefits of different patch configurations in terms of drag reduction, we measured the effects of varying patch separation distance on drag forces. Drag forces were measured using a force transducer developed by the former WL Delft Hydraulics (now Deltares, Delft, The Netherlands). The transducer consisted of a solid platform, carried by two steel cantilever beams, with four temperature-corrected strain gauges mounted in pairs on opposite sides of each of the two steel cantilevers (for details see [START_REF] Bouma | Trade-offs related to ecosystem engineering: A case study on stiffness of emerging macrophytes[END_REF]). The voltage output for the force transducer was linearly correlated with forces up to 10 N (r 2 = 0.99, p < 0.001). During the measurements, a C. platycarpa plant was mounted on top of the transducer and placed into the river bed at the upstream edge of patch D. For the measurements, we selected isolated plants of 55.1 ± 5.8 cm in height and with 4 to 9 ramifications. Plants were attached to the transducer by their stem, and positioned in a natural growth position to closely represent the natural conditions. Voltage readings were collected on a data logger at a frequency of 100 Hz and expressed as the mean value for 1 min. As bending and leaning of the plant on the vegetation patch interferes with measuring the actual drag on the individual, drag measurements were also performed by removing patch D and repeating the measurement on the single plant. To allow comparisons between individuals, drag was expressed as a function of total plant surface area.

Effects of patch interactions on seasonal in-stream landscape adjustments: evidence from temporal field surveys

To test whether new vegetation occurred preferentially at certain distances and directions from initial vegetation patches, we analysed field surveys of vegetation development from a study on a chalk stream reach within the Frome-Piddle catchment (Dorset, UK) over two years (monthly from July 2008 to July 2009, and bimonthly thereafter until July 2010; for further information on the field surveys, please see [START_REF] Davies | The transport and retention of fine sediments in seasonally vegetated lowland streams[END_REF]). The study reach was the Bere Stream (UK Grid Reference 385563, 93009), a relatively straight 30 m section with bankfull widths ranging between 7-9 m. The dominant in-channel aquatic macrophyte was water crowfoot (Ranunculus penicillatus subsp.

pseudofluitans) which has highly similar patch establishment dynamics and structural traits to Callitriche platycarpa (rooted at the upstream part of the patch and with very flexible stems that form an overhanging canopy; [START_REF] Haslam | River plants: the macrophyte vegetation of watercourses[END_REF]. Furthermore, the main factors affecting initial establishment are determined by mechanical forces (e.g. drag, flow velocity). These forces increase the risk of plant uprooting or dislodgement and relate to plant morphological characteristics [START_REF] Bal | Trade-off between drag reduction and light interception of macrophytes: comparing five aquatic plants with contrasting morphology[END_REF], rather than species characteristics such as growth rates. Thus, field observations of Ranunculus could be compared with the findings of the field manipulation experiments of C.

platycarpa.

The data set from the Frome-Piddle catchment afforded a unique opportunity to assess the occurrence of new vegetation and changes in vegetation cover and spatial distribution over time.

The field survey was a repeated measures design over time. During each survey, macrophyte distribution was mapped along 30 transects that were located at 1-m distance intervals along the 30m long study reach. Along each transect, measurement points were located at 0.5 m intervals to record macrophyte presence and species. The sample size was 2150 measurement points, replicated over 19 surveys, of which six surveys were used in this study. Reach survey data were analysed using GIS software. The total station coordinates of the transect markers were used to georeference a digitised version of the reach within a GIS. The output resulted in an array of points that were spatially arranged along transect lines. Vegetation cover observed at points in the reach data set were interpolated using an Inverse Distance Weighted (IDW) interpolation method. If the predicted surface outputs from IDW differed from the substrate cover observed at any extra observation point not used in the IDW, the substrate cover observed at that point prevailed above the IDW interpolation. Separate vegetation patches were derived using the minimum bounding geometry enclosing each of the polygon outputs from IDW. Although not measured in this study, seasonal changes in macrophyte cover are generally associated with changes in vegetation biomass density (g dry weight m -2 ). A previous study in the Bere Stream found that Ranunculus density was lowest during winter (January, about 100 g DW m -2 ) and peaked during the summer months (May -July), when it reached about 400 g DW m -2 [START_REF] Dawson | The annual production of the aquatic macrophyte Ranunculus penicillatus var. calcareus (RW Butcher) C.D.K. Cook[END_REF]).

We tested the hypothesis that directions of growth of new patches compared to existing patches during the survey period show preferential directions for plant growth, instead of being uniformly distributed in all directions. Therefore, six replicate surveys over three different periods were selected over the two years (December 2008 -July 2009, September 2009 -January 2010, January 2010 -July 2010) because a net increase in Ranunculus cover was measured within each of them, allowing the phase of new macrophyte patch colonization to be captured. The shortest distance and direction (angle) between each new vegetation patch and the closest existing patch at the beginning of each survey period were calculated using the 'Near' tool in ArcMap 10.4.

Statistical analyses

In the aerial photography, 22 replicate pairs of patches were considered. A chi-squared test was used to test for significant differences in the frequency of observed longitudinal and transversal distances between vegetation patches. In the field experiment, the statistical design was a fully factorial design with transversal and longitudinal distances as the main factors, comprising ten different configurations (treatments) each measured once. Regression analysis was used to test the effects of varying longitudinal and transversal distances on depth-averaged and near-bed (5 and 10% of depth above the river bed) flow velocities in four different positions (between the patches, at the upstream edge of patch D, next to patch U, next to patch D), and on turbulent kinetic energy at the upstream edge of patch D. We tested whether relative flow velocities would increase linearly with increasing inter-patch distances, or follow a quadratic relationship which might be expected if relative flow velocities first increase until a maximum at intermediate distances, and then decrease to 1 as they become equal to incoming flow velocity. In the latter case, patches become far enough apart so that they cease to interact. Hence, we fitted both linear and quadratic models using single (L or T distances) and multiple (L and T distances) predictor variables. We then used Akaike's Information Criterion to compare the adequacy of the candidate models, and selected the model with the lowest AIC score [START_REF] Akaike | Information theory and an extension of the maximum likelihood principle[END_REF]. Regression analysis was used to test for the relationship between flow velocities and drag forces on C. platycarpa in the field flume experiment. Ordinary Least Square (OLS) regression was used for spatial regression between the experimental drag measured around a vegetation patch, and the probability of naturally-observed patch occurrence.

The latter was first log-transformed (natural log of original value + 0.5) due to its skewed distribution. A chi-squared test was used to test for significant differences in angle of growth compared to a uniform distribution in all directions. A paired t-test was used to compare drag forces measured on single plants to drag on plants located at the upstream edge of a vegetation patch.

Results

Observed inter-patch distances between pairs of macrophytes

The analysis of aerial photographs from the Rhône River study reach revealed that naturallyoccurring C. platycarpa stands display a non-random distribution relative to neighbouring patches (Figure 1). We observed that the leading edge of the downstream patch was most frequently located between one third and halfway along the length of the upstream patch (i.e., L = 0.3 -0.5) (χ 5 0 = 20.54, p = 0.008). This longitudinal separation distance was relatively constant, regardless of the size and shape of the patches we analysed (width/length ratios ranged from 0.25 to 0.83). In the transversal direction, the downstream patch was most frequently located at 80% of the width of the upstream patch from the latter's lateral edge (i.e. T = 0.8), hence partially overlapping with, and sheltered by, the overhanging canopy of the patch ahead (χ 6 0 = 14.90, p = 0.021).

Effects of inter-patch distance on flow velocity and turbulence

Measurements of the hydrodynamic effects of different patch configurations in the Rhône River study reach showed that depth-averaged flow velocity and turbulence patterns were strongly affected by the distance between patches. In between the patches, flow velocity was strongly reduced when the patches were partly overlapping (i.e. for T = 0.5 and L = 0.46), but it increased when a clear separation developed between patches and flow was constricted. We found a significant linear relationship between flow velocities in between the patches and the relative transversal (T, spanwise) distance between the patches (F1, 8 = 31.45, r 2 = 0.79, p < 0.001; Figure 3a -c; Table 1). When the patches were close together, with no more than a 5 cm gap (T ≤ 1.08), flow velocities between them were reduced and the pair tended to behave more like a single patch.

However, flow velocity accelerated when the gap between the patches, and therefore T, increased.

In particular, at T = 1.58, flow velocities between the two patches were higher than incoming velocities due to flow constriction (Figure 3b).

We found that turbulence was minimized at intermediate distances along the length of an upstream patch, while it increased both when the patches were next to each other and when one was immediately downstream of the other. Turbulent kinetic energy upstream of the patch was significantly related to relative longitudinal distance L through a quadratic relationship (F2, 7 = 5.719, r 2 = 0.62, p = 0.03), the highest TKE occurred when patches were located next to each other (for L = 0; Figure 3d -f). From L=0, TKE decreased with increased relative longitudinal distance until a minimum at L = 0.66, after which it increased again for L > 0.66 as it entered the high TKE region in the wake of the upstream patch. This minimum TKE at L = 0.66 seems to be the point at which there was an optimal combination of sheltering from the oncoming flow by the upstream patch (which increased with L), and minimization of the high TKE region in the wake of the upstream patch (which decreased with L). For the mean flow velocities upstream of patch D, results of single and multiple regression showed no significant relationship with T and L distances (Table 1).

Areas of weakest flow deflection (i.e. reduced hydrodynamic forces) were found around the upstream patch at intermediate longitudinal distances and, in particular, when the two patches were partly overlapping. However, flow deflection increased both when the patches were next to each other and when one was immediately downstream of the other. A significant non-linear (quadratic) relationship was found between flow velocities next to patch U and both relative transversal (T) and relative longitudinal (L) distances (F4, 5 = 7.931, r 2 = 0.90, p = 0.03; Figure 3g -i; Table 1). As L increased, flow velocity first decreased for intermediate distances (between 0.16 and 0.58), due to weaker flow redirection around the patch. Then, it increased again to become equal to the incoming flow velocity, following a quadratic relationship. As T increased, and therefore the gap between the patches increased, the flow velocity increased until it was equal to the incoming flow velocity for T ≥ 1.5. However, flow velocities next to patch D showed no significant relationship with relative transversal (T) and longitudinal (L) distances (Table 1).

Testing the relationship between patch distance and near-bed flow velocities revealed no significant relationship between patch distances and velocities at 5% of the depth above the river bed (Supporting Information, Table S1). A significant quadratic relationship between flow velocities in between the patches and both relative transversal (T) and relative longitudinal (L) distances was confirmed for flow measurements at 10% of the depth (Supporting Information, Table S2).

Effects of inter-patch distances on drag forces

Existing vegetation patches appeared to create sheltered areas where drag was minimized, and new patches were more likely to occur in these locations. Measurements of the drag force derived from a plant's particular location around an existing vegetation patch revealed a significant relationship between flow velocity and drag force per unit surface area on C. platycarpa individuals (r 2 = 0.92, p = 0.0001; Figure 4a). As our field drag force measurements were in the same order of magnitude as measurements performed on the same species in a laboratory flume [START_REF] Puijalon | Plant resistance to mechanical stress: evidence of an avoidance-tolerance trade-off[END_REF], we assert that the field set-up provided comparable and accurate measurements. Drag forces ranged from 0.19 to 4.63 N m -2 , due to the flow modification by the vegetation patch, with lowest drag forces right along the lateral edge of the patch, at ≥ 0.55 m from the upstream edge. This distance along the length of the patch corresponded to the end of the rooted area and the start of the floating canopy, with the downstream patch forming an angle of 28° relative to the upstream patch. Plotting the drag in an interpolated spatial grid around a patch shows that the most frequent locations of neighbouring patches based on our field observations correspond to positions with intermediate to low drag forces (Figure 4b andd). Furthermore, the probability of observed patch occurrence in a certain position is inversely related to the observed drag force in that position (ordinary least squares spatial regression, r 2 = 0.28, p < 0.0001, Figure 4c).

Comparison of average drag force measurements on single plants, representing the conditions of initial establishment, compared to plants located at the upstream edge of a well-established patch (n = 10 configurations) showed that C. platycarpa individuals experience significantly higher drag when alone (Figure 5; paired t-test, t19 = -2.28, p = 0.03). This observation shows that drag forces on the upstream plants are mitigated by leaning onto other plants in a patch.

Effects of patch interactions on seasonal in-stream landscape adjustments: evidence from temporal field surveys

Field surveys over a two year period in the Frome-Piddle catchment (UK) showed that new vegetation patches occurred at specific orientations from existing vegetation patches (χ 7 0 = 9.20, p = 0.1 for Dec. 2008 -July 2009; χ 7 0 = 12.80, p = 0.025 for Sept. 2009 -Jan. 2010; χ 7 0 = 10.88, p = 0.053 for Jan. 2010 -July 2010, and χ 7 0 = 24.34, p < 0.001 for all survey periods together; Table 2).

Within each of the three time periods we analysed, the most common direction of growth was at angles between 0 and 60° from existing patches (with a peak around 30°), in a downstream direction towards the right bank with a second most common direction at angles between 120 and 180°, downstream towards the left bank (Figure 6; Table 2). The most common angles of growth found through field surveys are consistent with the angle of 28° found through field measurements and corresponding to a region where drag forces are the lowest (Figure 4). Overall, these observations support the hypothesis that new patches occur in a slightly angled line with respect to existing well-established patches, in locations with reduced hydrodynamic and drag forces (Figure 4).

The observed seasonal trends of in-stream vegetation growth and die-back were similar over the two survey years in the Frome-Piddle catchment (Table 2; the corresponding changes in fine sediment deposition within Ranunculus patches are reported in [START_REF] Davies | The transport and retention of fine sediments in seasonally vegetated lowland streams[END_REF]. During both years, Ranunculus reached its peak cover in the period May -July and began to decline shortly after (until December), due to the seasonal dieback linked to increasing channel discharge and decreasing daylengths and water temperatures. In September 2009, a particularly low Ranunculus cover was observed (7%), likely related to the increase in autumn discharges. However, in-stream vegetation started to recover from January onwards, when daylengths increased, with new Ranunculus patches recolonizing the stream bed.

Discussion

While most studies of bio-geomorphic feedbacks have focused on isolated or already established patches, our study examined the spatial configuration of patches and quantified where plant patches occur in relation to one another. A key finding was that new vegetation patches in streams organize themselves in V-like shapes during the establishment phase to reduce hydrodynamic and drag forces. Field observations showed that patches are more likely to grow at the end of the rooted area of the upstream patch, where its floating canopy starts (i.e., between one third and halfway down the length of an upstream patch), and slightly off to its side (overlapping with part of their width).

Measurements in the field revealed that these locations correspond to areas where drag is reduced, due to partial sheltering from high flow velocities and TKE by well-established vegetation patches.

Field manipulations supported this hypothesis, showing that mean flow velocity is reduced by partially overlapping with upstream patches in the across-stream direction, and turbulence is minimized when growing halfway down the length of an upstream patch in the main flow direction.

Flow deflection around the upstream patch is weakest when a partial V-shape is formed, suggesting that additional secondary patch growth can occur on the other side of the V. These patterns of patch alignment in formation resemble the formation adopted by migratory birds [START_REF] Portugal | Upwash exploitation and downwash avoidance by flap phasing in ibis formation flight[END_REF], or the drag-reducing queue formations in spiny lobsters [START_REF] Bill | Drag reduction by formation movement in spiny lobsters[END_REF]. This provides evidence of the role that bio-physical interactions have in shaping the way organisms position themselves spatially in landscapes, in both air-and water flow, across a range of scales.

Facilitative interactions within the landscape of a self-organized species

The positive and negative feedbacks underlying the formation of self-organized patterns have been identified for a wide range of ecosystems [START_REF] Rietkerk | Self-organization of vegetation in arid ecosystems[END_REF][START_REF] Van De Koppel | Scale-dependent feedback and regular spatial patterns in young mussel beds[END_REF][START_REF] Larsen | A delicate balance: ecohydrological feedbacks governing landscape morphology in a lotic peatland[END_REF]. At the scale of a single patch, it is well known that a positive feedback of reduced flow velocities within patches is linked to a negative feedback limiting lateral growth [START_REF] Bouma | Density-dependent linkage of scale-dependent feedbacks: A flume study on the intertidal macrophyte Spartina anglica[END_REF][START_REF] Schoelynck | Selforganised patchiness and scale-dependent bio-geomorphic feedbacks in aquatic river vegetation[END_REF]). However, while positive feedbacks are generally observed at a small scale within a patch [START_REF] Rietkerk | Regular pattern formation in real ecosystems[END_REF], knowledge of the larger-scale facilitation of seedling or fragment establishment by a self-organized species is limited. Our study provides a first indication of establishment mechanisms operating at this larger, between-patch scale. We show how an existing vegetation patch modifies flow velocities and resulting drag forces in its surroundings thereby leading to positive or negative effects on the occurrence of other patches, operating at a distance. Facilitative interactions within the same self-organized species, and over larger scales, might therefore be an important but overlooked process determining the evolution of spatial patterns over time.

The spacing of the vegetation patches resembles the organized spatial configurations observed in other organisms. For instance, migratory birds maximize the upward motion of air from the bird ahead and reduce drag due to air resistance [START_REF] Lissaman | Formation flight of birds[END_REF][START_REF] Weimerskirch | Energy saving in flight formation[END_REF][START_REF] Portugal | Upwash exploitation and downwash avoidance by flap phasing in ibis formation flight[END_REF], and fish schools adopt different spatial configurations that can lead to reduced energy expenditure [START_REF] Ashraf | Simple phalanx pattern leads to energy saving in cohesive fish schooling[END_REF]. Our temporal observations showed preferential patch occurrence at 0 to 60° angles from existing patches, with a peak around 30°. This angle is consistent with the 28° angle at which drag on the downstream patch was minimized in the field manipulation. However, the regions of minimum drag force did not strictly correspond to the most frequent location of patch occurrence. This discrepancy could be due to the low number of drag measurement points in that location, or to processes occurring during patch development (e.g. erosion of the upstream patch front and downstream displacement of patches (Sand-Jensen and Vindboek Madsen 1992), nutrient availability, etc.). The observed vegetation patch configurations might involve a balance between stress reduction and nutrient availability. For submerged aquatic plants, the position immediately in the wake of another patch could seem equally or even more beneficial in terms of drag reduction. However, the V position might be a hydrodynamic optimum to maximize drag reduction while still ensuring exposure to light and delivery of nutrients by water flow. Flume experiments on nitrogen uptake showed that ammonium uptake rates for Callitriche increased when the patch was located at a leading edge, where it was exposed to higher mean velocity (Cornacchia et al. 2018a). Instead, Callitriche had very low ammonium uptake rates when it was immediately downstream of another patch and exposed to low mean velocities. This finding suggests that partial, rather than complete, sheltering by established vegetation can allow more nutrients to be delivered to the downstream patch.

Similarly, in mussel beds, aggregation at high densities provides the advantage of protection from physical forces, but also increases competition for food (van de Koppel et al. 2005;[START_REF] De Paoli | Restoring mussel beds: A guide on how to survive on an intertidal mudflat[END_REF].

Therefore, the balance between reducing stress and maintaining resource availability might be an important factor influencing patch distributions in different self-organized systems. Further measurements of hydrodynamics and nutrient uptake, and/or numerical modelling studies are required to investigate the physical explanation for these patterns such as the V formation.

The consistency between the neighbouring patch distances observed for Callitriche platycarpa and Ranunculus penicillatus suggest that such V-shaped settlement might be typical for lotic aquatic environments. Thus, it might be a general process for submerged aquatic vegetation in running waters, at least for species with similar morphologies and experiencing comparable drag forces [START_REF] Bal | Trade-off between drag reduction and light interception of macrophytes: comparing five aquatic plants with contrasting morphology[END_REF]. However, vegetation distributions can be more complex than the streamlined, V-shaped patterns described here. Moderate flow velocities and uni-directional flows tend to create a streamlined patch distribution, whereas a near-homogeneous plant cover would emerge in streams with sustained periods of low flow velocities (Cornacchia et al. 2018b).

Moreover, a model accounting for interactions between neighbouring patches of emergent vegetation found that wake interactions and resulting deposition patterns influence secondary patch growth [START_REF] De Lima | Flow patterns around two neighboring patches of emergent vegetation and possible implications for deposition and vegetation growth[END_REF], yielding complex distributions and not necessarily recognizable Vshapes. More complex patterns in vegetation growth have also been observed in a stream with a rich abundance of aquatic plant species [START_REF] Cameron | Interactions between aquatic plants and turbulent flow: a field study using stereoscopic PIV[END_REF]. Plant traits could also influence the occurrence of recognizable V-shaped patterns. For instance, a V pattern might not be expected for species showing high resistance to hydrodynamic forces [START_REF] Puijalon | Plant resistance to mechanical stress: evidence of an avoidance-tolerance trade-off[END_REF], high root anchorage strength [START_REF] Schutten | Root anchorage and its significance for submerged plants in shallow lakes[END_REF][START_REF] Gurnell | The geomorphological context and impact of the linear emergent macrophyte, Sparganium erectum L.: a statistical analysis of observations from British rivers[END_REF][START_REF] Liffen | Profiling the below ground biomass of an emergent macrophyte using an adapted ingrowth core method[END_REF], or relying less on areas of low velocity and fine sediment deposition for their establishment and growth. Our observations were not able to provide evidence of this distribution pattern in other species, which were not as abundant in our field sites. Further studies are necessary to test if a clear dominant species is needed to achieve this configuration, and how the presence of other species might affect the patterns and spacing between patches.

The patches in our experiment were constructed on an array of 9408 holes per m 2 . As a nondimensional measure of canopy density [START_REF] Nepf | Flow and transport in regions with aquatic vegetation[END_REF], Callitriche patches have a frontal area per bed area ah = 0.200 ± 0.035 at the incoming flow velocity of 0.24 m s -1 (Cornacchia et al. 2018a).

This density value is similar to other studies. [START_REF] Bouma | Spatial flow and sedimentation patterns within patches of epibenthic structures: Combining field, flume and modelling experiments[END_REF] created patches with ah = 0.64. In [START_REF] Zong | Spatial distribution of deposition within a patch of vegetation[END_REF], ah ranged from 0.48 to 2.52. These values fall in the dense canopy regime described in [START_REF] Nepf | Flow and transport in regions with aquatic vegetation[END_REF], corresponding to ah > 0.1. Therefore, the hydrodynamic patterns presented in this study can generally be expected in other ecosystems with flexible submerged species under dense canopy conditions and presenting similar patch structure (i.e. overhanging canopies).

Initial patterns control future pattern formation: implications for ecosystem resilience

Our results on the role of patchiness on vegetation distribution suggest that initial vegetation patterns determine where future patches occur. This creates patterns at multiple spatial scales: a patch-patch scale during initial establishment, which over time leads to a pseudo-braided pattern in the organization of mature patches at the reach scale, with vegetated bands separated by unvegetated channels. These patterns likely develop on two different time scales. On the scale of generally 1 to 10 days, primary colonization by individual shoots relies on successful root development [START_REF] Barrat-Segretain | Comparative abilities of vegetative regeneration among aquatic plants growing in disturbed habitats[END_REF]; [START_REF] Barrat-Segretain | Regeneration and colonization of aquatic plant fragments in relation to the disturbance frequency of their habitats[END_REF]), which allows them to withstand scouring or dislodgement due to currents and drag (as in our field manipulation). After primary colonization, single shoots develop into patches through clonal growth over the course of months, based on our monitoring data and literature studies [START_REF] Cotton | The effects of seasonal changes to in-stream vegetation cover on patterns of flow and accumulation of sediment[END_REF][START_REF] Wharton | Macrophytes and suspension-feeding invertebrates modify flows and fine sediments in the Frome and Piddle catchments, Dorset (UK)[END_REF]. Therefore, the complex self-organized patterning of stream macrophytes likely results from processes interacting at different spatial and temporal scales.

Pattern formation at multiple scales, both spatial and temporal, has also been found to increase resilience in mussel beds which are another self-organized ecosystem [START_REF] Liu | Pattern formation at multiple spatial scales drives the resilience of mussel bed ecosystems[END_REF].

Similar to macrophytes, mussel aggregation into clumps improves their growth and offers protection against hydrodynamic forces (Van de Koppel et al. 2008). Thus, the presence of a few initial patches can facilitate the establishment of new patches. It might promote faster recovery following disturbance events such as floods by creating a self-reinforcing state that increases the resilience of lotic ecosystems. The sheltering effect presumably strengthens as the number of patches increases, eventually developing into near-full vegetation cover (cf. [START_REF] Van Der Wal | Spatial patterns, rates and mechanisms of saltmarsh cycles (Westerschelde, The Netherlands)[END_REF] for Spartina tussocks growing into a fully vegetated salt marsh). In regularly disturbed ecosystems, where the hydrologic regime and flow variability are among the primary factors controlling macrophyte establishment and development [START_REF] Riis | Hydrologic and hydraulic control of macrophyte establishment and performance in streams[END_REF], this process may be crucially important for vegetation recovery [START_REF] Barrat-Segretain | Comparative abilities of vegetative regeneration among aquatic plants growing in disturbed habitats[END_REF][START_REF] Barrat-Segretain | Regeneration and colonization of aquatic plant fragments in relation to the disturbance frequency of their habitats[END_REF][START_REF] Riis | Dispersal and colonisation of plants in lowland streams: success rates and bottlenecks[END_REF]. Our study suggests the general role of bio-physical interactions in shaping how organisms align themselves to hydrodynamic flows in different landscapes and across multiple spatial scales.

FiguresFigure 1

 1 Figures

Figure 2

 2 Figure 2 Overview of the ten patch configurations used in the field experiments, with indication of

Figure 3

 3 Figure 3 Relative flow velocity measurements (flow velocity relative to incoming flow) in between

Figure 4

 4 Figure 4 (A -B) Drag forces per unit surface area on single C. platycarpa individuals in different

Figure 5

 5 Figure 5 Drag forces on a single plant vs. a plant located in a vegetation patch, averaged over the

Figure 6

 6 Figure 6 Top: Planform representation of the distribution of in-stream macrophyte patches of

Table 1

 1 Regression results of linear and quadratic models including single (T, L) or multiple (T and L) predictor variables. Final selected models (in bold) are based on Akaike Information Criterion (AIC) values.

			Linear model	Quadratic model
					Predictor variables
			T * L	T	L	T * L	T	L
	Relative 8 between patches	R 2 p-value AIC	0.82 0.01 -17.64	0.79 0.0005 -19.96	0.00 0.84 -4.06	0.87 0.058 -16.99	0.81 0.002 -19.08	0.06 0.79 -2.67
	Relative 8 upstream of patch	R 2 p-value AIC	0.40 0.33 -6.22	0.24 0.15 -7.71	0.05 0.49 -5.59	0.71 0.26 -9.37	0.33 0.24 -7.05	0.28 0.31 -6.28
	"D"
	Relative 8 next to patch "U"	R 2 p-value AIC	0.41 0.329 -25.53	0.22 0.16 -26.77	0.00 0.99 -24.19	0.90 0.033 -40.09	0.25 0.36 -25.10	0.69 0.016 -33.95
	Relative 8	R 2	0.33	0.31	0.00	0.38	0.31	0.085
	next to	p-value	0.45	0.09	0.95	0.76	0.26	0.73
	patch "D"	AIC	-22.32	-26.05	-22.29	-19.15	-24.05	-21.18
	TKE	R 2	0.31	0.00	0.27	0.76	0.07	0.62
	upstream of patch "D"	p-value AIC	0.48 -80.09	0.99 -80.31	0.11 -83.53	0.18 -86.83	0.77 -79.04	0.03 -87.99

Table 2

 2 Changes in Ranunculus in-stream vegetation cover (%) and direction of growth of newly occurring vegetation patches with respect to the nearest existing vegetation patch (°), based on field observations in the Frome-Piddle catchment (UK), performed over three different time periods covering the annual growth cycle. Observations were of the dominant species Ranunculus penicillatus subsp. pseudofluitans.

			Dec. 2008 July 2009	Sept. 2009	Jan. 2010	July 2010
	Ranunculus cover (%)	13	22		7	22	30
	Angle to nearest
	vegetation patch	Dec. 08 -July 09	Sept. 09 -Jan. 10	Jan. 10 -July 10	Total
	(°)
	Downstream	0 -60 60 -120 120 -180	5 0 3			5 3 2	6 1 4	16 4 9
	Upstream	180 -240 240 -300 300 -360	1 1 1			0 0 0	5 0 1	6 1 2
	Total		11			10	17	38
	χ 2		9.20			12.80	10.88	24.34
	d.f.		5			5	5	5
	p-value	0.1			0.025	0.053	< 0.001

Acknowledgments

This work was supported by the Research Executive Agency, through the 7th Framework Programme of the European Union, Support for Training and Career Development of Researchers (Marie Curie -FP7-PEOPLE-2012-ITN), which funded the Initial Training Network (ITN) HYTECH 'Hydrodynamic Transport in Ecologically Critical Heterogeneous Interfaces', N.316546. Data collection in the Frome-Piddle catchment, Dorset, was supported by the Natural Environment Research Council (algorithm studentship awarded to Grieg Davies) and Queen Mary University of London (through a College studentship awarded to Bob Grabowski).


William Galland
email: galland.william@outlook.fr

Feth El Zahar Haichar

Sonia Czarnes

Celine Mathieu

Jean-Louis Demorge

Laurent Simon

Sara Puijalon

Florence Piola
email: piola@univ-lyon1.fr

Galland William

Biological inhibition of denitrification (BDI) in the field: effect on plant growth in two different soils

Keywords: Soil, denitrification, plant growth, soil texture and structure, lettuce

Intensive agriculture uses increasingly large amounts of nitrogen fertilizers to increase yields because nitrogen is one of the limiting factor of plant growth. Plants are in direct competition with denitrifying bacteria for nitrate, but biological denitrification inhibition (BDI) is a strategy developed by some plants in which procyanidins are produced that inhibit denitrification. This phenomenon increases the available nitrate in the soil.

Previous results showed that the addition of procyanidins to lettuce fields allowed effective BDI and increased soil nitrate and plant growth. However, agriculture is performed in different soils, and the action of procyanidins could depend on the type of soil. In this study, we tested the effect of procyanidin amendment on lettuce growth in two types of soils: loamy sand and sandy clay loam. Our results show that in both soils, the addition of procyanidins causes inhibition of denitrification, an increase in available nitrate, counterselection of denitrification communities and a gain in plant mass without modification of the soil structure. This study highlights a sustainable agricultural method effective in a variety of soils.

INTRODUCTION

In Europe, agriculture has expanded significantly over the past fifty years, following the development of phytosanitary products [START_REF] Tilman | Agricultural sustainability and intensive production practices[END_REF] and especially nitrogen (N) fertilizers, allowing an enhance in agricultural yields [START_REF] Casagrande | Fertilisation azotée minérale: assagissementa la fin des années 80[END_REF] in different soils with variable nitrate and ammonium concentrations. N depletion in soils is partly due to increasingly intense agricultural activity, where many successive crops consume the N initially present in the soil, without giving the ecosystem time to renew itself [START_REF] Mulvaney | Synthetic nitrogen fertilizers deplete soil nitrogen: a global dilemma for sustainable cereal production[END_REF]. These practices therefore deprive plants and crops of N: the most important but above all the most limiting element for growth [START_REF] Morot-Gaudry | Assimilation de l'azote chez les plantes: aspects physiologique, biochimique et moléculaire[END_REF], which leads farmers to use increasing amounts of N fertilizers [START_REF] Tilman | Agricultural sustainability and intensive production practices[END_REF]. These N fertilizers are used for intensive agriculture but are also transferred from the ecosystem or used by soil microorganisms [START_REF] Kaye | Competition for nitrogen between plants and soil microorganisms[END_REF]. Indeed, N in European soils is not entirely consumed by plants and crops but is also subjected to denitrification, with 59% lost as the greenhouse gas N 2 O; leached into soils, representing a loss of 20%; and volatilized into NH 3 , representing a loss of up to 21% [START_REF] Oenema | Integrated assessment of promising measures to decrease nitrogen losses from agriculture in EU-27[END_REF]. Ecological awareness led to the adoption in 1991 of a directive by the European Council to regulate the quantities of N added to the soil (1991:

Directive 91/676/EEC; hereafter referred to as NiD). The main purpose of this nitrate directive was to reduce the risk of N leaching, but this does not reduce denitrification losses due to denitrifying bacteria in the soil. Indeed, denitrification by microorganisms i.e. fungi [START_REF] Philippot | Denitrifying genes in bacterial and archaeal genomes[END_REF], archaea [START_REF] Shoun | Denitrification by fungi[END_REF] and bacteria [START_REF] Lecomte | Diversifying anaerobic respiration strategies to compete in the rhizosphere[END_REF] transforms nitrate into N2O a greenhouse gas representing a significant loss for the ecosystem [START_REF] Mosier | Nitrous oxide emissions from agricultural fields: Assessment, measurement and mitigation[END_REF] and up to N2 for some bacteria [START_REF] Kuypers | The microbial nitrogen-cycling network[END_REF]. However, [START_REF] Bardon | Evidence for biological denitrification inhibition (BDI) by plant secondary metabolites[END_REF] describes a phenomenon involving an invasive plant (Fallopia spp), which is able to inhibit denitrifying bacteria in the soil via exudation at the root level of a flavonoid tannin called procyanidin (Bardon et al., 2016a) and therefore reduce N losses by denitrification. This phenomenon, called biological denitrification inhibition (BDI), therefore reduces the activity and abundance of denitrifying bacteria and increases the nitrate pool in the soil, which can then be a source of N other than fertilizers for crops (Bardon et al., 2016b). Indeed, in [START_REF] Galland | Biological denitrification inhibition (BDI) in the field: A strategy to improve plant nutrition and growth[END_REF], it was demonstrated that in sandy clay loam-textured soil, the addition of procyanidins to the field induced BDI, decreased the abundance of denitrifying communities and allowed nitrate conservation in the soil, which was then used for lettuce farming to increase lettuce growth. These crops, as well as BDI and denitrification, could be soil dependent. Indeed, in France, there is a great diversity of soils [START_REF] Jamagne | Grands paysages pédologiques de France[END_REF], which differ from each other based on structure, i.e., the spatial arrangement of soil components [START_REF] Rabot | Soil structure as an indicator of soil functions: a review[END_REF]; texture, i.e., the granulometric distribution of soil mineral constituents [START_REF] Batey | Soil compaction: identification directly in the field[END_REF]; and the bacterial community [START_REF] Nannipieri | Microbial diversity and soil functions[END_REF][START_REF] Fierer | The diversity and biogeography of soil bacterial communities[END_REF][START_REF] Schreiter | Effect of the soil type on the microbiome in the rhizosphere of fieldgrown lettuce[END_REF]. These differences in soils play a role in the quality of crops but also in denitrifying bacterial communities. These bacteria may differ according to the soil and not have the same diversity and/or abundance, which may then change the use of N in the soil and its future in the soils [START_REF] Cavigelli | The functional significance of denitrifier community composition in a terrestrial ecosystem[END_REF]. In addition, the distribution of porosities based on soil structure can change the water content and oxygen availability [START_REF] Gliński | Microbial ecology of soil porous medium[END_REF], which play a role in denitrification, which is an anaerobic process [START_REF] Kraft | Microbial nitrate respiration-genes, enzymes and environmental distribution[END_REF]. Thus, differences in soil based on texture, structure and bacterial communities, among other parameters, can modify denitrification and the effect of procyanidins on denitrification activity, which, similar to other organic molecules, exhibit variable behaviours and affinities depending on the soil with which they are in contact [START_REF] Lützow | Stabilization of organic matter in temperate soils: mechanisms and their relevance under different soil conditions-a review[END_REF]. In this study, we aimed to test the effect of two different soils that theoretically do not have the same texture, structure and bacterial community on the action of procyanidins and consequently on BDI and traits related to lettuce growth. The assumption is that procyanidin amendment of any soil can induce BDI, which allows an increase in nitrate in the soil and thus an increase in the traits of lettuce. To test these hypotheses, two fields were used: one at the SERAIL Experimental Station (Brindas, 69126 Rhône, France), with a sandy clay loam soil texture, and an agricultural field in Manziat (01570 Ain, France), where the soil has a loamy sand texture. During the summer of 2018, the same variety of Batavia lettuce was planted in both fields in parallel, and the planted and unplanted soils were amended with procyanidins at three concentrations (0, 87 and 210 kg ha -1 ). Soil denitrification enzyme activity (DEA), soil nitrate concentration, shoot and root morphological traits (fresh masses of aerial and root parts, biomechanical characteristics of leaves and the N content of tissues), the abundance of total bacteria and the denitrifying community, and the porosities of the soils used were measured in lettuce and soil with or without procyanidin amendment.

MATERIALS AND METHODS

Plant growth and experimental design

Lettuce (Lactuca sativa var Loubresac, Earl LIMOUSIN) was grown in two fields at the same time in July 2018 following a Fisher system with 4 plots per treatment [START_REF] Preece | RA Fisher and experimental design: a review[END_REF]; the fields were located in an agricultural field in Manziat (01570 Ain, France) (46°22' 2.28 "N, 4°54' 3.671 "E) with loamy sand soil (sand: 82.5%, silt: 8.9% and clay: 8.5%; pH : 7.2; cation exchange capacity (CEC): 60 meq kg -1 ; organic carbon: 9.9 g kg -1 ) and at the SERAIL Experimental Station (Brindas, 69126 Rhône, France) (45°43'46.4 "N, 4°43'37.1 "E) with a sandy clay loam soil (sand: 68.7%, silt: 21.9% and clay: 9.5%; pH : 7.1; CEC: 58 meq kg -1 ; organic carbon: 6.9 g kg -1 ). In both fields, the experimental design was the same: lettuce was planted in 4 parallel rows of 20 lettuces in 6 m x 1.4 m plots (8.4 m 2 ), with an unplanted area of 2 m x 1.4 m (2.8 m 2 ) for measuring the corresponding characteristics of soil without plants.

For soils with or without lettuce, 3 treatments were applied: unamended without procyanidins and amended with procyanidins at the two concentrations found to be most effective in [START_REF] Galland | Biological denitrification inhibition (BDI) in the field: A strategy to improve plant nutrition and growth[END_REF]: 87 kg ha -1 and 210 kg ha -1 . The two experiments were watered the first week after planting with 3 mm of water every day. For the next 10 days, 8 mm of water was applied per day. From then until the end of the experiment, 12 mm of water was applied every two days. Procyanidins were added 2 weeks after planting (stage with 7-9 leaves) to soil whose nitrate had been brought to the ZENIT grid standard, i.e., 40 kg NO 3 -ha -1 [START_REF] Despujols | Control of nitrate level in autumn greenhouse lettuce[END_REF]. Commercial procyanidins (Laffort TANIN VR GRAPE ®112, Bordeaux, France)

were applied in aqueous solution (standard water) by 2 nozzle spray booms to provide 500 L ha -1 or 0.42 L per plot, between the rows of lettuce, and the soil was then hoed. Each site was binned and slightly watered (with 8 mm) just after the addition of procyanidins.

Denitrification Enzyme Activity (DEA)

Briefly, as described by [START_REF] Galland | Biological denitrification inhibition (BDI) in the field: A strategy to improve plant nutrition and growth[END_REF], DEA was measured for both fields from 5 g dry equivalent of pooled root-adhering soil (RAS) retrieved from 4 lettuces per plot and 4 samples of bulk soil from unplanted plots with or without amendment, the day of the final harvest. BDI (%) was measured by calculating the percentage of denitrification activity inhibition recorded by DEA compared to the corresponding unamended control.

Quantification of total bacterial and denitrifier abundance

Total DNA was extracted from 0.5 g of RAS from three treatments (unplanted soil, soil with lettuce, and soil with lettuce amended with only the higher concentration of 210 kg of procyanidins per hectare) in triplicate according to the manufacturer's protocol with a Fast DNA Spin Kit for Soil (MP Biomedical, Solon, OH, USA). The amount of DNA extracted was then estimated using a Quant-iT PicoGreen® dsDNA Assay kit (Molecular Probes, USA). Total bacterial and denitrifier abundances were quantified by qPCR using primers targeting the 16S rRNA and nirK/nirS genes, respectively, as described previously by [START_REF] Galland | Biological denitrification inhibition (BDI) in the field: A strategy to improve plant nutrition and growth[END_REF].

Nitrate concentrations in soil

Briefly, NO 3 -was extracted one week before procyanidin application (T0) from the planted rhizospheric soils (20 cm from the base of 4 lettuces per plot and pooled) and on the day of harvest (TF) from the RAS soils and from the unplanted soils for both fields. Nitrate was extracted from 5 g eq. of dried soil according to [START_REF] Galland | Biological denitrification inhibition (BDI) in the field: A strategy to improve plant nutrition and growth[END_REF].

Measurement of lettuce mass

After 5 weeks of growth in the Manziat field and 6 weeks of growth in the SERAIL field, 12 lettuces per plot or 48 lettuces per treatment were harvested and weighed to determine the fresh mass of the aerial parts. Among these 12 lettuces, 4 root systems were harvested (or 16 per treatment) to determine the mass of the root parts. Each fresh lettuce was weighed on a balance (± 0.5 g). The root system was washed with distilled water and weighed with a precision balance (± 0.001 g), dried at 68°C for 24 h and weighed again on the same balance in order to determine dry mass.

Leaf mechanical properties

One piece of tissue was cut from each leaf (4 leaves per plot for a total of 16 leaves per treatment in each field) for biomechanical measurements. Specific leaf toughness was measured in accordance with [START_REF] Galland | Biological denitrification inhibition (BDI) in the field: A strategy to improve plant nutrition and growth[END_REF].

Plant N content

As described in [START_REF] Galland | Biological denitrification inhibition (BDI) in the field: A strategy to improve plant nutrition and growth[END_REF], the total N concentration was measured using an elemental analyser (FlashEA 1112, Thermo Scientific, Waltham, USA) from 4 leaves and 4 root systems per plot (16 per treatment in each field) using 2 mg of ground root or leaf. The leaf and/or root N contents was expressed in percentage of N in the leaf and/or root dry mass.

Soil porosity measurement

For each treatment, to determine volumetric soil water moisture after capillary rise and bulk density, four undisturbed soil samples were collected using a stainless steel cylinder of 100 cm 3 (5.6 cm diameter, 4.05 cm height) with bevelled edges to ease insertion from unplanted soil or rhizospheric soil. The core samples were capped at both ends with two plastic lids to minimize soil and evaporative loss until analysis. After removing the two plastic lids, the core samples were placed on a geotextile. This geotextile had the ability to let water but not soil particles pass through. The geotextile was placed on a PVC rigid support with large mesh.

The geotextile was 3 cm from the bottom of large plastic bowls. Water was added to the plastic bowls until the level of water obtained was 2 mm higher than the bottom of the base of the core samples. The bowls were closed to prevent evaporation during the time of the experiment (approximately 34 h), and volumetric soil moisture after capillary rise and bulk density were then determined in the 100 cm 3 cylindrical soil cores (V) by successive weighing of the wet and 105°C-oven-dried soil cores. The volumetric soil water content after water capillary rise represents the water retained in the aggregates by capillary forces and the 'immobile' water, which moves slowly through the network of micropores [START_REF] Chen | Two-domain estimation of hydraulic properties in macropore soils[END_REF] and fills capillary pores occurring within soil aggregates. The micropores between particles and microaggregates belonging to the elementary fabric units are referred to as capillary porosity in this paper. Capillary porosity, expressed in cm 3 cm -3 , was estimated by subtracting the 105 °C-oven-dried soil weight from the wet soil weight and normalizing the difference to the 105 °C-oven-dried soil weight and the volume of the cylindrical soil cores (V) thereafter.

The bulk density of each soil core was determined as the ratio between the total 105 °C-ovendried soil weight and the soil cylinder volume V. The total porosity was calculated from the bulk density and solid density thereafter (assuming that the solid density was 2.65 g cm -3 ).

Macropores between the units of fabric, referred to as macroporosity and expressed in cm 3 .cm -3 , represent the rapid water transport and aeration of the soil. Macroporosity was calculated as the difference between total porosity and capillary porosity.

Data and statistical analyses

The difference in lettuce morphological traits (n > 48) between treatments was determined using analysis of variance (ANOVA) followed by a post hoc (Tukey's HSD) test. Similarly, the normality (Shapiro test) and homoscedasticity of the variance (Fischer test) of all the variables were tested. The significance of microbiological traits, nitrate concentration, soil measurement and N level in plant (n > 3) between treatments was tested non-parametrically with a Kruskal-Wallis test followed by a post hoc Nemenyi test. The same statistical tests were used to measure the differences between equivalent treatments and between the two fields, and the plot effect was tested and discarded for all traits (two-way ANOVA and mixed model). All the analyses were performed using R project software (v. 3.5.0).

RESULTS

Biological denitrification inhibition

As shown in Figure 1, in soil from the Manziat field with 87 kg ha -1 procyanidin amendment, a BDI of approximately 31% (p-value: 0.014) was observed compared to the unplanted soil without procyanidin addition. However, no significant BDI was observed in response to the 210 kg ha -1 procyanidin amendment. In the soil planted with lettuce, no significant BDI with the 87 kg ha -1 procyanidin amendment compared to the planted soil without procyanidin amendment was observed, whereas BDI (p-value: 0.03) of approximately 31% was observed for the highest concentration (210 kg ha -1 ). In the unplanted soil in the SERAIL field, there was BDI in the plots amended with 87 and 210 kg ha -1 procyanidins of 24% and 32%, respectively (p-value: 0.048), compared with the unamended soil. In addition, in planted soils, there was BDI of 27% (p-value: 0.047) relative to unamended planted soil for the 87 kg ha -1 procyanidin-amended lettuce and soils and BDI of 33% (p-value: 0.04) for the 210 kg ha -1 procyanidin-amended lettuce and plots. When comparing both fields, we noticed that in the unplanted and planted soil, BDI was induced for each tested concentration and was more important at the highest concentration, except for the BDI observed in unplanted and amended soil with procyanidin addition of 87 kg ha -1 , where the BDI was larger and different from than in planted soil planted with the same procyanidin concentration.

Abundance of total and denitrifying bacterial communities

In the Manziat and SERAIL fields, the total bacterial communities measured by the 16S rRNA gene (Fig. 2A) did not differ statistically between treatments, although there was a tendency at the SERAIL field for the total bacterial abundance to be reduced in the presence of lettuce plants. In the Manziat field, the abundance of the nirS gene (Fig. 2B) was identical in the unamended soil and in the RAS of unamended lettuce and amended lettuce at 210 kg ha -1 procyanidins. However, the abundance of the nirS gene was lower in lettuce amended with 210 kg ha -1 procyanidins than in unamended lettuce. In the SERAIL field (Fig. 2B), there were generally fewer bacteria harbouring the nirS gene than in the Manziat field, although the abundance of the community with the nirS gene in the RAS soil of unamended lettuces was identical to that in the unamended and planted soil. The abundance of nirS genes was higher in the unamended soil than in the RAS of lettuce amended with procyanidins at 210 kg ha -1 (p-value: 0.018). In Manziat, the abundance of bacteria harbouring the nirK gene (Fig. 2C) was identical between unplanted soil and unamended planted soil but lower in planted soils amended with procyanidins (p-value: 0.013). At SERAIL, the abundance of the nirK gene (Fig. 2C) was higher in unplanted soil (p-value: 0.0229) than in planted soil with or without procyanidins. The amendment of procyanidins slightly reduced the abundance of bacteria in the RAS of lettuce but not significantly compared to the RAS of unamended lettuce.

Effect of procyanidin addition to soil on nitrate concentrations

In the Manziat field on date T0 (Fig. 3A), nitrate concentrations were equivalent for unplanted soils and similar for planted soils. In addition, the nitrate concentrations in planted soils were significantly lower than those in unplanted soils. On the TF date, overall, the nitrate concentrations of the planted soils were significantly lower than those of the unplanted soils.

However, at 87 kg ha -1 , the nitrate concentration in unplanted soil was increased by 113 % (pvalue: 0.05) compared to that in unplanted and unamended soil. Moreover, the nitrate concentration was not significantly different (59 % higher in unplanted and amended soil at 210 kg ha -1 ). In all treatments, there was a decrease in the nitrate concentration between T0

and TF, except for soils unplanted and amended with 87 or 210 kg ha -1 procyanidins. In the SERAIL field (Fig. 3B), the nitrate concentrations at T0 were identical between planted soils, but not in the unplanted soil without amendment, in which the concentration was lower (pvalue: 0.041). In addition, there was no difference in the nitrate concentration in unplanted soils regardless of the concentration at T0. At TF, the nitrate concentrations in planted soils were identical, regardless of the concentration, and significantly lower than those in unplanted soils. In unplanted soils, the nitrate concentration of the soil amended with 87 kg ha -1 procyanidins was higher than the concentration of the unplanted soil amended with 210 kg ha - 1 procyanidins (p-value: 0.047) and 142 % higher than that in the unplanted and unamended soil (p-value: 0.046). Similarly, the nitrate concentration of the soil amended with procyanidins at 210 kg ha -1 was higher (by approximately 57 %) than that of untreated soil (pvalue: 0.049). It should be noted that between T0 and TF, all nitrate concentrations decreased except for that in the unplanted and unamended soil and the unplanted soil with amendment at 87 kg ha -1 .

Effect of procyanidin addition on lettuce traits

In Manziat (Fig. 4A), the addition of 87 kg ha -1 and 210 kg ha -1 procyanidins increased the fresh mass of the aerial parts of lettuce by 46% (p-value: 0.00012) and 33% (p-value: 0.025), respectively, compared to unamended lettuce. Similarly, at SERAIL (Fig. 4A), compared to the fresh mass of unamended lettuce, that of lettuce with the addition of procyanidins increased by 16% (p-value: 0.092) with 87 kg ha -1 and 25% (p-value: 0.00053) with 210 kg ha -1 . In Manziat (Fig. 4B), amendment with procyanidins at 87 kg ha -1 allowed a increase (pvalue: 0.0000026) in the fresh mass (approximately 73%) of roots compared to no amendment. At SERAIL (Fig. 4B), amendment with 87 kg ha -1 procyanidins allowed an increase (p-value: 0.15) in the root fresh mass (approximately 22%), and amendment with 210 kg ha -1 procyanidins allowed a increase (p-value: 0.017) in the fresh mass (approximately 28%) of roots compared to no amendment. Moreover, the specific toughness (J.m -3 ) of the three leaves of the 4th crown did not differ between treated and untreated lettuces in either field (Fig. 5). However, overall, the specific thoughness of the leaves of the 4th crown in Manziat was higher than that at SERAIL.

Nitrogen concentration in plants

In Manziat and at SERAIL (Fig. 6A), the N content in the leaves of amended lettuce was the same, regardless of whether they were amended. However, the N content decrease from 2.1 to 1.8 % of N with the amendment concentration. Based on the gains in fresh mass of the aerial parts of the lettuces, we can deduce that there was, on average, 1.46 g more N per lettuce for the treatment with 87 kg ha -1 procyanidins and 0.63 g more N for the treatment with 210 kg ha -1 procyanidins than in unamended lettuces. Similarly, in the SERAIL field, there was, on average, 0.94 g more N per lettuce with 87 kg ha -1 procyanidins and 0.56 g with 210 kg ha -1 procyanidins than in unamended lettuces. In Manziat (Fig. 6B), the N content in lettuce roots between treatments was the same. At SERAIL, although not significantly different, the N concentrations seemed lower when lettuce was amended with procyanidins.

Effect of procyanidins addition on soil porosities

In Manziat, procyanidin amendment of planted and unplanted soils did not significantly change the total porosity (Fig. 7A) or the capillary porosity (Fig. 7C). However, the macroporosity (Fig. 7E) of the planted soil amended with procyanidins at 87 kg ha -1 was lower than the macroporosity of the unamended planted soil (p-value: 0.0083572), and

although not significant, it was also lower in the planted soil amended with 210 kg ha -1 procyanidins. At SERAIL, procyanidin amendment of planted and unplanted soils did not change the total porosity (Fig. 7B), capillary porosity (Fig. 7D) or macroporosity (Fig. 7F).

DISCUSSION

The addition of procyanidins induces BDI in soils of both textures

As demonstrated in [START_REF] Galland | Biological denitrification inhibition (BDI) in the field: A strategy to improve plant nutrition and growth[END_REF], the addition of procyanidins to lettuce fields reduced denitrification activity. This reduction was observed for both soil textures. In the SERAIL field with a sandy clay loam-textured soil (the same soil as used in [START_REF] Galland | Biological denitrification inhibition (BDI) in the field: A strategy to improve plant nutrition and growth[END_REF]), the addition of procyanidins induced BDI from one year to the next, on the same orders of magnitude (between 16 and 32%, depending on the procyanidin concentrations in the soil). In addition, the results presented here showed that denitrification activity was also inhibited by the addition of procyanidins to the loamy sand soil of Manziat, and the inhibition percentages in the planted soils were the same between the two fields used in the experiment. Each plant selects its antagonistic microorganisms, as described by [START_REF] Berg | Plant species and soil type cooperatively shape the structure and function of microbial communities in the rhizosphere[END_REF], which would explain in our case the decrease in the abundance of the total bacterial community in the RAS of lettuce with or without procyanidins in the SERAIL field, although as shown by [START_REF] Buyer | Soil and plant effects on microbial community structure[END_REF], plants such as soybean and corn increase the total community. This phenomenon was not observed in [START_REF] Galland | Biological denitrification inhibition (BDI) in the field: A strategy to improve plant nutrition and growth[END_REF] because, as [START_REF] Dandie | Changes in bacterial denitrifier community abundance over time in an agricultural field and their relationship with denitrification activity[END_REF] shows, bacterial communities in arable soil are likely to change from one year to the next.

However, the abundance of the total bacterial community did not differ between the RAS of lettuce amended or unamended with procyanidins for either soil texture, which indicates that the addition of procyanidins did not have an antimicrobial effect on the soil microfauna, as

shown by [START_REF] Lacombe | The antimicrobial properties of the lowbush blueberry (Vaccinium angustifolium) fractional components against foodborne pathogens and the conservation of probiotic Lactobacillus rhamnosus[END_REF], in which a procyanidin concentration much higher than that used here had antimicrobial effects on some bacterial species. However, procyanidins act on the abundance of denitrifying bacterial communities. As described by Wallenstein et al. (2006), denitrifying bacterial communities have either copper-coupled nitrate reductase (encoded by nirK) and the other with cytochrome cd1 (encoded by nirS), which is why we targeted these two genes to measure denitrifier abundance. Thus, at a procyanidin concentration of 210 kg ha -1 , whether in sandy clay loam or loamy sand, denitrifying communities with the nirK gene and the nirS gene were less abundant in procyanidinamended soil than in unamended soil, identical to the result in [START_REF] Galland | Biological denitrification inhibition (BDI) in the field: A strategy to improve plant nutrition and growth[END_REF], despite the fact that denitrifying communities can change from one year to the next, as Yoshida et al.

( 2009) showed. This leads to the hypothesis that the loss of the denitrifying function of bacteria via the BDI phenomenon would cause a lack of competitiveness and would thus be counter-selected from the rhizosphere of amended lettuce. Denitrifying bacteria could no longer use nitrate as an electron acceptor, which would reduce their multiplication and persistence in the ecological niche of the rhizosphere, as observed in [START_REF] Dassonville | Niche construction by the invasive Asian knotweeds (species complex Fallopia): impact on activity, abundance and community structure of denitrifiers and nitrifiers[END_REF].

We also observed that the abundances were not the same between the two soil textures; there were more bacteria in the loamy sand soil of Manziat with the nirS gene and fewer with the nirK gene than at the SERAIL, as [START_REF] Rosa | The influence of soil properties on denitrifying bacterial communities and denitrification potential in no-till production farms under contrasting management in the Argentinean Pampas[END_REF] showed, indicating that the distribution of denitrifier diversity is not the same among soils.

The addition of procyanidins induces nitrate conservation and an increase in

lettuce morphological traits for both soil textures [START_REF] Bardon | Biological denitrification inhibition (BDI) with procyanidins induces modification of root traits, growth and N status in Fallopia x bohemica[END_REF] showed in mesocosms that in a soil with a sandy clay loam texture, procyanidin-induced BDI allows nitrate conservation in the soil of up to 6 times compared to that in the same soil that has not been amended with procyanidins. In our experiment, there were similar nitrate conservations in both soils at both concentrations, which were homogeneous between the two soils. This conservation after BDI allowed the lettuces to grow better in the amended soils, as observed in the previous year with another variety of lettuce. In our case, after adding procyanidins, we observed that in the planted soils in the two fields, lettuce consumed the nitrate present in the soil between the beginning and the end of the experiment, as [START_REF] Jackson | Crop nitrogen utilization and soil nitrate loss in a lettuce field[END_REF] observed in lettuces that use nitrate as the preferred source of N during growth. In addition, in the unplanted soils of the two fields, there was a loss of nitrate between the first measurement at the beginning of the experiment and the second measurement taken at harvesting. Such loss over time is due to N losses in the system such as leaching [START_REF] Di | Nitrate leaching in temperate agroecosystems: sources, factors and mitigating strategies[END_REF], denitrification [START_REF] Kuypers | The microbial nitrogen-cycling network[END_REF], but this loss was less significant when soils were amended with procyanidins, as expected. The protocol tried to limit these losses by applying procyanidins to the increased N requirements of lettuce [START_REF] Despujols | Control of nitrate level in autumn greenhouse lettuce[END_REF], knowing that the nitrate made available as a result of BDI is rapidly assimilated by the plant (Bardon et al., 2018;[START_REF] Galland | Biological denitrification inhibition (BDI) in the field: A strategy to improve plant nutrition and growth[END_REF]. In these two soils, although lettuce yield varies depending on soil texture [START_REF] Costigan | The effects of soil type on the early growth of lettuce[END_REF], the supply of procyanidins induced BDI, which allowed an increase in nitrate in the soil and induced a gain in lettuce mass in the amended plots. As in [START_REF] Galland | Biological denitrification inhibition (BDI) in the field: A strategy to improve plant nutrition and growth[END_REF], there was a greater root mass gain than aerial mass gain for lettuce roots in Manziat. Indeed, these traits exhibited a 78% increase in response to procyanidin amendment at 87 kg ha -1 when the aerial parts increased by 46%, whereas the previous study [START_REF] Galland | Biological denitrification inhibition (BDI) in the field: A strategy to improve plant nutrition and growth[END_REF]) discriminated against the direct action of procyanidins on the roots, and this effect was assumed to be due solely to the BDI phenomenon. It can therefore be deduced that procyanidin amendment at 87 kg ha -1 is sufficiently effective in loamy sand soil, while a higher concentration (such as 210 kg ha -1 ) is more effective in sandy clay loam soil. It was also observed that the percentages of N in tissues did not differ between amended and unamended lettuce for either soil texture, meaning that there was no plant physiological change due to the procyanidin amendment allowing better N absorption by the lettuce. However, as lettuce grew better in plots amended with procyanidins in both fields, the higher the mass, the higher the N concentration. Indeed, the procyanidin treatment made it possible to conserve N in the form of nitrate due to BDI and thus to make more nitrate available for lettuce, allowing better growth without modifying the plants' ability to absorb N. This observation is consistent with the finding of a greenhouse study conducted on several lettuce varieties where N use efficiency was not affected by soil nitrate concentrations [START_REF] Urlić | Effect of NO3 and NH4 concentrations in nutrient solution on yield and nitrate concentration in seasonally grown leaf lettuce[END_REF]. Similarly, although the specific toughness of lettuce leaves was higher in Manziat, which was probably due to different growing conditions and the fact that they were smaller in this soil, amending lettuce with procyanidins did not change the quality of the leaves. Thus, treatment with procyanidins does not change the vulnerability of leaves to potential herbivores and pests [START_REF] Clissold | Gross vs. net income: how plant toughness affects performance of an insect herbivore[END_REF][START_REF] Onoda | Global patterns of leaf mechanical properties[END_REF] and does not lead to a gustatory quality difference detected by consumers for lettuce potentially placed on the market [START_REF] Lopez-Galvez | Quality changes in packaged salad products during storage[END_REF][START_REF] Rico | Extending and measuring the quality of fresh-cut fruit and vegetables: a review[END_REF].

The addition of procyanidins did not induce a change in soil structure

The measurement of soil porosity was carried out because soil structure plays a role in denitrification [START_REF] Laudone | A model to predict the effects of soil structure on denitrification and N2O emission[END_REF]. In fact, the porosity of a soil is linked to soil aeration and therefore to anaerobic conditions that are favourable for denitrification [START_REF] Smith | Anaerobic zones and denitrification in soil: modelling and measurement[END_REF].

Moreover, denitrifiers are more abundant in aggregates than in pores [START_REF] Lecomte | Diversifying anaerobic respiration strategies to compete in the rhizosphere[END_REF].

Therefore, a change in porosity between our two soils may have played a role in the denitrification activity and consequently the inhibition of it by BDI. However, since two soils with different textures necessarily do not have the same structure [START_REF] Bouma | Influence of soil macroporosity on environmental quality[END_REF], it is normal for the total porosity to be slightly lower in sandy clay loam soil than in loamy sand soil.

Despite this, there was no difference in the efficiency of BDI, nitrate availability or the efficiency of lettuce cultivation, suggesting that the BDI process is independent of soil structure. Other abiotic factors such as pH, organic matter level may play a role in the denitrification capacity of denitrifying bacteria (Zumft, 1997) but these factors have not changed after the application of procyanidins. In addition, the initial N level may have an effect on denitrification [START_REF] Kuypers | The microbial nitrogen-cycling network[END_REF], in our case both soils have been set at an equivalent starting N level, which excludes at most an effect by this factor. However, we observed a decrease in the macroporosity of planted soils amended with 87 kg of procyanidins per hectare, potentially due to the significant root growth under this condition. In addition, as Hamblin (1986) explains, roots can, by growing, compact the soil and thus reduce macroporosity.

CONCLUSION

As in our previous study, the use of procyanidin amendment allowed biological inhibition of denitrification as well as a decrease in the competitiveness of denitrifiers in sandy clay loamtextured soil but also in loamy sand-textured soil. This BDI induced the conservation of nitrate in unplanted soils but allowed amended lettuce to grow better in planted soils.

Although the amendment at the lowest dose tested was most effective in loamy sand soil, the addition of procyanidins to the field did not change leaf quality nor N levels in tissues in either soil. Finally, soil porosities differed only slightly between treatments for both soils, which means that regardless of soil texture or structure, the induction of BDI in fields is applicable in two soil types and repeatable from one year to the next with another variety of lettuce.

Soil Plant Sci.

Figure 1 :

 1 Figure legends:

Figure 2 :

 2 Figure 2: Effects of procyanidins applied to the Manziat and SERAIL fields (210 kg of

Figure 3 :

 3 Figure 3: Effects of different concentrations of procyanidins applied to the field (0, 87 and

Figure 4 :

 4 Figure 4: Effects of different concentrations of procyanidins applied to soil planted with

Figure 5 :

 5 Figure 5: Effects of different concentrations of procyanidins applied to soil planted with

Figure 6 :

 6 Figure 6: Effects of different concentrations of procyanidins applied to soil planted with

Figure 7 :

 7 Figure 7: Effects of different concentrations of procyanidins applied to unplanted soil and soil

  Figure1

  Figure 4

  67, 748-757.

	Wallenstein, M.D., Myrold, D.D., Firestone, M., Voytek, M., 2006. Environmental controls
	on denitrifying communities and denitrification rates: insights from molecular
	methods. Ecol. Appl. 16, 2143-2152.
	Yoshida, M., Ishii, S., Otsuka, S., Senoo, K., 2009. Temporal shifts in diversity and quantity
	of nirS and nirK in a rice paddy field soil. Soil Biol. Biochem. 41, 2044-2051.
	Zumft, W.G., 1997. Cell biology and molecular basis of denitrification. Microbiol Mol Biol
	Rev 61, 533-616.

Acknowledgements

This work was supported by the Auvergne-Rhône-Alpes region (ARC 2016(ARC -2019) ) for thesis subvention and the French National Research Agency (ANR-18-CE32-0005, DIORE).

Quantitative PCR was performed on the DTAMB platform (FR BioEnvis, University Lyon 1).

Field experiments were performed at the SERAIL station. Microbial activities were measured on the AME platform (UMR 5557), and C and N content were measured on the Isotope Ecology platform (UMR 5023). We thank Laurent Philippot and Delphine Moreau for scientific discussions.