D R Sabina

Emma Ladouceur
email: emmala@gmail.com

Costantino Bonomi
email: costantino.bonomi@muse.it

Helge Bruelheide
email: helge.bruelheide@botanik.uni-halle.de

Jitka Klimešová
email: jitka.klimesova@ibot.cas.cz

Sabina Burrascano
email: sabina.burrascano@uniroma1.it

Peter Poschlod
email: peter.poschlod@ur.de

Maria Tudela-Isanta

Pietro Iannetta
email: pete.iannetta@hutton.ac.uk

Andrea Mondoni
email: andrea.mondoni@unipv.it

Bernard Amiaud
email: bernard.amiaud@univ-lorraine.fr

Bruno E L Cerabolini
email: bruno.cerabolini@uninsubria.it

J Hans

C Cornelissen
email: j.h.c.cornelissen@vu.nl

Joseph Craine

Frédérique Louault
email: frederique.louault@inra.fr

Vanessa Minden
email: vanessa.minden@uni-oldenburg.de

Kinga Öllerer
email: kinga.ollerer@gmail.com

Vladimir Onipchenko
email: vonipchenko@mail.ru

Nadejda A Soudzilovskaia
email: n.a.soudzilovskaia@cml.leidenuniv.nl

Jiménez-Alfaro Borja
email: jimenezalfaro.borja@gmail.com

The functional trait spectrum of European temperate grasslands

Keywords: clonality, functional traits, germination, grasslands, regeneration niche, seed traits, specialist species, species pool, trait spectrum

In specialist species of alpine grassland habitat types of continental Europe, nonregeneration traits seem to be filtered across habitat gradients, and most regeneration traits demonstrate multiple strategies within each habitat type, indicating possible variable trait strategies with trait groups associated with different processes.

INTRODUCTION

At the global scale, the variation in plant functional traits in multidimensional traitspace is determined by two axes related to plant size and leaf area [START_REF] Diaz | The global spectrum of plant form and function[END_REF].

These two dimensions are mainly linked with ecological trade-offs on a uniformly fast, medium, or slow growth strategy gradient [START_REF] Reich | The world-wide "fast-slow" plant economics spectrum: a traits manifesto[END_REF][START_REF] Salguero-Gómez | Fast-slow continuum and reproductive strategies structure plant life-history variation worldwide[END_REF]; and along a leaf construction economics spectrum (Wright, Reich, Westoby, Ackerly & Baruch 2004). The multidimensional trait perspective helps to understand evolutionary constraints of functional diversity for plant species, but linking this trait variation with ecological drivers is still needed [START_REF] Bruelheide | Global trait-environment relationships of plant communities[END_REF]. Functional plant strategies can be explained by traits filtered in biogeographic regions and in local ecological communities as a response to historical and environmental conditions [START_REF] De Bello | Variations in species and functional plant diversity along climatic and grazing gradients[END_REF][START_REF] De Bello | Functional species pool framework to test for biotic effects on community assembly[END_REF][START_REF] Poschlod | Seed ecology and assembly rules in plant communities[END_REF]. However, linking local filtering with regional and continental processes remains a major challenge [START_REF] Pärtel | Macroecology of biodiversity: disentangling local and regional effects[END_REF], and new approaches in functional-trait ecology are needed to better understand these patterns and processes in plant community ecology.

Within different historical and environmental contexts, some species are more influenced by ecological filters than others, resulting in some level of species sorting in different habitats [START_REF] Leibold | Metacommunity ecology[END_REF]. While some species may be restricted to one habitat as specialists [START_REF] Fridley | Cooccurrence based assessment of habitat generalists and specialists: a new approach for the measurement of niche width[END_REF]), other species can plastically respond to Comment citer ce document : Ladouceur, E. (Auteur de correspondance), Bonomi, C., Bruelheide, H., Klimešová,, J., Burrascano, S., Poschlod, P., Tudela-Isanta, M., Iannetta, P., Mondoni, A., Amiaud, B., Cerabolini, B.

E. L., Cornelissen,, J. H. C., Craine, J., Louault, F., Minden, V., Öllerer, K., Onipchenko, V., Soudzilovskaia, N. A., Jiménez-Alfaro, B. ( 2019). The functional trait spectrum of European

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different environmental conditions (Vellend 2016) and occur commonly across environmental gradients as generalists. The presence of generalists in local communities weakens the importance of environmental filtering within habitat types, and the predictability of environment-trait relationships in favour of non-niche processes such-as dispersal limitation [START_REF] Fridley | Cooccurrence based assessment of habitat generalists and specialists: a new approach for the measurement of niche width[END_REF]. In contrast, plant specialists consistently associated with local environmental conditions are expected to present specific traits that make these species a strong competitor in a given habitat. Studying the trait variation of plant specialists may therefore help to detect environmental filtering within the species pool, or the species which can potentially occur at a site [START_REF] Pärtel | Dark diversity: shedding light on absent species[END_REF]. Identification of functional species pools is a pre-requisite to differentiate functional patterns produced by abiotic filters [START_REF] De Bello | Functional species pool framework to test for biotic effects on community assembly[END_REF], and separating specialists from generalists within species pools could perhaps strengthen this approach.

Plant species may be particularly sensitive to environmental filtering at the regeneration stage and this might be more important than other life-history stages as species could be totally excluded from a habitat due to inappropriate environmental conditions for germination or successful establishment (Grub 1977). However, our knowledge of plant trait ecology is largely focused on few traits concerning aboveground vegetative growth and morphology, and very few studies have assessed the potential role of regeneration traits [START_REF] Poschlod | Seed ecology and assembly rules in plant communities[END_REF][START_REF] Jiménez-Alfaro | Seed germination traits can contribute better to plant community ecology[END_REF][START_REF] Larson | Regeneration: an overlooked aspect of trait-based plant community assembly models[END_REF][START_REF] Saatkamp | A research agenda for seed-trait functional ecology[END_REF]). Regeneration traits have been long acknowledged as relevant to the natural maintenance of biodiversity [START_REF] Grubb | The maintenance of species-richness in plant communities: the importance of the regeneration niche[END_REF], and have been found to be important for both species coexistence and species sorting

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E. L., Cornelissen,, J. H. C., Craine, J., Louault, F., Minden, V., Öllerer, K., Onipchenko, V., Soudzilovskaia, N. A., Jiménez-Alfaro, B. ( 2019). The functional trait spectrum of European

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( [START_REF] Bernard-Verdier | Community assembly along a soil depth gradient: contrasting patterns of plant trait convergence and divergence in a Mediterranean rangeland (H. Cornelissen[END_REF][START_REF] Pierce | How well do seed production traits correlate with leaf traits, whole-plant traits and plant ecological strategies?[END_REF][START_REF] Fernández-Pascual | Environmental filtering drives the shape and breadth of the seed germination niche in coastal plant communities[END_REF].

Processes captured by regeneration traits including flowering, seed production, clonal growth, dispersal, germination, and growth rates are relevant to community assembly, species turnover, survival and persistence [START_REF] Pohl | Functional traits and root morphology of alpine plants[END_REF][START_REF] Poschlod | Seed ecology and assembly rules in plant communities[END_REF][START_REF] Klimešová | Herbs are different: clonal and bud bank traits can matter more than leaf-height-seed traits[END_REF]. When combined with non-regeneration traits, regeneration traits might add new dimensions to the plant trait spectrum [START_REF] Laughlin | The intrinsic dimensionality of plant traits and its relevance to community assembly[END_REF][START_REF] Pierce | How well do seed production traits correlate with leaf traits, whole-plant traits and plant ecological strategies?[END_REF][START_REF] Salguero-Gómez | Fast-slow continuum and reproductive strategies structure plant life-history variation worldwide[END_REF][START_REF] Herben | Reproduction by seed and clonality in plants: correlated syndromes or independent strategies?[END_REF], providing a better understanding of the role of environmental filtering in plant communities and on different types of traits.

Here, we study the functional trait variation of a species pool representative of European temperate grasslands. Our case study consists of the most frequent and dominant species occurring in widely distributed grasslands types, with similar growth and life forms but differing in species composition and environmental conditions along gradients of altitude and traditional long-term disturbance regimes [START_REF] Ellenberg | Vegetation ecology of Central Europe[END_REF][START_REF] Körner | Alpine plant life: functional plant ecology of high mountain ecosystems[END_REF][START_REF] Nagy | Alpine Biodiversity in Europe[END_REF][START_REF] Dainese | Do climate, resource availability, and grazing pressure filter floristic composition and functioning in alpine pastures?[END_REF]. By combining non-regeneration traits and less commonly studied regeneration traits, our first aim was to describe the trait spectrum of the species pool of European temperate grasslands, and to test whether this spectrum reflects the main dimensions observed at the global scale. Our second aim was to test whether habitat specialists of each grassland type show trait differentiation that might explain environmental filtering. Despite the marked dominance of few life-and growth-forms in European grasslands, we expect habitat specialists to exhibit trait combinations that may allow us to functionally characterize

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E. L., Cornelissen,, J. H. C., Craine, J., Louault, F., Minden, V., Öllerer, K., Onipchenko, V., Soudzilovskaia, N. A., Jiménez-Alfaro, B. ( 2019). The functional trait spectrum of European

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vegetation types, possibly with more subtle detail than at a global scale across disparate biomes.

METHODS

Species data

We focused on five grassland types representing wide ecological variation in altitude, soil and disturbance (Table 1) as described in the classification of European habitats [START_REF] Galvanek | Management of Natura 2000 habitats: species-rich Nardus grasslands 6230[END_REF][START_REF] Garcia-Gonzalez | Management of Natura 2000 habitats alpine and subalpine calcareous grasslands 6170[END_REF][START_REF] Calaciura | Management of Natura 2000 habitats: semi-natural dry grasslands (Festuco-Brometalia) 6210[END_REF]European Environment Agency 2012). We obtained the species list of constituent species from a continental review [START_REF] Schaminée | Review of grassland habitats and development of distribution maps of heathland, scrub and tundra habitats of EUNIS habitats classification[END_REF]) based on the European Vegetation Archive [START_REF] Chytrý | European Vegetation Archive (EVA): an integrated database of European vegetation plots[END_REF] and over 1 million field surveys to report species frequencies in these European habitat types. We removed rare species with <5% frequency of occurrence in each grassland type at the continental scale. We identified as specialists those species with a significantly (P < 0.05) higher frequency of occurrence in one grassland type than any other using a Fisher's exact test [START_REF] Agresti | Categorical data analysis[END_REF]. Most of these specialists are generally described as characteristic or dominant species of the study grassland types in Europe (see habitat descriptions and references in Table 1). All other species were labelled as generalists. We note that our definition of specialists applies exclusively to the five grassland types compared here, assuming the association of species with one grassland type is mainly due to ecological preferences.

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E. L., Cornelissen,, J. H. C., Craine, J., Louault, F., Minden, V., Öllerer, K., Onipchenko, V., Soudzilovskaia, N. A., Jiménez-Alfaro, B. ( 2019). The functional trait spectrum of European

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Traits selection and data collection

The majority of trait data was compiled from existing datasets contributed to the TRY Plant Trait Database (see Data Use and Table 2) [START_REF] Kattge | TRY -a global database of plant traits[END_REF] 2013). Traits were selected to represent different aspects of plant organs or whole plant properties and their functional significance and life history [START_REF] Laughlin | The intrinsic dimensionality of plant traits and its relevance to community assembly[END_REF][START_REF] Jiménez-Alfaro | Seed germination traits can contribute better to plant community ecology[END_REF]. Data were then extracted by matching accepted plant names and known synonyms from the target species list into subsets. Eleven traits were used from TRY, across 47 TRY datasets, and 10 from other sources (Table 2), selected from a larger list of traits of interest. A trait was used as long as there were at least three data points for each grassland type. Trait units of measurement were standardised across datasets, and where multiple values existed, we used the mean of all individual traits of each species. While this approach does not account for intraspecific trait variation, it is expected that the influence of this variation takes place mostly within each grassland type, representing less than 20% of total variation [START_REF] Siefert | A global meta-analysis of the relative extent of intraspecific trait variation in plant communities[END_REF].

Data Analysis

All statistical analyses and plotting were conducted using the R Studio language and environment for statistical computing and graphics (version 3.4.0). Each R package used is referenced as each approach is explained.

Comment citer ce document : Ladouceur, E. (Auteur de correspondance), Bonomi, C., Bruelheide, H., Klimešová,, J., Burrascano, S., Poschlod, P., Tudela-Isanta, M., Iannetta, P., Mondoni, A., Amiaud, B., Cerabolini, B.

E. L., Cornelissen,, J. H. C., Craine, J., Louault, F., Minden, V., Öllerer, K., Onipchenko, V., Soudzilovskaia, N. A., Jiménez-Alfaro, B. ( 2019). The functional trait spectrum of European

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We used a Principal Component Analysis (PCA) to describe the multivariate trait spectrum and to identify the contribution of individual traits. We used the R package missMDA (Husson & Josse 2018) to replace missing values in the numerical traits for the PCA and to estimate parameters based on existing values within the dataset [START_REF] Josse | Handling missing values in exploratory multivariate data analysis methods[END_REF][START_REF] Josse | missMDA: A package for handling missing values in multivariate data analysis[END_REF]. Out of 9,002 (643 rows of numerical trait data x 14 columns) possible records in the PCA, 48.5% of data was missing and replaced with predicted values from the observed data. Categorical traits were excluded from the multivariate analysis. Missing data was unevenly distributed across traits, with lesscommonly studied regeneration traits missing more data than others, but averages between non-regeneration and regeneration traits overall were the same, and all traits were considered regardless (Data Quality, Table S1). The implication of this gap-filling method is that the variance in the estimators is underestimated [START_REF] Josse | Handling missing values in exploratory multivariate data analysis methods[END_REF][START_REF] Josse | missMDA: A package for handling missing values in multivariate data analysis[END_REF]. The gap-filled data was then log transformed as data were not normally distributed. The loadings of each trait and the scores of each species were extracted for the first five axes. Results were plotted using ggplot2 (Wickham 2009),

FactoMineR [START_REF] Husson | FactoMineR: Multivariate exploratory data analysis and data mining[END_REF], and factoextra [START_REF] Kassambara | factoextra: Extract and visualize the results of multivariate data analyses[END_REF].

The collinearity of traits in the PCA was evaluated in a correlation matrix using the package corrplot (Wei & Simko 2017).

We examined the distribution of specialists and generalists in the trait space by plotting the PCA scores of both species groups for each grassland type. The PCA results

were used to compare the trait space of different grassland types, plotted using packages ade4 [START_REF] Dray | ade4: analysis of ecological data: exploratory and euclidean methods in environmental sciences[END_REF] and adegraphics (Dray & Siberchiot 2018). Differences in PCA scores between grassland types were tested with a

Comment citer ce document : Ladouceur, E. (Auteur de correspondance), Bonomi, C., Bruelheide, H., Klimešová,, J., Burrascano, S., Poschlod, P., Tudela-Isanta, M., Iannetta, P., Mondoni, A., Amiaud, B., Cerabolini, B.

E. L., Cornelissen,, J. H. C., Craine, J., Louault, F., Minden, V., Öllerer, K., Onipchenko, V., Soudzilovskaia, N. A., Jiménez-Alfaro, B. ( 2019). The functional trait spectrum of European

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permutational analysis of variance (PERMANOVA) using vegan (Oksansen et al. 2018) and with a post-hoc pairwise PERMANOVA statistical tests using RVAideMemoire [START_REF] Hervé | RVAideMemoire: Diverse basic statistical and graphical functions[END_REF]. Both tests were based on 999 permutations. To identify the traits that best separated the different grassland types, we employed discriminant analysis using the gap-filled data. A stepwise forward variable model selection was performed based on Wilk's Lambda criterion using the packages klaR [START_REF] Roever | klaR: Classification and Visualization[END_REF], and mda [START_REF] Hastie | mda: mixture and flexible discriminant analysis[END_REF], which minimizes within-class distances and contextually maximises class discrimination [START_REF] Bianco | Morpho-colorimetric characterisation of Malva alliance taxa by seed image analysis (R. Bekker[END_REF].

We tested for differences in mean trait values among grassland types using a post-hoc pairwise Kruskal-Wallis χ 2 test from the package PMCMR [START_REF] Pohlert | The pairwise multiple comparison of mean ranks package (PMCMR)[END_REF]. Raw data were plotted for single traits, with no gap-filling or transformation taking place.

Categorical traits were plotted in the package ggplot2 (Wickham 2018). The numerical traits and individually plotted PCA axis coordinates were visualized as RDI plots (Raw data, descriptive and inference statistics) created using the package yarrr [START_REF] Phillips | A Companion to the e-Book "YaRrr!: The pirate's guide to R[END_REF], to effectively visualise the breadth of each trait within categories, as well as for visual comparison between them. This allowed for individual investigation of trait patterns found in the multivariate space without gap-filling.

RESULTS

We compiled a list of 645 species in total (excluding 44 species with missing data), including 257 generalists and 388 specialists, 52 taxonomic families and 244 genera (Table S1, Supporting Information). Overall, we identified 56 specialists in meadows,

Comment citer ce document : Ladouceur, E. (Auteur de correspondance), Bonomi, C., Bruelheide, H., Klimešová,, J., Burrascano, S., Poschlod, P., Tudela-Isanta, M., Iannetta, P., Mondoni, A., Amiaud, B., Cerabolini, B.

E. L., Cornelissen,, J. H. C., Craine, J., Louault, F., Minden, V., Öllerer, K., Onipchenko, V., Soudzilovskaia, N. A., Jiménez-Alfaro, B. ( 2019). The functional trait spectrum of European

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grasslands, and 47 in acidic alpine grasslands for which there was available trait data (Table S1). Both the specialists and generalists represent > 83% of the species detected in the study habitats and in the context of this study we refer to them as the continental species pool.

Multivariate trait spectrum

The first, second and third axis of the PCA based on 14 numerical traits explained 23%, 9.2 % and 9.1% of the total variance, respectively (Fig. 1). All non-regeneration traits, including radial growth rate, SLA and plant height had relatively high loadings on the first axis of the PCA (Fig. 1a, Table 3). The regeneration traits with the highest contribution with the first axis were Tmax, soil seed bank longevity, flowering duration and flowering onset. Plant height and SLA also contributed to the second axis, together with flowering onset, seed mass, seed number per ramet, and flowering duration (Fig.

1a, b, Table 3, Table S2). On the third axis, regeneration traits (To, seed mass, clonal index, flowering onset and Tmin) contributed the most variation (Fig. 1 b, Table 3).

Most of the traits (85%) were significantly correlated among each other (Table S4). The strongest correlations were between flowering onset and flowering duration (Pearson r = -0.463); between Tmax and duration of seed bank longevity (0.358); and between plant height and seed number (0.345). To was negatively correlated with plant height and seed number per ramet Tmin, clonal shoot cyclicity and flowering onset were negatively correlated with all traits except To, seed mass and each other. Seed mass was negatively correlated with seed number per ramet and clonal index, and positively correlated with all other traits except To. The other traits had positive correlations.

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E. L., Cornelissen,, J. H. C., Craine, J., Louault, F., Minden, V., Öllerer, K., Onipchenko, V., Soudzilovskaia, N. A., Jiménez-Alfaro, B. ( 2019). The functional trait spectrum of European

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Trait variation of habitat specialists

The groups of habitat specialists were differentiated among each other in the trait space (PERMANOVA F=13.43, R2=0.095, P=<0.001, Fig. 2 a, Table S6b,c). Main differences between habitats were related to the first axis of variation (Fig. S1 b, Kruskal-Wallis s 2 = 127.4, P= <0.001, Table S5). On axis 2, only acidic alpine grasslands were differentiated from Nardus-dominated grasslands (Fig. S1 b, s 2 = 12.029, P= 0.03, Table S5). The variability between group means (F-value) was larger for regeneration (F= 13.77, R2 0.098, P=<0.001, Table S6f) than for non-regeneration traits (F= 10.071, R2= 0.073, P=<0.001, Table S6e). The most important traits in differentiating specialist groups according to the discriminant analyses were plant height, flowering duration, seed bank longevity, SLA, and flowering onset (Table 3,I; Table S7; Fig. S2 ). There was an overall misclassification error of 51%, which was mainly brought about by a strong overlap in predictions for Nardus-dominated grasslands with calcareous and acidic alpine grasslands (Table S8a). Predictions were similar when non-regeneration traits were analysed separately, better characterising certain grassland specialists, while other specialists were better characterised by regeneration traits (Table S8bc). However, the discriminative power was more accurate when all traits were used together, rather than separately (Table S8).

Acidic alpine grasslands had the lowest SLA (Kruskal-Wallis s 2 = 73.28, P= <0.001, Table S1), shortest plant height (s 2 = 95.59, P= <0.001, Table S10), and a slow radial growth rate (s 2 = 28.56, P= <0.001, Table S10) with a late (s 2 = 51.38, P= <0.001, Table S10) and short flowering duration (s 2 = 74.87, P= <0.001, Table S10) (Fig. 3, Fig. 4).

Sempervivum arachnoideum, with its far-reaching runners was the only acidic alpine

Comment citer ce document : Ladouceur, E. (Auteur de correspondance), Bonomi, C., Bruelheide, H., Klimešová,, J., Burrascano, S., Poschlod, P., Tudela-Isanta, M., Iannetta, P., Mondoni, A., Amiaud, B., Cerabolini, B.

E. L., Cornelissen,, J. H. C., Craine, J., Louault, F., Minden, V., Öllerer, K., Onipchenko, V., Soudzilovskaia, N. A., Jiménez-Alfaro, B. ( 2019). The functional trait spectrum of European

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specialist with a high clonal spread rate. Human assisted dispersal was proportionally less present in calcareous alpine and acidic alpine grassland specialists than in other grassland types (Fig. S3 d). The traits of Nardus-dominated grassland specialists were similar to alpine specialists in terms of their non-regeneration traits, i.e. short height, low SLA and slow radial growth. They start flowering at a similar time to acidic, calcareous alpine, dry grasslands and generalists, but flowering for a similarly short length as both alpine grassland types, and much shorter time than dry grassland specialists (Table S9, P=0.01).

Nardus grassland specialists had the smallest seed mass by a large margin (s 2 = 28.30, P= <0.001, Table S10); a soil seed bank characterised by short-term persistent seeds (Table 2); and a high Tmin, but only differentiated from the very low Tmin of meadows (P=0.03, Table S11). There was higher proportion of seed shedding in late summer in Nardus-dominated (70%), calcareous alpine (79%) acidic alpine grasslands (79%) (Fig. S3 c), which was consistent with the marginally narrower window of germination temperatures available to specialists of these grassland types (Fig. 4 g-i).

Finally, both meadows and dry grasslands had the highest SLA, tallest plants, the fastest radial growth rates, and the earliest flowering onset and longest flowering duration compared to the other three, high-altitude habitats. Meadows also had a faster clonal lateral spread rate than calcareous alpine specialists (s 2 = 13.53, P= 0.018, Table S11).

Specialists of dry grasslands had a notably larger presence of physical dormancy (PY) (24%, Fig. S3 a) than other habitat types.

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E. L., Cornelissen,, J. H. C., Craine, J., Louault, F., Minden, V., Öllerer, K., Onipchenko, V., Soudzilovskaia, N. A., Jiménez-Alfaro, B. ( 2019). The functional trait spectrum of European

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DISCUSSION

The trait spectrum of European temperate grasslands

The main trait dimension of the temperate grasslands analyzed in this study is similar to the 'fast-slow' continuum described globally [START_REF] Reich | The world-wide "fast-slow" plant economics spectrum: a traits manifesto[END_REF][START_REF] Salguero-Gómez | Fast-slow continuum and reproductive strategies structure plant life-history variation worldwide[END_REF]) and to the latitude-driven first dimension of the global spectrum of vascular plants (Westoby 1998;[START_REF] Diaz | The global spectrum of plant form and function[END_REF]. The main gradient between fast-growing plants with high regeneration rates (on the right side of the PCA) and slow-growing plants with shorter flowering duration (on the left side) is likely driven by ecological differences in seasonal length and climate along the altitudinal range in which these species occur. We further found that regeneration traits including annual radial growth rate, clonal lateral spread, Tmax, and seed bank longevity also contribute to the fast-slow strategy.

The second axis of trait variation of European temperate grasslands suggests a leaf economic spectrum driven by environmental gradients, which is mainly explained by the contribution of SLA. Plant height, flowering onset and seed mass also contributed largely to the second axis, while on the third, fourth and fifth axes major contributions were related to regeneration traits such as To, Tmin, flowering duration, clonal shoot cyclicity, clonal index, clonal spread, and seed number. Similarly, [START_REF] Pierce | How well do seed production traits correlate with leaf traits, whole-plant traits and plant ecological strategies?[END_REF] found that reproduction traits affect plant survival independently from primary strategies, while Salguero-Gómez (2016) found that regeneration traits, such as degree of iteroparity and net reproductive rate, were perpendicular to the leaf economics spectrum. Other studies found weak correlation or even a lack of correlation between seed and clonal traits across a whole flora [START_REF] Herben | Species traits and plant performance: functional trade-offs in a large set of species in a botanical garden[END_REF][START_REF] Herben | Reproduction by seed and clonality in plants: correlated syndromes or independent strategies?[END_REF]. Our

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E. L., Cornelissen,, J. H. C., Craine, J., Louault, F., Minden, V., Öllerer, K., Onipchenko, V., Soudzilovskaia, N. A., Jiménez-Alfaro, B. ( 2019). The functional trait spectrum of European

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results therefore suggest that reducing the species pool to a unique formation (temperate grasslands) removes functional variation of distinct habitat types (such as forests, wetlands, etc.) that may confound the interpretation of habitat-specific trait dimensions. In addition, the use of traits representing different life-stage processes (regeneration and non-regeneration traits) provides a more comprehensive explanation of the observed functional patterns.

Trait differences between habitat specialists

Our results support the idea that environmental filtering and disturbance governs the functional composition of plant specialists related to temperate grassland types in Europe. Specialists of low-altitude disturbed and managed habitats are characterised by 'fast' traits such as greater height, SLA, longer flowering duration and increased radial growth rate. In contrast, the 'slow' traits stand out in specialists of harsh alpine habitats with less disturbance. The combination of all available traits discriminated grassland types better than considering non-regeneration or regeneration traits separately, supporting the multidimensional nature of plant traits for understanding environmental relationships [START_REF] Laughlin | The intrinsic dimensionality of plant traits and its relevance to community assembly[END_REF]. Nevertheless, we found weak functional differentiation between the high-altitude acidic and calcareous alpine grasslands, despite having distinct differences in soil conditions and species composition. Trait-based differences between these habitats have been found in germination traits related specifically to pH and water availability that require more experimental data [START_REF] Tudela-Isanta | Habitat-related seed germination traits in alpine habitats[END_REF] than is currently available for this entire species pool. Despite the comprehensive set of traits used in this study, the lack of more specific traits, reflecting e.g. physiological species responses, makes it possible to differentiate up to three major functional

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E. L., Cornelissen,, J. H. C., Craine, J., Louault, F., Minden, V., Öllerer, K., Onipchenko, V., Soudzilovskaia, N. A., Jiménez-Alfaro, B. ( 2019). The functional trait spectrum of European

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groups: (i) high-altitude grasslands (both acidic and calcareous grasslands); (ii) lowaltitude grasslands from disturbed habitats (dry grasslands and meadows); and (iii) mid-altitude Nardus-dominated grasslands (differentiated from (i) or (ii) depending on which trait is being examined).

The explanatory power of traits for differentiating habitat types was mainly related to non-regeneration traits and flowering, which are in general more underdispersed than would be expected randomly within each habitat, suggesting environmental filtering may be taking place on these traits. The regeneration traits of specialists showed more over-dispersion than expected randomly, varying more within than among grassland types, supporting the idea that a multitude of regeneration niches may coexist within the same grassland type [START_REF] Grubb | The maintenance of species-richness in plant communities: the importance of the regeneration niche[END_REF]. This suggests that regeneration traits may have a different ecological role than non-regeneration traits, such as the competitive niches of species, or coexistence mechanisms [START_REF] Mayfield | Opposing effects of competitive exclusion on the phylogenetic structure of communities[END_REF][START_REF] Hillerislambers | Rethinking Community Assembly through the Lens of Coexistence Theory[END_REF]). However, we found differentiation of soil seedbank longevity across habitats, which is likely influenced by traditional long-termmanagement practices such as regular mowing or grazing in meadows [START_REF] Bekker | Seed bank characteristics of Dutch plant communities[END_REF]Fenner & Thompson 2005). In addition, human dispersed seeds are less represented among alpine grassland specialists, demonstrating the importance of traditional management for seed dispersal [START_REF] Poschlod | Plant species richness in calcareous grasslands as affected by dispersability in space and time[END_REF][START_REF] Auffret | Can seed dispersal by human activity play a useful role for the conservation of European grasslands?[END_REF]) and the possible complementary effect of long-term disturbance regimes for understanding functional differentiation in these habitats [START_REF] Louault | Plant traits and functional types in response to reduced disturbance in a semi-natural grassland[END_REF][START_REF] Kahmen | Effects of grassland management on plant functional trait composition[END_REF]. Our results also suggest that clonal traits could be affected by abiotic and biotic filters such as disturbance and soil, which perhaps are clearer in wider gradients than

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Comment citer ce document : Ladouceur, E. (Auteur de correspondance), Bonomi, C., Bruelheide, H., Klimešová,, J., Burrascano, S., Poschlod, P., Tudela-Isanta, M., Iannetta, P., Mondoni, A., Amiaud, B., Cerabolini, B.

E. L., Cornelissen,, J. H. C., Craine, J., Louault, F., Minden, V., Öllerer, K., Onipchenko, V., Soudzilovskaia, N. A., Jiménez-Alfaro, B. ( 2019). The functional trait spectrum of European

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explored here [START_REF] Fujita | Low investment in sexual reproduction threatens plants adapted to phosphorus limitation[END_REF], so the extent of environmental filtering at different scales and gradients on these traits [START_REF] Klimešová | Clonal growth forms in Arctic plants and their habitat preferences: a study from Petuniabukta, Spitsbergen[END_REF][START_REF] Klimešová | Clonal and bud bank traits: patterns across temperate plant communities (S. Bartha[END_REF] is worth investigating further.

CONCLUSION

This study is, to our knowledge, the first attempt to investigate the trait variation of a continental species pool within a particular vegetation type. We found that the trait spectrum of European temperate grasslands is related to the main trade-offs observed at the global scale. However, our analyses also reveal new contributions of traits with a functional role in our study system, details that might be lost when analyzing the functional variation across distinct vegetation types. Since temperate grasslands are by definition dominated by grasses and forbs, the analysis of functional variation within this relatively homogeneous system allows us to focus on patterns and drivers linked with the specific differentiation of grassland types. Non-regeneration traits related to plant growth were mainly related to environmental gradients and disturbance across grasslands, while regeneration traits demonstrated a multitude of regeneration strategies existing within grassland types. We conclude that functional characterization of habitat specialists within species pools may be a promising approach for understanding the role of environmental filtering on trait-based ecology and vegetation diversity across large scales. However, this approach is also limited by the quality of plant traits available. Besides the integration of regeneration and non-regeneration traits, future research will need to explore traits with a stronger physiological impact on species ecological responses.

Comment citer ce document : Ladouceur, E. (Auteur de correspondance), Bonomi, C., Bruelheide, H., Klimešová,, J., Burrascano, S., Poschlod, P., Tudela-Isanta, M., Iannetta, P., Mondoni, A., Amiaud, B., Cerabolini, B.

E. L., Cornelissen,, J. H. C., J., Louault, F., Minden, V., Öllerer, K., Onipchenko, V., Soudzilovskaia, N. A., Jiménez-Alfaro, B. ( 2019). The functional trait spectrum of European

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This article is protected by copyright. All rights reserved. 2 for trait abbreviations). Grey arrows/labels represent non-regeneration traits and black arrows/labels regeneration traits. The five species that contribute the most variation to each axis are labelled in blue and detailed in Table S3. Percentages for the three main axes represent the explained variance. Each point represents a species, and each line shows its distance from the centre point of the data for each species group. a) Colored ellipses representing species belonging to each specialist group are separated by facets, detailed in the key; b) pooled specialists vs. generalists (See Table 1 for grassland type abbreviations). Degrees of freedom=5.

Figure 2 :

 2 Figure 2: Trait space of habitat specialists grouped in five grassland types and generalists. Sample scores representing 645 plant species in a Principal Component Analysis (PCA) for axis 1 & 2 based on numerical plant traits and a correlation matrix.Each point represents a species, and each line shows its distance from the centre point of the data for each species group. a) Colored ellipses representing species belonging to each specialist group are separated by facets, detailed in the key; b) pooled specialists vs. generalists (See Table1for grassland type abbreviations). Degrees of freedom=5.

Figure 3 :

 3 Figure 3: Non-regeneration traits across habitats. a) SLA, b) plant height, c) annual radial growth rate, d) flowering onset, e) flowering duration. RDI plots (Raw data, Descriptive and Inference statistics) show jittered points of raw data, centre bars indicate the mean of the data, beans outline the smoothed density of the data, whiskers mark the 10% and 90% quartiles of the data, and inference bands show the Bayesian 95% High Density Interval inferential statistics for each group. Numbers at the top of each group indicates the number of data points for each trait, and letters show statistical differences between groups.

Figure 4 :

 4 Figure 4: Regeneration traits across habitats. a) clonal lateral spread, b) clonal index (number of offspring + spread)and c) clonal shoot cyclicity, d) dry seed mass, e) seed number per ramet/plant, f) soil seed bank longevity, and seed germination traits g) minimum germination temperature, h) optimal germination temperature and i) maximum germination temperature. RDI plots as in Fig.3.

Table 1 : Description of the five grassland types investigated.

 1 Altitude shows estimated ranges above the sea level. Number of specialist species describes the total number of specialists identified for each grassland type. EUNIS and ANNEX I habitats and their management practices according to www.eunis.eea.europa.eu/habitats. Soil pH and moisture values are derived from the Ellenberg indicator values of each species(Fitter & Peat 1994; Sanda et al. 2003; Ciocârlan 2009; Moretti & Legg 2009; Ellenberg 2010; Hill et al.; Kattge; Öllerer), expressed as the mean of those specialists (Table2). VPL= vegetation period length(Aeschimann et al. 2004). Data sources listed in Appendix S2.Comment citer ce document : Ladouceur, E. (Auteur de correspondance), Bonomi, C., Bruelheide, H., Klimešová,, J., Burrascano, S., Poschlod, P., Tudela-Isanta, M., Iannetta, P., Mondoni, A., Amiaud, B., Cerabolini, B.

	Grassland type	Altitude	# of species specialist	classification (EUNIS) habitat Information System European Nature	EU Habitat Directive ANNEX I habitats of	practice management Traditional	Soil pH	moisture Soil	VPL
	Meadows	0-	57	E2.2 Low & Medium	Lowland Hay	Mowing,	6.9	4.78	March-
		1000m		altitude meadow E2.3	Meadows 6510 + High	(Grazing)	(neutral		October (8
				Mountain hay	Altitude Hay Meadows		)		months)
				meadows	6520
	Dry		77	E1.2 Perennial	Semi-natural Dry	Mowing &	7.3	3.2	March-
	Grasslands	500-		calcareous grassland	Grasslands (Festuco-	Grazing	(calcare		October (8
		1400m		and basic steppes	Brometalia) 6210		ous)		months)
	Nardus-	1400-	81	e1.7 Closed non-	Mountain acid	Grazing	4.39	5.8	May-
	dominated	1800m		Mediterranean dry	grassland Species Rich		(acidic)		September
				acid & neutral	Nardus Grasslands				(5
				grassland	6230				months)
	Calcareous	1800-	149	E4.4 Calcareous alpine	Alpine & subalpine	None	7.7	4.68	June-
	Alpine	2700m		and subalpine	calcareous grasslands		(calcare		August (3
				grassland	6170		ous)		months)
	Acidic	>2700m	52	4.3 Acid alpine and	Acidic Alpine	None	2.3	4.5	June-
	Alpine			subalpine grassland	grasslands 6150		(acidic)		August (3
									months)

E. L., J. H. C., Craine, J., Louault, F., Minden, V., Öllerer, K., Onipchenko, V., Soudzilovskaia, N. A., Jiménez-Alfaro, B. (

2019

). The functional trait spectrum of European

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Table 2 : Traits and environmental data used in this study.

 2 Methods and methods sources are indicated where relevant.. See extended version of this table including all data sources in Supporting Information Appendix 2.

	Figure/Trait	Type	Ecological significance	Method Indications
	Non-regeneration traits
	Specific leaf area (SLA)	Continuous	Growth rate
	(cm 2 /g)
	Plant height	Continuous	Competitiveness for light
	(cm)		resources, and chances to be
			grazed/mown
	Annual radial plant growth rate	Continuous	Growth
	(growth rate) (mm/year)
	Regeneration traits
	Flowering onset (month)	Ordinal	Sexual reproduction,	According to (Aeschimann et al. 2004)
			pollinator attraction
	Flowering duration (months)	Ordinal	Sexual reproduction,	According to (Aeschimann et al. 2004)
			pollinator support
	Clonal lateral spread (cm/year)	Continuous	Growth	The horizontal increment of the clonal
				growth organ (cm/year)
	Clonal index	Ordinal	Number of offspring +	Number of clonal offspring produced per
			spread	parent and year, and the clonal lateral
				spread combined (Johansson et al. 2010).
	Clonal shoot cyclicity (years)	Continuous	Turnover of shoots	The lifespan of a clonal shoot (years),
				starting from the sprouting of a bud,
				vegetative growth, flowering and fruiting,
				until shoot death (Klimešová & De Bello
				2009).

Comment citer ce document : Ladouceur, E. (Auteur de correspondance), Bonomi, C., Bruelheide, H., Klimešová,, J., Burrascano, S., Poschlod, P., Tudela-Isanta, M., Iannetta, P., Mondoni, A., Amiaud, B., Cerabolini, B.

E. L., Cornelissen,, J. H. C., Craine, J., Louault, F., Minden, V., Öllerer, K., Onipchenko, V., Soudzilovskaia, N. A., Jiménez-Alfaro, B. (

2019

). The functional trait spectrum of European

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This article is protected by copyright. All rights reserved.

Comment citer ce document : Ladouceur, E. (Auteur de correspondance), Bonomi, C., Bruelheide, H., Klimešová,, J., Burrascano, S., Poschlod, P., Tudela-Isanta, M., Iannetta, P., Mondoni, A., Amiaud, B., Cerabolini, B.

E. L., Cornelissen,, J. H. C., Craine, J., Louault, F., Minden, V., Öllerer, K., Onipchenko, V., Soudzilovskaia, N. A., Jiménez-Alfaro, B. (

2019

). The functional trait spectrum of European

ccepted Article

This article is protected by copyright. All rights reserved.

Comment citer ce document : Ladouceur, E. (Auteur de correspondance), Bonomi, C., Bruelheide, H., Klimešová,, J., Burrascano, S., Poschlod, P., Tudela-Isanta, M., Iannetta, P., Mondoni, A., Amiaud, B., Cerabolini, B.

E. L., Cornelissen,, J. H. C., Craine, J., Louault, F., Minden, V., Öllerer, K., Onipchenko, V., Soudzilovskaia, N. A., Jiménez-Alfaro, B. (

2019

). The functional trait spectrum of European

Table 3 :

 3 Loadings of the plant trait values for the first three axes of the PCA for: all traits and all species. Bold numbers indicate the top three (3)-five (5) highest loadings on each axis.

	a) All Traits	i) All species (Main Analysis)
		Axis 1	Axis 2	Axis 3	Axis 4	Axis 5
	Variance Explained	23.1	9.15	9.08	7.84	6.83
	Eigenvalue	3.23	1.28	1.27	1.1	0.96
	SLA	0.29	-0.30	0.05	0.07	0.06
	Plant height	0.27	0.49	0.09	0.19	0.25
	Radial growth rate	0.30	-0.04	0.07	0.1	-0.07
	Flowering onset	-0.29	0.36	0.33	0.05	-0.06
	Flowering duration	0.31	-0.32	-0.24	-0.27	0.25
	Clonal spread	0.28	0.18	0.26	-0.19	-0.40
	Clonal index	0.26	-0.07	0.38	-0.19	-0.46
	Clonal cyclicity	-0.25	0.1	0.22	-0.37	0.08
	Seed mass	0.16	0.34	-0.4	0.5	-0.2
	Seed # /ramet	0.24	0.34	0.27	-0.17	0.51
	Soil seed bank longevity	0.33	-0.04	0.08	-0.01	0.11
	T min	-0.18	-0.23	0.33	0.41	-0.15
	T o	-0.05	-0.3	0.43	0.43	0.37
	T max	0.37	-0.04	0.13	0.18	-0.12

Trait space of the functional species pool of European temperate grasslands.

  Sample scores representing 645 plant species in a Principal Component Analysis (PCA) based on numerical plant traits and a correlation matrix. Each point represents a species, arrows represent the visualisation of the contributing variables (See Table

Acknowledgements

EL, BJA, MTI, AM, PI and CB acknowledge the research leading to these results has received funding from the People Programme (Marie Curie Actions) of the European Union's Seventh Framework Programme FP7/2007-2013/ under REA grant agreement n°607785-as a part of the NAtive Seed Science TEchnology and Conservation (NASSTEC) Initial Training Network (ITN). BJA was further funded by the Marie Curie Clarín-COFUND program of the Principality of Asturias and the European Union (ACB17-26). BJA, and HB acknowledge support from the German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig funded by the German Research Foundation (DFTG FZT 118) through the sPlot research platform. PI acknowledges support from the Rural & Environment Science & Analytical Services Division of the Scottish Government. KÖ thanks RO1567-IBB03/2018 for financial support.

EL, BJA, MTI, AM, PI and CB acknowledge the research leading to these results has received funding from the People Programme (Marie Curie Actions) of the European Union's Seventh Framework Programme FP7/2007-2013/ under REA grant agreement n°607785-as a part of the NAtive Seed Science TEchnology and Conservation (NASSTEC) Initial Training Network (ITN). BJA was further funded by the Marie Curie Clarín-COFUND program of the Principality of Asturias and the European Union (ACB17-26). BJA, and HB acknowledge support from the German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig funded by the German Research Foundation (DFTG FZT 118) through the sPlot research platform. PI

Data Accessibility

Most data were collected from donated existing databases within the TRY Global Plant Trait Database (Table 2, & Supporting Information Appendix S2). Mean values of all trait data are detailed in Supporting Information Appendix S3 Table S1. Each individual dataset which was used to calculate the mean value of each trait is referenced individually in the extended version of Table 2, in Supporting Information Appendix S2.

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Author Contributions

BJA conceived the idea. EL, CB and BJA designed the methodology, and arranged acquisition of data. BA, SB, BC, JHC, JC, JK, FL, VM, AM, KÖ, VO, PP, NS, MTI, donated substantial amounts of data. EL lead data analysis and writing of the manuscript. BJA, HB, JK, SB, PP, MTI, PI, AM and CB contributed critical feedback to data interpretation and initial drafting of the manuscript. All authors made intellectual contributions and provided essential feedback. The first nine authors, and last author are ordered by their relative contribution, the others are ordered alphabetically.

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Supporting Information

Additional supporting information may be found in the online version of this article.

Appendix S1: Statistical results, species trait summary, Table S2-Table S11 supporting figure descriptions Figure S1-Figure S3 Appendix S2:


O Tingaud

R Etchart-Salas

V Rat

J.-F Coudert

H Ageorges

A Grimaud

A Denoirjean

P Fauchais

G Montavon

N Caron

S Alexandre

Suspension Plasma Spraying of Zirconia Coatings: Process and Coating Structure

Keywords: Suspension Plasma Spraying, suspension injection, coating structure

Suspension plasma spraying (SPS) permits to manufacture finely structured coatings (nano-or submicron-sized) coatings. Compared to conventional plasma spraying, SPS exhibit several major differences: i) a more pronounced sensitivity to arc root fluctuations; ii) a shorter spray distance; iii) a higher thermal flux transmitted from the plasma flow to the substrate. Several operating parameters play relevant roles in the suspension processing and the coating architecture.

Introduction

Several emerging technologies include in their design finely structured layers (nano-or micron-sized) such as environmental barriers for photocatalytic applications (anatase-TiO 2 , γ-Al 2 O 3 , etc.), electric insulation for solar energy generators (Al 2 O 3 , (MgO) 2 (Al 2 O 3 ) 2 (SiO 2 ) 5 , etc.), ionic and electronic conductions for Solid Oxy-Fuel Cells (SOFC) (ZrO 2 -7Y 2 O 3 , perovskites, etc.), etc. Those layers should be manufactured on large surfaces and should ideally exhibit thicknesses ranging from 10 to 50 µm, average values. Moreover, those layers should also exhibit a large variety of architectures, from dense and gas-tight ones to very porous ones.

Producing finely-structured "thick" layers by thermal spraying, in particular plasma spraying when considering refractory feedstock, requires reducing the feedstock particle average size. Conventionally, those particles are carried out to the plasma jet via a carrier gas and injected radially a few millimeters downstream from the exit of the plasma torch. In such a configuration, the momentum imparted to the particles has to be of the same order than the momentum density imparted to the plasma flow. When reducing the average particle diameters, the particle velocity has to be increased in order to maintain as constant as possible the particle momentum. While the decrease in the injector internal diameter to increase the carrier gas velocity reaches technological difficulties that cannot be solved (injector plugging), the increase in the carrier gas flow rate leads to the plasma jet disruption by the cold carrier gas flow as the required flow rate reaches very high values (in the order of one fourth of the plasma forming gas mass flow rate) when considering injected particle diameters smaller than 5 µm.

Suspension Plasma Spraying (SPS) [1][START_REF] Wittman | Proc. ITSC 2002 conf[END_REF] aims at circumventing the previously detailed technological limitations. In this process, a stabilized suspension, made of a liquid, solid particles and a dispersant, is injected within the plasma flow. The liquid is very quickly vaporized and the individual particles, or the particle agglomerates, depending on the average size of the solid feedstock, are heated and simultaneously accelerated towards the substrate surface were they impact, spread and solidify, analogously in a first approximation to larger particles, to form a layer.

Major mechanisms occurring in SPS

Two technological routes can be used to inject a liquid within a plasma flow, either pneumatic injection (based on a secondary atomization of a liquid stream within a dedicated nozzle by a secondary plasma gas flow) or mechanical injection (based on the injection within the plasma flow of a continuous liquid stream). From the first route results a divergent stream of liquid droplets (characterized by broad particle size and velocity distributions) which heavily disturb the plasma flow and which does not lead to a homogeneous treatment of the droplets into the plasma flow, resulting in layers exhibiting heterogeneous, non-cohesive and porous structures. The second route is based on pressurized tanks associated to an injector of diameter varying from 50 to 300 µm, depending on the characteristics of the liquid and its flow rate. This permits to sow the plasma jet with a liquid without disturbing the flow. The droplet treatment which results is hence more homogeneous, as are the structures of the produced layers. This second solution will be exclusively considered in the following.

The suspension can be injected either radially [1] or axially [START_REF] Oberste-Berghaus | Proc. ITSC 2005 conf[END_REF] to the plasma flow, depending on the plasma torch design. In the following, only the case of a radial injection will be considered and discussed, that is to say suspension plasma spraying implementing a direct current stick-type cathode plasma torch.

Several natures of liquid can be used as carrier. The first developments used de-ionized water [1][START_REF] Wittman | Proc. ITSC 2002 conf[END_REF] but most of the works nowadays consider ethanol since the enthalpy of vaporization of this latter fluid is lower than that of water (0.84 MJ.kg -1 to be compared to 2.26 MJ.kg - 1 ). Of course, one has to consider also the other sources of energy dissipation corresponding to vapor molecular decomposition and atomic ionization before mixing with the plasma flow species.

The required condition for the continuous liquid stream to penetrate the plasma flow is that its momentum density has to be higher than the one of the plasma flow, that is to say:

2 plasma plasma 2 liquid liquid V V ρ > ρ (1)
where ρ liquid and ρ plasma represent the specific mass of the carrier and the plasma, respectively, and V liquid and V plasma the velocity module of the liquid and the plasma, respectively.

Upon penetration within the plasma flow, the liquid stream will encounter two mechanisms, fragmentation and vaporization [START_REF] Gelfand | [END_REF]. In a first approximation, one can say that whatever the characteristic dimension of the liquid stream fragmentation occurs before vaporization; the characteristic time of this latter mechanism being two order of magnitude higher than the one related to fragmentation. This signifies that the liquid stream encounters fragmentation upon penetration within the plasma flow to form liquid droplets. Those droplets evaporate in a second time. Indeed, the fragmentation occurs for a liquid flow characteristic dimensionless Weber number, We, higher than 12-14 [START_REF] Gelfand | [END_REF]. We represents the ratio of inertia forces to surface tension ones and is expressed as follows:

liquid liquid 2 liquid d . V . We σ ∆ ρ = (2)
where ρ liquid represents the liquid specific mass, d liquid the liquid stream characteristic dimension (average diameter), σ liquid the liquid surface tension (considered in the calculation at ambient temperature in contact with air at ambient pressure) and ∆V the difference in velocities between the liquid stream and the plasma flow. From a practical point of view, such a threshold of 12-14 for the dimensionless Weber number is reached at the fringes of the plasma jet. This signifies that depending upon their momentum liquid droplets will penetrate more or less into the plasma flow. For the ones with lower momentums, they will very likely travel at the fringes of the flow where the solvent will be evaporated but the droplet content will be poorly treated. The fragmentation of the liquid stream at the earliest interactions with the plasma flow is also promoted by the plasma instabilities which result mostly from the arc root fluctuations [START_REF] Heberlein | Heat and Mass Trans. under Plasma Cond[END_REF].

The suspension characteristics also affect the fragmentation mechanism [6]. Indeed, the higher the suspension surface tension and dynamic viscosity, the more delayed the fragmentation.

The suspension injection velocity, that is to say the suspension stream momentum density, constitutes a third major operating parameter for suspension injection. Indeed, this velocity will drastically influence the dispersion of the droplet clouds within the plasma flow [START_REF] Etchart-Salas | Proc. ITSC 2007 conf[END_REF]: the higher the suspension injection velocity, the lower the dispersion angle of the droplet cloud within the plasma flow. Decreasing the droplet cloud dispersion angle within the plasma flow permits to decrease the droplet flow pattern upon impact onto the substrate while increasing the homogeneity of their treatment within the plasma flow.

When considering the processing of droplets by the plasma flow, one has to consider the solid particle average size. Either the suspension is made of nano-sized particles (about 200 nm, average diameter) or of micron-sized particles (about 1 µm, average diameter). Considering a suspension of nano-sized particles, one can envisage the following scenario [6]: i) once fragmentation of the liquid stream has occurred, solvent begins to evaporate; ii) the evaporation of the solvent leads to the formation of micron-sized aggregates made of nano-sized particles; iii) these aggregates are not stable within the plasma flow and desegregate into smaller aggregates; iv) the smaller ones are very likely totally or partially vaporized whereas the larger ones melt to form small liquid particles which impact, spread and solidify to form flattened lamellae of equivalent diameters in the order of the micrometer. One can envisage the following scenario for the processing of a suspension made of micron-sized particles [6]: i) once fragmentation of the liquid stream has occurred, solvent begins to evaporate; ii) the evaporation of the solvent leads to the formation of aggregates constituted by a few particles; iii) these aggregates melt and form liquid particles which impact, spread and solidify to form flattened lamellae of equivalent diameters in the order of a few micrometers.

As the vaporization of the liquid phase and the dissociation and ionization of resulting species very significantly decreases the enthalpy of the plasma, this leads to a very significant decrease in the plasma core size: the interaction time between the plasma flow and the droplets / particles is decreased. Moreover, as the particles to be processed exhibit small diameters, their thermal inertia as well as their inertia are much lower than they are for larger particles and their velocity and temperature very quickly decrease when they exit the plasma jet and interact with the surrounding colder atmosphere. As a result, the stand-off distance has to be adjusted compared to conventional plasma spraying. Depending on the operating parameters, the suspension characteristics and the particle sizes, the stand-off distance varies from 35 to 50 mm. A consequence of this relatively short stand-off distance is the increase in the heat flux transmitted from the plasma and the recombined gases to the substrate. The higher heat fluxes transferred to substrates due to shorter stand-off distances will modify the sprayed layer characteristics as solidification kinetic of the first deposited layers will be lowered compared to conventional plasma spraying. This significantly modifies their structure which evolves, at the microscopic scale, from a layered architecture for conventional plasma spraying to first a dendritic and then a granular one for suspension plasma spraying (Fig. 1) [START_REF] Delbos | Proc. ITSC 2002 conf[END_REF].

Collected flattened particles onto polished substrates are characterized by [6]: i) almost the absence of peripheral projections around the lamellae. This signifies that the dimensionless flattening Sommerfeld number, K f , is lower than 6 [START_REF] Fauchais | [END_REF]; ii) the absence of intralamellar cracks within the lamellae, a contrario to Al 2 O 3 lamellae collected under conventional plasma spray conditions, indicating that the residual quenching stress developing within the lamellae upon rapid solidification and cooling is lower than the intrinsic mechanical resistance of Al 2 O 3 .

The most surprising is very likely to be able to collect a significant quantity of such lamellae onto a substrate. Indeed, the condition for the in-flight particles to impact the substrate instead of following the gas stream flowing parallel to the substrate surface due to their low inertia is that their dimensionless Stockes number be higher than 1. The dimensionless Stockes number is defined as follows:

BL g p 2 p p e V d St µ ρ = ( 7
)
where ρ p represents the particle specific mass, d p its average diameter upon impact and V p its impact velocity. µ g is the gas dynamic viscosity and e BL the average thickness of the boundary layer developing at the substrate surface. This signifies that, depending on the particle size distribution resulting from the suspension stream fragmentation and the processing of the liquid droplets within the plasma jet, particles will impact more or less farer from the gun centerline axis. From a practical point of view, the larger particles characterized by dimensionless Stockes numbers higher than 1 will impact in the center of the particle flow pattern whereas the ones characterized by dimensionless Stockes numbers close to 1 will impact at the periphery of the particle flow pattern. From this specific particle flow pattern, proportionally more extended compared to conventional plasma spraying, results the following coating manufacturing sequence [START_REF] Etchart-Salas | Proc. ITSC 2007 conf[END_REF]: i) the bottom part of the deposited layer results from the stacking of small lamellae issuing from the periphery of the particle flow pattern; ii) the intermediate part of the deposited layer, representing most of the thickness due to the density of larger impinging particles, is then built-up; iii) the upper part of the deposited layer results once again from the stacking of small lamellae issuing from the periphery of the particle flow pattern. Such a sequence generates specific interpass stacking defects as depicted in Fig. 2.a. When adjusting suspension injection conditions to reduce the droplet dispersion within the plasma flow (Fig. 2.b) and when adjusting plasma torch operating mode from the restrike to the takeover one (Fig. 2.c) to reduce even further these dispersions [START_REF] Etchart-Salas | Proc. ITSC 2007 conf[END_REF], the density of stacking defects can be reduced. Finally, the adjustment of the kinematics of the spray torch in front of the substrate permits to reduce these inter-pass stacking defects and to produce typical structures as the one depicted in cracks(considering the picture resolution, this corresponds to crack sizes larger than 0.15 µm).

Effects of suspension characteristics on ZrO 2 coating architecture

A stabilized suspension is made of: i) a liquid carrier (water or ethanol are the most used ones); ii) a dispersant (electrostatic, stearic or electrostearic dispersant); iii) solid precursor particles, either nano-sized or micronsized.

Depending on their manufacturing process, solid precursors will exhibit different particle morphologies, average sizes and particle size distributions. Those characteristics will influence the suspension characteristics, for example in terms of the dispersant mass fraction. Moreover and as already underlined in section 2, the droplet treatment by the plasma flow and its evolution towards molten particles will depend upon the average sizes of the solid precursor particles. In such a way, the particle size distribution of the precursors will play a relevant role into their treatment by the plasma flow and hence onto the layer manufacturing mechanism. Beside the average size itself (nano-or micron-sized particles), two cases have to be considered, either a broad particle size distribution or a narrow one. When operating a suspension made of a solid precursor with a narrow particle size distribution, the treatment of the droplets and then of the resulting molten particles will be similar. This will result in a homogenous coating architecture. On the opposite, when operating a suspension made of a solid precursor with a broad particle size distribution, the treatment of the droplets and then the resulting molten particles will be dissimilar. In particular, some small aggregates made of the smallest particles will be easily vaporized since in this case, the plasma operating parameters will have been optimized to process larger particle diameters. This could results in the stagnation of vapors in the vicinity of the substrate which would generate stacking defects leading to heterogeneous structures. These effects are illustrated in Fig. 3 which displays two coating architectures manufactured from two suspensions made of solid precursors exhibiting dissimilar particle size distributions: the broader the particle size distribution, the more heterogeneous the coating architecture [6][START_REF] Etchart-Salas | Proc. ITSC 2007 conf[END_REF][START_REF] Delbos | Proc. ITSC 2002 conf[END_REF].

Conclusion

SPS present a large interest to manufacture under atmospheric conditions "thick" (10 to 50 µm) finelystructured layers onto large surfaces.

This process, under development, requires a very tight control of the operating conditions and pertinent technological solutions. Among the major extrinsic operating parameters to be considered, one can cite: i) the mechanical (pneumatic) injection which proved to less perturb the plasma flow and permit a more homogeneous treatment of the suspension within the plasma jet; ii) the characteristics of the suspension. Ethanol as liquid carrier, compared to de-ionized water for example, requires less energy to be vaporized; iii) the particle size distribution from which derives in part the coating pore architecture. Narrow particle size distribution will promote dense coatings whereas broad particle size distributions will promote porous coatings; iv) the injection conditions which aims at providing the suspension stream with a momentum density higher than the plasma flow momentum density. The higher the suspension energy density, the lower the dispersion of the fragmented droplet cloud within the plasma flow and the more homogeneous the droplet plasma treatment; v) the arc root fluctuations which significantly affect the suspension plasma treatment. The take-over operating mode has to be favored by selecting mono-atomic plasma gas species; vi) the short stand-off distance which increases the thermal transfer to the substrate and modifies in turn the coating architecture; vii) the kinematics which has to be optimized to reduced the stacking defect density.

Fig. 2 Fig. 1 .

 21 Fig. 1. SPS ZrO 2 layer architecture (micron-sized particles, ethanol-based suspension, suspension load: 20 wt.%, Ar-H 2 -He plasma, 40-10-50 SLPM, arc current intensity: 500 A, anode internal exit diameter: 6 mm, stand-off distance: 40 mm) [8].

Fig. 3 .

 3 Fig. 3. ZrO 2 coating architectures manufactured from two suspensions made of solid precursors exhibiting dissimilar particle size distributions [8].

Acknowledgments

SPCTS -UMR CNRS 6638 is a corresponding research laboratory of the Commissariat à l'Energie Atomique -Direction des Affaires Militaires (LRC CEA-SPCTS M08

), the financial support of which is gratefully acknowledged.