Laurène Perthame

Nathalie Colbach

Hugues Busset

Annick Matejicek

Delphine Moreau
email: delphine.moreau@inrae.fr

Morphological response of weed and

Keywords: Morphology, plasticity, specific leaf area, leaf biomass ratio, height biomass ratio, competition, light

Introduction

Weeds are the most harmful pest in arable fields [START_REF] Oerke | Crop losses to pests[END_REF], because they compete with the crops for resources (light, nutrients, water). Herbicides are the most effective curative weed management technique, but their use needs to be reduced because of the harm it may do to human and environmental health (Waggoner et al., 2013, Haarstad and[START_REF] Haarstad | Ten Years of Pesticide Monitoring in Norwegian Ground Water[END_REF].

Furthermore, frequent usage of herbicide can lead to increased herbicide resistance and thus to technical lock-ins [START_REF] Davis | Are herbicides a once in a century method of weed control?[END_REF]. Reducing herbicide use may result in an altered residual weed flora, thus increasing competition between weeds and crops. Choosing crop species/varieties that are competitive for resources might be an option for managing weeds while reducing herbicide use.

In intensive temperate cropping systems, light is generally the main resource for which plants compete [START_REF] Wilson | Plant competition and resource availability in response to disturbance and fertilization[END_REF][START_REF] Perry | Founder control and coexistence in a simple model of asymmetric competition for light[END_REF]. However, reducing mineral fertilizers to decrease their environmental impacts [START_REF] Sutton | Too much of a good thing[END_REF] may limit soil-nitrogen availability, and result in periods of nitrogen stress for plants. Thus, it is crucial to identify crop plants that are competitive for both light and nitrogen. To address this issue, it is necessary to better understand the diversity of species morphological response to nitrogen in interaction with light. Experiments have shown that interactions between competition for light and nitrogen can occur [START_REF] Ditomaso | Approaches for improving crop competitiveness through the manipulation of fertilization strategies[END_REF]. These interactions vary with resource supply [START_REF] Casper | Plant competition underground[END_REF][START_REF] Cahill | Fertilization effects on interactions between above-and belowground competition in an old field[END_REF] and are difficult to predict [START_REF] Mcphee | The separation of above-and below-ground competition in plants A review and critique of methodology[END_REF][START_REF] Mariotti | Above-and below-ground competition between barley, wheat, lupin and vetch in a cereal and legume intercropping system[END_REF][START_REF] Little | Effects of fertility amendments on weed growth and weed-crop competition: a review[END_REF]. Specific leaf area, leaf biomass ratio or height per unit aboveground biomass are three key morphological variables that respond to shading and are thus crucial to determine plant success in crop-weed competition for light. Specific plant height, or plant height per unit of aboveground biomass (HBR, cmg -1 ) illustrates the plant's effort in occupying vertical space.

The leaf biomass ratio (LBR in gg -1 , plant leaf biomass / total aboveground plant biomass) reflects how much effort the plant invests into light-intercepting organs. Finally, the specific leaf area (SLA in cm²g -1 , ratio of plant leaf area to plant leaf biomass) illustrates how efficiently the plant translates this effort into light-intercepting area. Studies have characterised the diversity of species morphological response to shading (Colbach et al., 2020b) which is useful to determine traits that improve crop competitiveness against weeds [START_REF] Colbach | The response of weed and crop species to shading: which parameters explain weed impacts on crop production[END_REF].

Previous studies have investigated the effect of soil-nitrogen or -nutrient gradients on these three morphological variables [START_REF] Vanderwerf | Evidence for optimal partitioning of biomass and nitrogen at a range of nitrogen availabilities for a fast-growing and slowgrowing species[END_REF][START_REF] Poorter | Growth and carbon economy of a fast-growing and a slow-growing grass species as dependent on nitrate supply[END_REF][START_REF] Vanarendonk | Effects of nitrogen supply on the anatomy and chemical composition of leaves of four grass species belonging to the genus Poa, as determined by image-processing analysis and pyrolysis mass spectrometry[END_REF][START_REF] Knops | Specific leaf area along a nitrogen fertilization gradient[END_REF][START_REF] Evans | Influence of nitrogen and duration of weed interference on corn growth and development[END_REF][START_REF] Singh | Effect of N application on emergence and growth of weeds associated with rice[END_REF][START_REF] Berger | Does soil nitrogen affect early competitive traits of annual weeds in comparison with maize?[END_REF] sometimes in interaction with shading [START_REF] Meziane | Interacting determinants of specific leaf area in 22 herbaceous species: effects of irradiance and nutrient availability[END_REF][START_REF] De Groot | Interactive effects of nitrogen and irradiance on growth and partitioning of dry mass and nitrogen in young tomato plants[END_REF][START_REF] Shipley | Interspecific consistency and intraspecific variability of specific leaf area with respect to irradiance and nutrient availability[END_REF][START_REF] An | Specific leaf area, leaf nitrogen content, and photosynthetic acclimation of Trifolium repens L. seedlings grown at different irradiances and nitrogen concentrations[END_REF]). Yet, the nitrogen actually available to plants varies with environmental factors (soil characteristics, water and light, cropping techniques). To date, no studies have documented, at the plant scale, the effect of plant nitrogen stress on aboveground morphology in interaction with shading.

The objective of this study was to characterize the response of three aboveground morphological variables (specific leaf area, leaf biomass ratio and height per unit biomass), crucial regarding plant-plant competition for light, to plant nitrogen stress in interaction with shading on a range of crop and weed species. We (1) quantified the interspecies diversity in response of plant morphological variables to nitrogen stress, (2) investigated to which extent these responses varied with shading, and (3) investigated the effects of clade, species type and habitat requirements to explain the interspecific variability.

Materials and methods

Principle

To characterize the response of aboveground morphology to nitrogen stress, we used the calculation approach derived from [START_REF] Munier-Jolain | Investigating and modelling the morphological plasticity of weeds[END_REF] and (Colbach et al., 2020b) based on experimental measurements on individual plants. In our study, individual plants of different crop and weed species were grown in optimal and stressed conditions regarding light and nitrogen (details in section 2.2). We investigated the impact of nitrogen stress on three morphological variables which were chosen for their importance in plant-plant competition for light: specific leaf area (SLA in cm²g -1 , ratio of plant leaf area to plant leaf biomass), leaf biomass ratio (LBR in gg -1 , plant leaf biomass / total aboveground plant biomass) and height per unit of aboveground biomass (HBR, cmg -1 ) (details in section 2.3 and 2.4). Equations linking morphological variables to stress indices were established (details in section 2.5).

Finally, the species morphological response to nitrogen stress was linked to species features such as clade, species type and habitat requirements (details in section 2.6).

Greenhouse experiments

Greenhouse experiments were conducted in Dijon (France), growing four crop and four weed species (Table 1) common in French arable fields. They included monocotyledonous and dicotyledonous species, and covered the range of the N-number of [START_REF] Ellenberg | Zeigerwerte der Gefässpflanzen Mitteleuropas Göttingen[END_REF]. This index ranks species from 1 (oligotrophic species mostly found in nitrogen-poor soils) to 9 (nitrophilic species mostly found in nitrogen-rich soils).

Plants were grown under different concentrations of nitrogen solution and two contrasted light treatments (except F. arundinacea whose plants did not survive in shaded conditions) (Table 1). The set-up of experiments 1, 2 and 3 of Table 1 is fully described in [START_REF] Perthame | Quantifying the nitrogen demand of individual plants in heterogeneous canopies: A case study with crop and weed species[END_REF].

Additional experiments 4 and 5 were conducted similarly. Briefly, in all experiments, plants were grown in individual 2-L pots filled with a solid, inert and draining substrate (60% attapulgite and 40% expanded clay). To obtain a gradient of plant nitrogen nutrition from suboptimal to supraoptimal, plants were grown under four or five nutrient solutions, varying in their nitrate concentration from 0.2 to 14 mM depending on species requirements. The different nutrient solutions were applied under two contrasted light treatments: 100% (unshaded) and 40% or 10% (shaded with a shading net) of incident light. These light treatments were chosen because weed species can experience shading up to 90% during their growth (Munier-Jolain et al., 2014). Each nutrient solution was provided by automatic watering several times a day at a frequency allowing the pots to drain, avoiding the accumulation of ions in the substrate and ensuring non-limiting irrigation. Twenty-four plants were grown per species × nitrogen treatment × light treatment combination, except for T. aestivum and P. aviculare in the shaded treatment at the highest nitrogen concentration of the solution where twenty plants were grown.

Plant measurements

For each species × nitrogen treatment × light treatment combination, four to six plants were sampled randomly at four dates (from 5 to 18-weeks after sowing). Samplings were carried out during the vegetative stage for all species, except for M. sativa (for two dates) and P. aviculare (for all dates) which were at reproductive stage. For each plant and at each sampling, plant height was measured (except for B. napus, G. molle and A. myosuroides in the shaded treatment due to human error). Plant height was measured with a ruler as "the shortest distance between the upper boundary of the main photosynthetic tissues on a plant and the ground level" (i.e. the substrate level in our experiments) as described in [START_REF] Cornelissen | A handbook of protocols for standardised and easy measurement of plant functional traits worldwide[END_REF]. In addition, plant leaf area was determined with a leaf area meter (LI-3100 Area Meter; Li-Cor, Lincoln, NE, USA), and leaf and stem biomass were measured after drying for 48h at 80°C. Finally, the nitrogen concentration in the aboveground plant part (leaves and stems) was measured using Dumas procedure after plant grinding (ThermoScientific TM FLASH 2000 CHNS/O Analyzer).

Nitrogen stress index

To estimate the nitrogen nutrition level of a plant independently of its light environment, the linear relationship between aboveground nitrogen amount (Nsh in g) and leaf biomass (BL in g) was used, as demonstrated in [START_REF] Perthame | Quantifying the nitrogen demand of individual plants in heterogeneous canopies: A case study with crop and weed species[END_REF] The relationship between aboveground nitrogen amount and leaf biomass at optimal nitrogen nutrition was calculated for a range of crop and weed species (Table S1 section A online). For a given leaf biomass, the aboveground nitrogen amount measured can be compared to the optimal aboveground nitrogen amount indicated by the relationship. At the plant scale, the ratio between the measured aboveground nitrogen amount and the optimal aboveground nitrogen amount given by the relationship corresponds to the nitrogen nutrition status of a plant. In the present study, this ratio was calculated for each plant to estimate the nitrogen nutrition stress of the plant.

The nitrogen stress index (Nstress in gg -1 ) was calculated as the mean of the four to six plants of each species × light treatment × nitrogen treatment × sampling date combination as:

[1] Nstress = 1 -Nsh measured / Nsh at optimal nitrogen nutrition This index varies (i.e. increases or decreases) with the nitrogen nutrition status of a plant. When the nitrogen stress index is equal to 0, the plant is at optimal nitrogen nutrition level. The more the nitrogen stress index exceeds 0, the more nitrogen-deficient the plant is. Conversely, the more negative the index is, the more supraoptimal the plant nitrogen level is.

The species parameters of response to nitrogen stress

The principle to determine the species parameters for all three morphological variables was derived from [START_REF] Munier-Jolain | Investigating and modelling the morphological plasticity of weeds[END_REF] and (Colbach et al., 2020b) The same approach was used for the Leaf Biomass Ratio (LBR, gg -1 ) to estimate the species potential LBR (LBR0s, gg -1 ) and the species LBR response to nitrogen stress (LBR_muNs, no unit) as well as the shading effect (L_LBR0l and L_LBR_muNl). Negative values of LBR_muNs indicate that nitrogen-deficient plants decrease their leaf biomass ratio.

The approach for the Height Biomass Ratio (HBR, cmg -1 ) included a third parameter (b_HBRs) to illustrate the sensitivity of plant height to plant aboveground biomass (Bsh in g) Here, for each morphological variable, we focused on the two parameters characterizing response to nitrogen stress and the effect of light treatment (for example, applied to SLA, it corresponds to SLA_muNs and L_SLA_muNl). Indeed, response to shading in unstressed nitrogen conditions was extensively studied in Colbach et al. (2020b) and was analysed in supplementary material section C online.

Linking nitrogen-stress response to species features

The determinants underlying the interspecific differences in morphological responses to nitrogen stress (i.e. parameters SLA_muNs, LBR_muNs and HBR_muNs) were analysed. To achieve this, we studied the effects of clade (monocotyledonous versus dicotyledonous species), species types (crop versus weed species) and habitat requirement (for nitrogen and light with respectively the N-number and the L-number of Ellenberg; Table 1), in interaction with shading. The effect of these species features on parameter values was analysed with linear models (lm function of R). Only factors significant at p≤0.1 were kept.

Results

Response of plant morphology to nitrogen stress

For all eight species, the effect of nitrogen stress on specific leaf area (SLA) was significant (Table 2): plants produced smaller thicker leaves (i.e. SLA decreased) when nitrogen deficiency increased (SLA_muNs < 0) (Figure 1). When looking at unshaded treatment only, the response to nitrogen stress varied among species, with the slope decreasing by a three-fold factor between A. myosuroides, the least plastic species, and P. aviculare, the most plastic species.

For four out of eight species, the leaf biomass ratio (LBR) was independent of nitrogen stress index (Table 3). For the others, the response of leaf biomass to nitrogen stress varied from species investing relatively more biomass in stems than leaves (i.e. LBR decreased) when nitrogen deficiency increased (LBR_muNs < 0 for T. aestivum in unshaded treatment, P.

aviculare, and A. myosuroides), to species increasing their leaf biomass ratio in case of nitrogen deficiency (LBR_muNs > 0 for M. sativa) (Figure 2).

Finally, height was independent of nitrogen stress index (Table 4), except for two species.

Plants of T. aestivum decreased their height for a given biomass in situation of nitrogen deficiency (HBR_muNs = -0.17) while plants of F. arundinacea etiolated (i.e. increased their height for a given biomass) in situation of nitrogen deficiency (HBR_muNs = 0.13).

Did the response of plant morphology to nitrogen stress vary with shading?

The response of specific leaf area to nitrogen stress depended on light treatment for only two out of seven species (Table 2). For G. aparine, the decrease of specific leaf area when nitrogen stress increased was stronger in shaded treatment than in unshaded treatment (Figure 1G) (pvalue = 0.0028). It was the opposite for P. aviculare (Figure 1F) (p-value = 0.0007). It should be noted that, for these two species, light treatment in interaction with nitrogen stress index explained little variability of specific leaf area, particularly compared to nitrogen stress index and light treatment as a single factor (Table 2).

Among the four species for which leaf biomass ratio varied with nitrogen stress index, only the response of T. aestivum depended on light treatment (Table 3, p-value = 0.0006). For this species, unshaded plants were leafier when nitrogen nutrition was supraoptimal (LBR_muNs < 0), whereas for shaded plants leaf biomass ratio was independent of nitrogen stress index (Figure 2D).

Finally, height response to nitrogen stress was independent of light treatment for all species (Table 4).

Correlations between species nitrogen responses and species features

Ellenberg-N number as a sole factor was the only significant factor at p≤0.1 explaining the response of specific leaf area to nitrogen stress (SLA_muNs). The decrease of specific leaf area with increasing nitrogen stress tended to be stronger for nitrophilic species (high Ellenberg-N values) (Table 5).

Similarly, the species type (crop/weed) as a sole factor was the only significant factor at p≤0.1 explaining the response of leaf biomass ratio to nitrogen stress (LBR_muNs). Weed species tended to invest more biomass into stems than leaves when nitrogen deficiency increased (LBR_muNs < 0) while it was the opposite for crop species (LBR_muNs > 0) (Table 5).

We did not investigate the effect of species type, clade or habitat requirement on height response to nitrogen stress as height was independent of nitrogen stress for most species.

Discussion

An original approach to quantify intrinsic species response to nitrogen stress

The present study was the first to quantify the response of three aboveground morphological variables, crucial for light competition, to plant nitrogen stress in interaction with shading for both crop and weed species, at the plant scale. The originality of the approach consisted in using a plant nitrogen stress index [START_REF] Perthame | Quantifying the nitrogen demand of individual plants in heterogeneous canopies: A case study with crop and weed species[END_REF] independent of light environment as explanatory variable. In contrast, previous studies investigated the effect of environmental variables such as nitrogen input rate (in field conditions) [START_REF] Poorter | Growth and carbon economy of a fast-growing and a slow-growing grass species as dependent on nitrate supply[END_REF][START_REF] Knops | Specific leaf area along a nitrogen fertilization gradient[END_REF][START_REF] Evans | Influence of nitrogen and duration of weed interference on corn growth and development[END_REF][START_REF] Singh | Effect of N application on emergence and growth of weeds associated with rice[END_REF] or nitrogen solution concentration (in controlled conditions) [START_REF] Vanarendonk | Effects of nitrogen supply on the anatomy and chemical composition of leaves of four grass species belonging to the genus Poa, as determined by image-processing analysis and pyrolysis mass spectrometry[END_REF][START_REF] Meziane | Interacting determinants of specific leaf area in 22 herbaceous species: effects of irradiance and nutrient availability[END_REF][START_REF] De Groot | Interactive effects of nitrogen and irradiance on growth and partitioning of dry mass and nitrogen in young tomato plants[END_REF][START_REF] Shipley | Interspecific consistency and intraspecific variability of specific leaf area with respect to irradiance and nutrient availability[END_REF][START_REF] Berger | Does soil nitrogen affect early competitive traits of annual weeds in comparison with maize?[END_REF][START_REF] An | Specific leaf area, leaf nitrogen content, and photosynthetic acclimation of Trifolium repens L. seedlings grown at different irradiances and nitrogen concentrations[END_REF] on morphological variables which might explain the contrasted results of these previous studies.

Indeed, in field conditions, a nitrogen input rate provided in different fields does not necessarily result in similar nitrogen nutrition for plants, depending on cropping techniques and biophysical processes. The present study allowed separating the nitrogen availability in the environment from the plant nitrogen nutrition. We showed that shading only had a small to no effect on the response of the three morphological variables to nitrogen stress. Consequently, our results are more generic, valid in every plant growth environment, thus reflecting species intrinsic properties regarding their response to nitrogen stress.

Are our results consistent with literature?

Due to the originality of our approach (section 4.1), it was difficult to directly compare our results with previous studies. We thus focused on confronting the direction of variation of morphological variables, by considering that plant nitrogen stress decreases with increasing nitrogen inputs (either in field conditions or controlled conditions).

It is well known that specific leaf area (SLA) decreases with lower nitrogen supply (thus higher nitrogen stress) [START_REF] Poorter | Growth and carbon economy of a fast-growing and a slow-growing grass species as dependent on nitrate supply[END_REF][START_REF] Vanarendonk | Effects of nitrogen supply on the anatomy and chemical composition of leaves of four grass species belonging to the genus Poa, as determined by image-processing analysis and pyrolysis mass spectrometry[END_REF][START_REF] Knops | Specific leaf area along a nitrogen fertilization gradient[END_REF][START_REF] Freschet | Integrated plant phenotypic responses to contrasting above-and below-ground resources: key roles of specific leaf area and root mass fraction[END_REF][START_REF] Singh | Effect of N application on emergence and growth of weeds associated with rice[END_REF], as we found in the present study. Leaf biomass ratio (LBR) was independent of nitrogen supply in [START_REF] Berger | Does soil nitrogen affect early competitive traits of annual weeds in comparison with maize?[END_REF] or increased with lower nitrogen supply in [START_REF] Freschet | Integrated plant phenotypic responses to contrasting above-and below-ground resources: key roles of specific leaf area and root mass fraction[END_REF]. In contrast, in our study, LBR decreased with increasing nitrogen stress for three species (it was the opposite for M. sativa). Also, [START_REF] Berger | Does soil nitrogen affect early competitive traits of annual weeds in comparison with maize?[END_REF] found that plant height per unit biomass increased with higher nitrogen supply while we did not observe such changes with nitrogen stress. These morphological changes all affect plant light capture, and thus carbon nutrition. In situations of non-limiting nitrogen nutrition, carbon nutrition becomes limiting. In such situations, increasing leaf area per unit biomass and proportion of leaf biomass results in higher light capture and thus higher plant carbon nutrition.

Our results suggest, for a few species, that carbon nutrition is mostly driven by specific leaf area and leaf biomass ratio and less by height per unit biomass.

An interaction between nitrogen supply and light availability on SLA was often reported, SLA decreasing more importantly with lower nitrogen supply in low light environments [START_REF] Meziane | Interacting determinants of specific leaf area in 22 herbaceous species: effects of irradiance and nutrient availability[END_REF][START_REF] De Groot | Interactive effects of nitrogen and irradiance on growth and partitioning of dry mass and nitrogen in young tomato plants[END_REF][START_REF] Shipley | Interspecific consistency and intraspecific variability of specific leaf area with respect to irradiance and nutrient availability[END_REF][START_REF] Freschet | Integrated plant phenotypic responses to contrasting above-and below-ground resources: key roles of specific leaf area and root mass fraction[END_REF]. In contrast, in our results, interaction between light treatment and nitrogen stress on SLA had a small significant effect only for two out of seven species and the direction of the interaction depended on the species. Similarly, a significant interaction between nitrogen and light availability was reported, LBR increasing more in response to lower nitrogen supply in low light environments [START_REF] Freschet | Integrated plant phenotypic responses to contrasting above-and below-ground resources: key roles of specific leaf area and root mass fraction[END_REF], while there was no significant interaction between light treatment and nitrogen stress on LBR in our study. These contrasted results can be explained by the use, in our study, of the plant nitrogen stress index independent of plant light growth environment, the latter strongly affecting plant nitrogen nutrition [START_REF] Seginer | Plant spacing effect on the nitrogen concentration of a crop[END_REF], instead of an environmental variable (i.e. nitrogen supply). The plant variable allows disentangling the effect of nitrogen availability from the effect of light availability on plant morphology.

We observed interspecific variations of plasticity. In particular, our approach allowed explaining ecological integrative features (such as Ellenberg-N number) that could be useful to characterise the plasticity of a large number of species without dedicated experiments.

Nitrophilic species tended to be more plastic than oligotrophic species. In particular, contrary to [START_REF] Freschet | Integrated plant phenotypic responses to contrasting above-and below-ground resources: key roles of specific leaf area and root mass fraction[END_REF], nitrophilic species showed a stronger decrease in their efficiency to produce leaf area per unit leaf biomass in response to increasing nitrogen stress. This result should be confirmed with more species as we tested only eight species in the present study and used a rather high significativity threshold (p≤0.1). This finding lines up knowledge on nitrophilic species growth (mostly found in nitrogen-rich soils) which strongly decreases in response to lower nitrogen supply because they cannot fulfil their nitrogen requirements [START_REF] Moreau | A plant nitrophily index based on plant leaf area response to soil nitrogen availability[END_REF][START_REF] Moreau | The ecophysiological determinants of nitrophily in annual weed species[END_REF].

Our results showed that the response of leaf biomass ratio to nitrogen stress was highly plastic and depended on the species. We were able to detect a novel trend, i.e. crop species tended to increase their leaf biomass ratio in response to increasing nitrogen stress while it was the opposite for weed species, which should be confirmed with more species.

It is important to note that our results were seen on a few number of species, thus more species should be investigated to support our conclusions. Also, our results were obtained regardless of the plant growth stages. In previous studies, the interaction of plant stages (or harvest dates)

with light and/or nitrogen treatments on morphological variables were significant [START_REF] Shipley | Interspecific consistency and intraspecific variability of specific leaf area with respect to irradiance and nutrient availability[END_REF]Colbach et al., 2020b). It means that the response of morphological variables to nitrogen stress might vary between plant stages. This aspect should be investigated via experiments with sampling dates made at key growth stages.

Practical application: impact on field competition

Specific leaf area (SLA) and leaf biomass ratio (LBR) are crucial for light competition and the differential species responses of these morphological variables to nitrogen stress might affect crop-weed competition. For example, P. aviculare was the species that the most decreased its SLA (in unshaded conditions) and its LBR in response to nitrogen stress. In the case of nitrogen stress, this species might grow less than other species, as it decreased the area and proportion of its photosynthetically active tissues the most as well as its capacity to shade neighbouring plants. At the opposite, A. myosuroides, which decreased its SLA and LBR the least, might be more competitive for light than the other species in the case of nitrogen stress.

Height is also important for light competition and for the establishment of plant hierarchies [START_REF] Nagashima | The processes of height-rank determination among individuals and neighbourhood effects in Chenopodium album L-Stands[END_REF][START_REF] Colbach | The response of weed and crop species to shading: which parameters explain weed impacts on crop production[END_REF], so differential responses of plant height per unit biomass to plant nitrogen stress could affect the outcome of crop-weed competition. For example, at a given biomass, T. aestivum growth could be more disfavoured by nitrogen stress than weed growth because weed height per unit biomass remains unchanged (for the species experimented here) whereas T. aestivum decreases height per biomass. Conversely, F.

arundinacea (whose height per unit biomass increases with nitrogen stress) would be advantaged relatively to weeds in the case of nitrogen stress.

However, the outcome of crop-weed competition regarding light and nitrogen depends on many other factors. For instance, the competitive advantage of a species depends on its efficiency to produce specific leaf area, leaf biomass ratio or height per unit biomass at optimal nitrogen nutrition (parameters SLA0, LBR0 and HBR0). These parameters values change with light environment of the plants. For example, shaded plants are more efficient to produce leaf area per unit leaf biomass at optimal nitrogen nutrition than unshaded plants (Colbach et al., 2020b).

Many other processes can affect the outcome of crop-weed competition, such as plant germination and growth dynamics, phenology, access to water, pedoclimate and cropping techniques, such as fertilisation (which affects timing of nutrient availability), soil management, crop cultivar, sowing date and density or herbicide use [START_REF] Little | Effects of fertility amendments on weed growth and weed-crop competition: a review[END_REF]. Mechanistic crop models (i.e. based on biological or physical processes) allow synthetizing existing knowledge, exploring diverse prospective scenarios and designing cropping systems [START_REF] Renton | Modelling crop-weed competition: Why, what, how and what lies ahead?[END_REF][START_REF] Gaudio | Current knowledge and future research opportunities for modeling annual crop mixtures[END_REF]. Thus, integrating the parameters outlined in the present study into a mechanistic model simulating weed dynamics and crop yield over the years from cropping system, pedoclimate and species traits such as FLORSYS (Colbach et al., 2020a;[START_REF] Moreau | Integrating crop-weed competition for nitrogen in the FLORSYS weed-dynamics simulation model[END_REF] and performing simulations help to identify the key traits that influence plant-plant competition and how they impact it [START_REF] Colbach | The response of weed and crop species to shading: which parameters explain weed impacts on crop production[END_REF]. Global sensitivity analysis analyse the variability of model outputs in response to the simultaneous variation of model inputs (such as species parameters) throughout their entire range of variation, taking into account the interactions between inputs [START_REF] Saltelli | Global Sensitivity Analysis: The Primer[END_REF]. Such analyses would allow to identify and rank parameters in function of their influence on plant-plant competition, thus providing guidelines on competitive crop species/cultivars to sow.

Conclusions

By using a plant nitrogen stress indicator instead of an environmental variable (i.e. nutrient supply), we could characterize species morphological intrinsic response to nitrogen stress in every plant growth environment. Specific leaf area (SLA) decreased in response to nitrogen stress for all species, while leaf biomass ratio (LBR) was more plastic, weed species increasing more their stem biomass than leaf biomass in response to higher nitrogen stress, in contrast to crop species. Height per unit biomass (HBR) was mostly independent of nitrogen stress. This novel plant indicator has the benefits of disentangling the effect of light from nitrogen availability. Morphological response to nitrogen stress was independent from shading for a majority of species, the light effect observed for a few rare species was negligible compared to their response to nitrogen stress. Our approach also allowed us to partially explain species response to habitat (characterised by ecological integrative indices). These results help to better understand the behaviour of a given species in situations of competition for light and nitrogen, an increase of SLA, LBR and HBR in response to nitrogen stress increasing species light competitiveness in situation of nitrogen deficiency. As species competitiveness depends on many factors, the parameters developed in this study can be integrated in mechanistic crop models. Simulations with such models will allow ranking parameters depending on their influence and effect on plant-plant competition. [START_REF] Ellenberg | Zeigerwerte der Gefässpflanzen Mitteleuropas Göttingen[END_REF] for all species except the N-number of B. napus and T. aestivum [START_REF] Moreau | A plant nitrophily index based on plant leaf area response to soil nitrogen availability[END_REF]. NA for non-available data.

Figure

  Figure S2 section B online):

(

  [START_REF] Munier-Jolain | Investigating and modelling the morphological plasticity of weeds[END_REF]:[4] Hpsl = HBR0sl Bshpsl b_HBRs exp(HBR_muNsl Nstresspsl) + errorpsl Which was logn-transformed into:[5] logn (Hpsl) = logn(HBR0s) + L_HBR0l + b_HBRs logn(Bshpsl) + HBR_muNsNstresspsl + L_HBR_muNl Nstresspsl + errorpslwhere Hpsl (cm) is the height measured on plant p of species s in light condition l. Similarly to SLA and LBR, parameter HBR0s (cmg -1 ) assesses species potential HBR at optimal nitrogen nutrition, HBR_muNs (no unit) the species HBR response to nitrogen stress, L_HBR0l (cmg - 1 ) and L_HBR_muNl (no unit) the light effect on respectively potential HBR and HBR response to nitrogen stress. For B. napus, A. myosuroides and G. molle, L_HBR0l and L_HBR_muNl were removed from the model as height was measured only in unshaded treatment (see 2.3). Negative HBR_muNs values indicate that nitrogen-deficient plants decrease their height per unit biomass. The third parameter b_HBRs (no unit) estimates whether heavy and light plants at optimal nitrogen nutrition level of a given species produce the same height for a given biomass (b_HBRs =1) or whether light plants produce more height for a given biomass than heavy plants at optimal nitrogen nutrition (b_HBRs <1). As before, equation [5] was fitted with the lm function of R and weighting observations by the inverse of the relative standard deviation of height for each species × light treatment × nitrogen treatment × sampling date, and partial R 2 were calculated.

For

  example, Ravier et al. (2017) computed wheat nitrogen nutrition index from a large range of experiments on different sites and cropping systems. The distribution of nitrogen nutrition index at various growth stages was different from the distribution of nitrogen rate for the experimental treatments. Similarly, in controlled conditions experiments, a nitrogen solution concentration can result in different plant nitrogen nutrition depending on other environmental variables (such as pot size, substrate, watering).

Figure 1 :

 1 Figure 1: Relationship between logn-transformed values of specific leaf area and nitrogen

Figure 2 :

 2 Figure 2: Relationship between logn-transformed values of leaf biomass ratio and nitrogen

  to explore the proportion of variance of logn-7 transformed values of specific leaf area explained by nitrogen stress index and light 8 treatment, except for F. arundinacea analysed only in unshaded treatment. Only factors 9 significant at p≤0.05 were kept, NS indicate non-significant factors that were removed from the 10 model. P-values are indicated in parenthesis. R² values (calculated from the type-III sum of squares of ANOVA) from 13 model Erreur ! Source du renvoi introuvable. applied to leaf biomass ratio to explore the 14 proportion of variance of logn-transformed values of leaf biomass ratio explained by 15 nitrogen stress index and light treatment, except for F. arundinacea analysed only in 16 unshaded treatment. Only factors significant at p≤0.05 were kept, NS indicate non-significant 17 factors that were removed from the model. P-values are indicated in parenthesis. 18a Non-significant factor kept in the model because of significant interaction with nitrogen stress

Table 1 : Details of the experiments performed in greenhouse in Dijon (France).

 1 Plants were grown under four or five nitrogen treatments and two light treatments: unshaded (100% of incident light available to plants) or shaded.

	Expe-	Species	Mono-	or	Ellenberg N-	Ellenberg L-	Nitrogen treatments (mM)	Percentage of incident light
	riment	(cultivar for	dicotyledonous		number b	number b	Unshaded	Shaded	available to plants in shaded
		crops)	species				treatment	treatment	treatment
	#1	Medicago	Dicotyledon		NA	8	0.4, 1, 5	0.2, 0.4, 1 and 5	10%
		sativa (Agathe					and 10
		NF a	)
		Festuca	Monocotyledon		5	8		Only unshaded	Only unshaded treatment
		arundinacea						treatment
		(Soni)
	#2	Brassica	Dicotyledon		12.4	NA	1, 5, 10 and	0.4, 1, 5 and 10	10%
		napus					14
		(Kadore)
		Geranium	Dicotyledon		4	7
		molle
	#3	Triticum	Monocotyledon		4.4	NA	1, 5, 10 and	0.4, 1, 5, 10 and	40%
		aestivum					14	14
		(Caphorn)
		Polygonum	Dicotyledon		6	7
		aviculare
	#4	Alopecurus	Monocotyledon		6	6	1, 5, 10 and	0.4, 1, 5 and 10	10%
		myosuroides					14
	#5	Galium	Dicotyledon		8	7	1, 5, 10 and	0.4, 1, 5, 10 and	40%
		aparine					14	14
	a Non-N2-fixing

b

Ellenberg N-and Ellenberg L-number estimated from

Table 2 :

 2 Partial R² values (calculated from the type-III sum of squares of ANOVA) from 6 model Erreur ! Source du renvoi introuvable.

Table 4 :

 4 Partial R² values (calculated from the type-II sum of squares of ANOVA) from model Erreur ! Source du renvoi introuvable. to

explore the proportion of variance of logn- transformed values of height explained by nitrogen stress index, light treatment and logn- transformed values of aboveground biomass (Bsh in g

  )[START_REF] Munier-Jolain | Investigating and modelling the morphological plasticity of weeds[END_REF]. Only factors significant at p≤0.05 were kept, NS indicate non-significant factors that were removed from the model. P-values are indicated in parenthesis.

	Factor				Partial R² (p-value)
			Crop species			Weed species
		Brassica	Festuca	Medicago	Triticum	Alopecurus	Galium	Geranium	Polygonum
		napus	arundinacea	sativa	aestivum	myosuroides	aparine	molle	aviculare
	Light	Only	Only	0.269	0.144	Only	0.044	Only	NS
	Treatment	unshaded treatment	unshaded treatment	(0.012)	(0.0009)	unshaded treatment	(0.0032)	unshaded treatment
	Nstress	NS	0.343	NS	0.103	NS	NS	NS	NS
			(0.0392)		(0.0031)
	Logn(Bsh) 0.986	NS	0.662	0.572	0.936	0.875	NS	0.599
		(<0.0001)		(<0.0001)	(<0.0001)	(<0.0001)	(<0.0001)		(0.0001)
	Nstress ×	Only	Only	NS	NS	Only	NS	Only	NS
	Light	unshaded	unshaded			unshaded		unshaded
	Treatment	treatment	treatment			treatment		treatment
	Total	0.986	0.343	0.931	0.819	0.936	0.919	NS	0.599
	variance
	explained

Table 5 : Response of two parameters (response of specific leaf area to nitrogen stress and response of leaf biomass to nitrogen stress) to species features (Ellenberg-N number and species type).

 5

	Factor		SLA_muN	LBR_muN
		Slope	-0.037	Non-significant at p≤0.1
	Ellenberg-N	Intercept	-0.246
	number	R²	0.269
		p-value	0.07
		Weed	Non-significant at p≤0.1	-0.375
		Crop		0.233
	Species type
		R²		0.490
		p-value		0.05

Acknowledgements

This project was supported by INRAE, the European Union's Horizon 2020 Research and innovation programme under grant agreement N 727217 (ReMIX project), the Casdar RAID project funded by the French Ministry in charge of Agriculture and Food (Ministère de l'Agriculture et de l'Alimentation, avec la contribution financière du compte d'affectation spéciale 'Développement agricole et rural'). Laurène Perthame benefited from a PhD studentship funded by the French Ministry of Research. The authors are grateful to Gaëtan Louarn for helpful discussions about experimental design and for providing some seed lots, as well as Danilo dos Reis Cardoso Passos, Estelle Genottin, Laura Ponticelli and the greenhouse staff for their technical assistance.

Funding information

INRAE

French Ministry of Research European Union's Horizon 2020 Research and innovation programme under grant agreement ReMIX project N 727217 Casdar RAID project funded by the French Ministry in charge of Agriculture and Food (Ministère de l'Agriculture et de l'Alimentation, avec la contribution financière du compte d'affectation spéciale 'Développement agricole et rural') Word count = 6307

Conflict of interest

The authors declare that they have no conflict of interest.

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