Nicolas Loiseau
email: nicolas.loiseau1@gmail.com

Claude Elisabeth Payri

Lydiane Mattio

Serge Andréfouët

Mary Grellier

Mayalen Zubia

M Zubia1

Functional convergence in macroalgal assemblages of isolated coral reefs in the Mozambique Channel

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

Introduction

Coral reefs are highly complex ecosystems that shelter an exceptional biodiversity and provide critical goods and ecological services [START_REF] Moberg | Ecological goods and services of coral reef ecosystems[END_REF][START_REF] Cinner | Comanagement of coral reef social-ecological systems[END_REF][START_REF] Mora | Ecological limitations to the resilience of coral reefs[END_REF]. Macroalgae are key components of coral reef communities providing essential ecological functions such as primary production, provision of trophic resources, nutrient retention and recycling, stabilization of the reef structure through calcification, contribution to sand formation, and provision of habitats, including nursery areas for juvenile fish [START_REF] Fong | Coral reef algae in coral reefs: an ecosystem in transition[END_REF][START_REF] Koch | Climate change and ocean acidification effects on seagrasses and marine macroalgae[END_REF][START_REF] Evans | Importance of macroalgal fields as coral reef fish nursery habitat in north-west Australia[END_REF].

Coral reefs worldwide are in serious decline owing primarily to overfishing [START_REF] Paddack | Recent region-wide declines in Caribbean reef fish abundance[END_REF], pollution (De'ath and Fabricius 2010), invasive species [START_REF] Kulbicki | Distributions of Indo-Pacific lionfishes Pterois spp. in their native ranges: implications for the Atlantic invasion[END_REF], and climate change [START_REF] Munday | Climate change and the future for coral reef fishes[END_REF][START_REF] Graham | Managing resilience to reverse phase shifts in coral reefs[END_REF]. Phase shifts towards macroalgae-dominated system have followed coral loss in several areas [START_REF] Diaz-Pulido | High CO 2 enhances the competitive strength of seaweeds over corals[END_REF][START_REF] Koch | Climate change and ocean acidification effects on seagrasses and marine macroalgae[END_REF][START_REF] Ainsworth | Climate change disables coral bleaching protection on the Great Barrier Reef[END_REF]. Investigating the ecological processes that may facilitate these changes is of key importance [START_REF] Bittick | Bolstered physical defences under nutrient-enriched conditions may facilitate a secondary foundational algal species in the South Pacific[END_REF]) and these macroalgal 1 phase shifts have been fairly well documented in some cases [START_REF] Done | Phase shifts in coral reef communities and their ecological significance in the ecology of Mangrove and related ecosystems[END_REF][START_REF] Carassou | Does herbivorous fish protection really improve coral reef resilience? A case study from New Caledonia (South Pacific)[END_REF][START_REF] Doropoulos | Sensitivity of coral recruitment to subtle shifts in early community succession[END_REF]. Most studies dedicated to the description of macroalgal communities have been based on taxonomical inventories and analyses of species richness [START_REF] Payri | Benthic algal and seagrass communities in Baa atoll, Maldives[END_REF][START_REF] Keith | Global diversity of marine macroalgae: environmental conditions explain less variation in the tropics[END_REF][START_REF] Mattio | Marine flora of the Iles Eparses (Scattered Islands): a longitudinal transect through the Mozambique Channel[END_REF]). However, it is now widely acknowledged that functional diversity is a great addition to the traditional taxonomical approaches for assessing species assemblages (Diaz and Cabido 2001;[START_REF] Violle | Let the concept of trait be functional![END_REF][START_REF] Stuart-Smith | Integrating abundance and functional traits reveals new global hotspots of fish diversity[END_REF][START_REF] Loiseau | Indices for assessing coral reef fish biodiversity: the need for a change in habits[END_REF]. Functional diversity has the potential to link morphological, physiological, and phenological variations at the individual level (i.e. functional traits) to ecosystem processes and patterns [START_REF] Violle | Let the concept of trait be functional![END_REF]) but also to reveal the impact of disturbances on community [START_REF] Mouillot | A functional approach reveals community responses to bances[END_REF].

The capacity of each macroalgal species to contribute to ecosystem processes depends on several biological traits related to growth, primary productivity, fixation to the substrate, and reproduction [START_REF] Littler | Morphological form and photosynthetic performances of marine macroalgae: tests of a functional/form hypothesis[END_REF][START_REF] Littler | The evolution of thallus form and survival strategies in benthic marine macroalgae: field and laboratory tests of a functional form model[END_REF][START_REF] Littler | Evolutionary strategies in a tropical barrier reef system: functional-form groups of marine macroalgae[END_REF][START_REF] Steneck | A functional group approach to the structure of algal-dominated communities[END_REF][START_REF] Lotze | Ecophysiological traits explain species dominance patterns in macroalgal blooms[END_REF][START_REF] Griffin | Functional diversity predicts overyielding effect of species combination on primary productivity[END_REF].

Most flora trait-based studies have targeted terrestrial plants, while the analysis of functional traits in marine vegetated ecosystems, particularly macroalgal communities, is still in its infancy (see [START_REF] Jänes | Functional traits of marine macrophytes predict primary production[END_REF] for temperate macrophytes). In addition, a few studies that focused on macroalgae functional diversity have only grouped together species sharing broadly similar physiological or morphological characteristics [START_REF] Littler | Morphological form and photosynthetic performances of marine macroalgae: tests of a functional/form hypothesis[END_REF]Littler 1980, 1984;[START_REF] Littler | Evolutionary strategies in a tropical barrier reef system: functional-form groups of marine macroalgae[END_REF][START_REF] Steneck | Feeding capabilities and limitation of herbivorous molluscs: a functional group approach[END_REF][START_REF] Steneck | A functional group approach to the structure of algal-dominated communities[END_REF][START_REF] Cheal | Coral-macroalgal phase shifts or reef resilience: links with diversity and functional roles of herbivorous fishes on the Great Barrier Reef[END_REF][START_REF] Balata | Testing a new classification of morphological functional groups of marine macroalgae for the detection or responses to disturbance[END_REF]. This method assumes that all species belonging to the same functional group interact the same way with the ecosystem, although these broadly defined groups may include species with significant differences that were not taken into account (i.e., groups ignores all the differences between species belonging to the same group, whereas these differences may be important, [START_REF] Petchey | How do different measures of functional diversity perform?[END_REF][START_REF] Ricotta | A note on functional diversity measures[END_REF][START_REF] Petchey | Functional diversity: back to basics and looking forward[END_REF]. Assessing the functional diversity using pre-defined functional groups can be problematic, because the user's choices can be subjective [START_REF] Chapin | Plant functional types as predictors of transient responses of arctic vegetation to global change[END_REF]Diaz and Cabido 2001). Hence, the defining group and the number of groups from an arbitrary grouping protocol can produce non-desirable variabilities. This method distorts the representation of the functional diversity [START_REF] Petchey | Functional diversity (FD), species richness and community composition[END_REF] and the conclusions that are made about the processes structuring communities. In macroalgae, all Halimeda species belong to the same functional group (calcareous group, [START_REF] Littler | The evolution of thallus form and survival strategies in benthic marine macroalgae: field and laboratory tests of a functional form model[END_REF], while some of them have very different ecological niches (e.g., sandy areas vs hard substratum). Describing the functional niche of macroalgae species and assemblages requires the consideration of an exhaustive set of functional traits. Only a few studies (and none to our knowledge in coral reef ecosystems) have assessed the structure of functional diversity using a macroalgal functional trait database [START_REF] Griffin | Functional diversity predicts overyielding effect of species combination on primary productivity[END_REF].

In this paper, we address this gap by applying a functional trait-based approach to coral reef macroalgal communities at three remote coral reefs characterized by a preserved environment. We first describe the coral reef macroalgae functional niches using the selected categorical traits as a proxy of continuous measurement for their functional niches. We then apply a multicomponent approach to beta diversity (taxonomic and functional beta diversity) for investigating the structure of functional traits at two spatial scales: among reefs and among sites (within reefs). This two-scale approach has been shown to reveal the spatial scaling of ecological factors and to provide useful information for conservation planning. In doing so, we also assess the relationship between beta diversities and geomorphology, depth and swell exposure. Finally, we discuss how functional traits can be used to better understand macroalgae distribution and how these results could help with the management of conservation area.

Materials and methods

Study area

Three coral reefs of the Îles Éparses (Scattered Islands) were sampled: Europa, Glorioso (Glorieuses), and Juan de Nova (Fig. 1). With an exceptional biodiversity and preserved ecosystems, the Îles Éparses offer a unique opportunity to analyze the distribution and structure of functional traits in macroalgal communities' (for a thorough description of the Îles Éparses protection status, environmental conditions, and species inventories, see the special issue: [START_REF] Quétel | Iles Eparses (SW Indian Ocean) as reference ecosystems for environmental research[END_REF].

The Îles Éparses are among the last sanctuaries of marine and terrestrial tropical biodiversity in the South Western Indian Ocean. Their geographic isolation and very limited past human occupation have largely preserved these territories [START_REF] Quétel | Iles Eparses (SW Indian Ocean) as reference ecosystems for environmental research[END_REF]). Together, Europa, Glorioso and Juan de Nova harbor 2% and 7% of the reefs' geomorphological unit's diversity, worldwide, and in the western-central Indian Ocean, respectively [START_REF] Andréfouët | Atlas des récifs coralliens de l'Océan Indien Ouest Atlas of Western Indian Ocean Coral Reefs Centre IRD de Nouméa[END_REF].

Sampling strategy

We used data from the taxonomic inventory of the three reefs published by [START_REF] Mattio | Marine flora of the Iles Eparses (Scattered Islands): a longitudinal transect through the Mozambique Channel[END_REF].

Macroalgae were collected from a total of 16 sites at Europa (December 2011), 26 sites at Glorioso (December 2012), and 27 sites at Juan de Nova (December 2013) (Mattio et al. 2016, Fig. 1). All collections were made during the same season (Austral summer) to produce comparable data sets. Sites were chosen based primarily on satellite images to include most of the major geomorphological units (geomorphological habitats) found between the intertidal zone and 20 m deep (see [START_REF] Payri | Benthic algal and seagrass communities in Baa atoll, Maldives[END_REF] for a description of methods). Specimens were collected from the following geomorphological units: forereef, mangrove, reef flat, shallow terrace, and deep terrace (Fig. 1). Only reef flat and forereef habitat were present at the three reefs, the "deep terrace" habitat was found at Glorioso and Juan de Nova only, and Europa was the only reef with mangroves [START_REF] Zubia | Benthic cyanobacterial diversity of Iles Eparses (Scattered Islands) in the Mozambique Channel[END_REF], Table S1). In addition to the geomorphological information, we recorded depth and interpreted swell exposure from the geographical position of each site considering the direction of the dominant swell (see supplementary material Table S1).

At each site, the sampling effort was standardized by searching during 60 min over a 10 × 50 m surface area within the same habitat [START_REF] Mattio | Marine flora of the Iles Eparses (Scattered Islands): a longitudinal transect through the Mozambique Channel[END_REF]. During this time, we randomly searched all the possible species and all the different encountered species were collected. Samples were sorted, photographed, labeled with a preliminary field identification, and pressed the same day. The available taxonomic inventories accounted for a total of 316 macroalgae, 134 for Europa, 170 for Glorioso, and 157 for Juan de Nova [START_REF] Mattio | Marine flora of the Iles Eparses (Scattered Islands): a longitudinal transect through the Mozambique Channel[END_REF].

Macroalgae functional traits

Based on the literature and our taxonomic expertise, we compiled a functional trait database using ten traits that describe the main aspects of macroalgal ecology. These traits were selected for their relevance in the investigation of the functional diversity of macroalgae, but also because they were available or could be inferred for a wide range of species (Table 1), providing proxies of the functional niche of each taxonomic unit. Following [START_REF] Kissling | Towards global data products of Essential Biodiversity Variables on species traits[END_REF], we selected traits related to four of the five critical functions that describe the functional diversity of species: phenology, morphology, physiology, and movement. Because continuous value was unavailable for most species, we choose to use categorical traits as a proxy of continuous measurement for Mapping data were extracted from the Millennium Coral Reef Mapping Project [START_REF] Andréfouët | Atlas des récifs coralliens de l'Océan Indien Ouest Atlas of Western Indian Ocean Coral Reefs Centre IRD de Nouméa[END_REF]. Different colors indicate geomorphological classes. At Europa, the site that appears inland is a mangrove site all traits. If no data are available for a specific species, we first used similarities across taxonomic levels. When trait information was not well known or not reported in the literature (e.g., production of repellent molecules), it was reported as "NA" in the database. We describe these traits below and provide the final database as a supplementary material (see Table S2 and Figure S2 for an illustration of assignment of functional traits).

Growth

It is an important component of macroalgal niches. Relative growth rate depends on the CO 2 assimilating capacity, carbon-use strategy [START_REF] Ho | Differential growth responses to water flow and reduced pH in tropical marine macroalgae[END_REF], and photosynthetic activity of the species. Macroalgae can be rapid and efficient initial colonizers of space on almost any area of coral reefs after disturbance [START_REF] Fong | Coral reef algae in coral reefs: an ecosystem in transition[END_REF]. Two main contrasted strategies have been observed: (1) opportunistic species with fast growth (F), high productivity, and high reproductive capacity, which are characteristics of pioneer macroalgae communities (e.g., turf); and (2) slow growing macroalgae (S) such as calcareous macroalgae (including Rhodophyta and Chlorophyta) or fleshy brown macroalgae [START_REF] Littler | The evolution of thallus form and survival strategies in benthic marine macroalgae: field and laboratory tests of a functional form model[END_REF]). These modalities have been assigned based on anatomical and morphological characteristics proposed by [START_REF] Littler | Morphological form and photosynthetic performances of marine macroalgae: tests of a functional/form hypothesis[END_REF], [START_REF] Littler | The evolution of thallus form and survival strategies in benthic marine macroalgae: field and laboratory tests of a functional form model[END_REF], [START_REF] Littler | Evolutionary strategies in a tropical barrier reef system: functional-form groups of marine macroalgae[END_REF]Steneck and[START_REF] Steneck | A functional group approach to the structure of algal-dominated communities[END_REF].

Mean height

The size has a primary role in defining the ecological niche of macroalgae [START_REF] Littler | The evolution of thallus form and survival strategies in benthic marine macroalgae: field and laboratory tests of a functional form model[END_REF][START_REF] Steneck | A functional group approach to the structure of algal-dominated communities[END_REF]. Size determines the energy requirements and the primary production of each species [START_REF] Littler | The evolution of thallus form and survival strategies in benthic marine macroalgae: field and laboratory tests of a functional form model[END_REF]. No: no proliferation record was found in the literature Yes: some records of proliferation.

Food web (primary producer) Coral resilience Repellent molecules

No: no production of repellent molecules Yes: production of repellent molecules

Defense against herbivory Regulation of competition

Size also determines the capacity of a particular species to provide a canopy that can be a habitat for other species [START_REF] Steneck | A functional group approach to the structure of algal-dominated communities[END_REF]. The size of a macroalgal species can also be an asset in the competition for space in coral reefs through coral-algae interactions. For the purpose of the present study, three modalities have been defined for this functional trait: small (< 2 cm), medium (2-5 cm), and high (> 5 cm) species.

Longevity

The role of macroalgae longevity in mediating marine biodiversity and ecosystem functioning has often been neglected [START_REF] Bracken | The underappreciated role of life history in mediating the functional consequences of biodiversity change[END_REF]. However, the longevity of macroalgae is closely related to their productivity (carbon fixed per gram of dry mass per hour) with generally greater longevity corresponding to lower productivity [START_REF] Steneck | A functional group approach to the structure of algal-dominated communities[END_REF]. Two modalities have been defined to represent this functional trait: annual (A) and perennial (P) species.

Primary productivity

Photosynthetic organisms harvest photons using pigments and use the excitation energy to fix CO 2 into biomass [START_REF] Berteotti | Increased biomass productivity in green algae by tuning non-photochemical quenching[END_REF]. The productivity of macroalgae plays an important role through the regulation of nutrient cycling and carbon cycling. Primary production is affected by many factors including physiological conditions, environmental characteristics, and season, but also by intrinsic factors of the organisms themselves. Hence, there is a very strong functional relationship between species morphology and primary production [START_REF] Littler | The evolution of thallus form and survival strategies in benthic marine macroalgae: field and laboratory tests of a functional form model[END_REF][START_REF] Payri | Production primaire et calcification des algues benthiques en milieu corallien[END_REF]. For this trait, four modalities were defined based on daily carbon production (e.g., 1 = low < 2mgC/g dw/day to 4: high > 40 mg C/g dw/day) following [START_REF] Payri | Production primaire et calcification des algues benthiques en milieu corallien[END_REF] (Table 1).

Calcification

The level of calcification is an important component that determines the ability to (1) avoid or limit grazing by fish or invertebrate, (2) cement fragmented rubbles or create rocky intertidal zones like algal crest, and (3) provide critical habitat for numerous other organisms [START_REF] Steneck | Feeding capabilities and limitation of herbivorous molluscs: a functional group approach[END_REF][START_REF] Littler | Evolutionary strategies in a tropical barrier reef system: functional-form groups of marine macroalgae[END_REF][START_REF] Pennings | Effect of plant toughness, calcification, and chemistry on herbivory by Dolabella auricularia[END_REF][START_REF] Mccoy | Coralline algae (Rhodophyta) in a changing world: integrating ecological, physiological, and geochemical responses to global change[END_REF]. For instance, non-geniculate coralline macroalgae (massive forms, e.g., Hydrolithon spp.) contribute to the cementation of reefs, while geniculate coralline macroalgae (articulated forms, e.g., Jania spp., Amphiroa spp.) or some green calcareous macroalgae (e.g., Halimeda spp.) contribute to the formation of sand [START_REF] Montaggioni | Chapter five patterns of carbonate production and deposition on Reefs[END_REF]. The mode and extent of calcification vary widely among the calcareous macroalgae, from low to heavily calcified species, which results in different functions.

For this trait, we defined four modalities relating to the level of calcification: "no", "low", "medium", and "high" following [START_REF] Payri | Production primaire et calcification des algues benthiques en milieu corallien[END_REF] (see Table 1).

Substratum

The substratum preferentially occupied by macroalgae is critical for determining macroalgal ecological niches. Each species has specific substratum affinities (bedrock, coral rubble, dead coral, live coral, and sand). [START_REF] Vieira | Toward an inordinate fondness for stars, beetles and Lobophora? Species diversity of the genus Lobophora (Dictyotales, Phaeophyceae) in New Caledonia[END_REF] also recently pointed out that different substrata create niche partitioning between the major lineages of the genus Lobophora spp. This trait is directly correlated with habitat characteristics and also influences the interaction and, potentially, the competition with other sessile species. For the purpose of this study, we distinguished three main substratum types: no substratum (epiphyte species), and hard and soft substratum (see Table 1).

Fixation strength

Macroalgae are attached (except for rare holopelagic species) to a substratum which can be hard (e.g., rocks) or soft (e.g., sand and rubbles). Some species are strongly attached (e.g., large brown macroalgae Sargassum spp. or tiny filamentous turf like Gelidiales) or loosely attached (e.g., Cladophora spp. and Boodlea spp.). The strength of fixation to the substratum has important implications for the species life histories as it can vary depending on the developmental stages and depth (e.g. Sargassum hornerii, [START_REF] Xu | Attachment strength of the subtidal seaweed Sargassum horneri (Turner) C Agardh varies among development stages and depths[END_REF].

Strong attachment, which can maintain macroalgae for long periods, provides three-dimensional habitat-building capacity like in brown macroalgae or Halimeda spp., which can form large meadows [START_REF] Rossier | A comparison of fish assemblages from two types of algal beds and coral reefs in the south-west lagoon of New Caledonia[END_REF]. Low fixation strength helps in species dispersal. We based this trait on the different fixation ways of species (e.g., bulbous holdfast, stupose holdfast, etc.). Considering the high diversity of holdfast type, we chose to use a proxy of "fixation strength". We distinguished three modalities corresponding to different strength of fixation ("low", "medium", and "high") using taxonomical descriptions and observations. Fixation strength was derived from each species' fixation type, assuming that, e.g., an encrusting calcified attachment to rocky substratum was stronger than, e.g., rhizoids in soft sand.

Interactions with substratum or benthic organisms

This trait is critical for determining the ecological niche of macroalgal species. It is directly correlated with habitat characteristics and macroalgal growth forms. The latter are associated with ecological features, particularly the level of interactions with other sessile organisms like corals. For example, encrusting growth forms are often found in interaction with live corals (e.g., Lobophora hederacea, [START_REF] Vieira | Matching names and clades in the brown algal genus Lobophora (Dictyotales, Phaeophyceae): an effort to integrate type specimens in modern taxonomy[END_REF]. We distinguished four modalities for this trait:

(1) whether they are "epiphyte" or not, and (2-4) depending on the shape of the species, four modes of epilithic interactions ranging from low contact (< 25%) when the contact zone is limited to the holdfast region (e.g., erect plants), to full contact (100%) for flat and encrusting species fully adhering to the substratum (see Table 1).

Ability to proliferate

Phase shifts to macroalgal dominance have been described worldwide (cf. introduction), pinpointing to the ability of macroalgae to proliferate following coral loss [START_REF] Greff | The interaction between the proliferating macroalga Asparagopsis taxiformis and the coral Astroides calycularis induces changes in microbiome and metabolomic fingerprints[END_REF]. The ability of species to proliferate has a direct impact on the fitness of reef organisms (recruitment, reproduction, etc.) and the resilience of coral reefs. Two modalities (no or yes) have been defined for this trait by considering the ecology of the species and by building a bibliographic synthesis.

Capacity of production of repellent molecules

The production of metabolite is a critical trait in macroalgae. Many macroalgae produce chemical defenses in response to herbivory, or against competitors and pathogens ( [START_REF] Hay | Marine plant-herbivore interactions: the ecology of chemical defense[END_REF]. The ability of macroalgae to avoid herbivory using allelopathic compounds has implication in the food web through both bottom-up and top-down controls [START_REF] Rasher | Chemically rich seaweeds poison corals when not controlled by herbivores[END_REF][START_REF] Rasher | Macroalgal terpenes function as allelopathic agents against reef corals[END_REF][START_REF] Rasher | Competition induces allelopathy but suppresses growth and anti-herbivore defence in a chemically rich seaweed[END_REF]. Two modalities (no or yes) have been defined for this trait by building a bibliographic synthesis and using the database MarinLit.

Out of the 316 macroalgal species recorded in this study, functional trait information was completely lacking for only two species, which were excluded from the analyses (Kallymenia sp. and Rhodopeltis sp). Further analyses were performed using the ten functional traits: five traits in relation to life-history strategy (growth, mean height, longevity, primary productivity, and calcification) and five ecological traits (substratum, fixation strength, interactions with substratum and benthic organisms, ability to proliferate, and repellent molecule production) (see Table 1).

Macroalgae functional space

Pairwise functional distances between functional entities (unique combination of functional trait modalities) were computed using the Gower distance, which allows mixing different types of variables while giving them equal weight [START_REF] Gower | A general coefficient of similarity and some of its properties[END_REF][START_REF] Podani | Extending gower's general coefficient of similarity to ordinal characters. Taxon, extending gower's general coefficient of similarity to ordinal characters[END_REF]. A Principal Coordinates Analysis (PCoA) was then performed using this functional distance matrix. [START_REF] Maire | How many dimensions are needed to accurately assess functional diversity? A pragmatic approach for assessing the quality of functional spaces[END_REF] demonstrated that the quality of the functional space (used to compute the functional beta diversity indices) can vary according to the number of dimensions/axes, the number of functional traits, and/or the nature of functional traits (quantitative or qualitative). They showed that using a poorly defined functional space could lead to erroneous ecological conclusions [START_REF] Maire | How many dimensions are needed to accurately assess functional diversity? A pragmatic approach for assessing the quality of functional spaces[END_REF][START_REF] Loiseau | Performance of partitioning functional beta-diversity indices: influence of functional representation and partitioning methods[END_REF]). To avoid these biases, we used the mean squared deviation (mSD) index [START_REF] Maire | How many dimensions are needed to accurately assess functional diversity? A pragmatic approach for assessing the quality of functional spaces[END_REF] to select the optimal functional space and, therefore, prevent the misinterpretation of beta functional diversity patterns. In our study, five dimensions provided the best balance between true distances and computing time for functional space.

Diversity indices

To reveal the functional structure of communities, we graphically represented the functional space of the three reefs (Europa, Glorioso, and Juan de Nova) and the distribution of species within this functional space. To investigate the structure of functional traits in macroalgal communities, we computed the mean trait value of a community weighted by the number of species (CWM, which remains robust when facing missing data, [START_REF] Májeková | Evaluating functional diversity: missing trait data and the importance of species abundance structure and data transformation[END_REF]. CWM reflects the values of the most dominant traits in a given community. It was calculated using the modified equation of [START_REF] Lavorel | Assessing functional diversity in the field-methodology matters![END_REF]:

where p ij is the number of species i in the community j, and T ij is the mean trait value of the species i in the community j. For qualitative traits (or binary), the modality that was the most represented in the community was considered as the dominant traits in the community.

Finally, to investigate the spatial distribution pattern of species and functional traits, we also computed the taxonomic and functional beta diversity at two spatial scales: among reefs and among sites (within reefs). To determine the relative contribution of turnover and nestedness-resultant to overall beta diversity (taxonomic and functional),

CWM j = n ∑ i p ij T ij ,
we used the additive partitioning of the pairwise Jaccard dissimilarity proposed by [START_REF] Baselga | Partitioning the turnover and nestedness components of beta diversity[END_REF][START_REF] Baselga | The relationship between species replacement, dissimilarity derived from nestedness, and nestedness[END_REF] and [START_REF] Villéger | Decomposing functional b-diversity reveals that low functional b-diversity is driven by low functional turnover in European fish assemblages[END_REF] based on functional space representation. Overall taxonomic and functional beta diversities (Sβ tot and Fβ tot , respectively) were decomposed into two components: turnover (Sβ tur and Fβ tur , respectively) and nestedness-resultant (Sβ nes and Fβ nes , respectively). Spatial turnover implies the replacement of some species by others as a consequence of environmental sorting and/or spatial and historical constraints [START_REF] Qian | Beta diversity of angiosperms in temperate floras of eastern Asia and eastern North America[END_REF]. The nestedness-resultant component measures differences in richness between assemblages nested to some degree [START_REF] Baselga | Comparing methods to separate components of beta diversity[END_REF][START_REF] Legendre | Interpreting the replacement and richness difference components of beta diversity[END_REF]. At large spatial scale (between reefs), to avoid biases on the value of beta diversity indices because of differences in sampling effort [START_REF] Cardoso | Testing the performance of beta diversity measures based on incidence data: the robustness to undersampling[END_REF][START_REF] Beck | Undersampling and the measurement of beta diversity[END_REF], we standardized the survey effort by randomly selecting 16 sites per reefs, 999 times. For each iteration, we computed beta diversity indices and used the average value of the indices. To graphically represent the values of beta diversity indices, we used principal coordinate analysis (PCoA). Standard deviation ellipses were projected on the ordination plot to visualize the multivariate dispersion in community composition in function of reefs.

Null model

We used a null model to investigate the potential presence of ecological factors that could drive the pattern of taxonomic and functional beta diversity. The null model simulated the compositional dissimilarity that would be expected in the absence of factors that would cause the clumping of species or species traits [START_REF] Chase | Using null models to disentangle variation in community dissimilarity from variation in B-diversity[END_REF][START_REF] Kraft | Disentangling the drivers of B diversity along latitudinal and elevational gradients[END_REF]). Null models were applied at two spatial scales, among reefs and among site (within reefs). For taxonomic beta diversity, we randomly assigned species to site holding constant both row sums (species incidences) and column sums (site species richness) as in the observed presence/absence matrix [START_REF] Ulrich | Null model analysis of species nestedness patterns[END_REF]. For functional beta diversity, we applied a randomization of functional traits (i.e., we reshuffled the species traits matrices). We reassigned randomly the observed trait combinations to species. This permutation process allowed keeping the flowing constant: (1) the species richness at each site or reef, (2) the taxonomic beta diversity and its components at each pair of reef/site, and (3) the pool of functional strategies (i.e., trait combinations). We then calculated a P value from the 999 iterations of null models [START_REF] Veech | Significance testing in ecological null models[END_REF]. More specifically, we derived the P value as the proportion of the null distribution of beta diversity that is more extreme than the observed beta diversity. If deterministic factors are absent or weak, we expect the observed beta diversities to range between 5 and 95% of the null distribution. In contrast, if niche-based processes prevail (limiting similarity), the observed beta diversity should be significantly different from the null distribution. Typically, beta diversity should be lower than expected at random (lower than 5% of the null distributions) if environmental filtering occurs. In contrast, if limiting similarity occurs, we expect the observed beta diversities to be higher than 95% of the null distribution. At large spatial scale, the observed beta diversities that are higher than the null distribution highlight a shift due to biotic or abiotic selections.

Data analysis

Beta diversity for both diversity components (taxonomic and functional) were analyzed with a permutational multivariate analysis of variance (PERMANOVA, 9999 permutations). For each reef, geomorphology, depth, and swell exposure were analyzed as the source of variation in beta diversity. All statistical analyses and data manipulations were carried out in R 3.3.1 (R Development Core Team 2016). In addition to the core software, the 'vegan' [START_REF] Oksanen | Vegan: community ecology package version 2.3-5[END_REF], 'betapart' (Baselga andOrme 2012), 'plyr' version 1.8.3 (Wickham et al. 2011), and 'ecodist' (Goslee and Urban 2007) packages were used.

Results

Among reefs, the overall taxonomic beta diversity ranged from 0.77 ± 0.07 (mean ± SD) and was essentially due to turnover (96%) (see Fig. 2 and Table S1 for the number of species per station).

Fig. 2 The multiple-site beta diversities and their partitioning components of turnover (dark gray) and nestedness-resultant (light gray). Computed from the Îles Éparses macroalgal data set for taxonomic (Sβtur and Sβnes) and functional (Fβtur and Fβnes) facets at small spatial scale (among sites) and at high spatial scale (among reefs). Vertical bars represent standard deviation of the overall beta diversity In contrast, functional beta diversity was lower than taxonomic beta diversity (0.31 ± 0.1). The taxonomic beta diversity between Europa and Glorioso and Juan de Nova was higher than the null expectation (P value = 0.993 and 0.999, respectively). Similarly, the functional beta diversity was higher than the null expectation (mean P value = 0.992 and 0.999, respectively). Conversely, the taxonomic and functional beta diversities between Glorioso and Juan de Nova were not different from the null expectation (P value = 0.895 and 0.63, respectively). The decomposition of the beta diversity indicated that the functional beta diversity between Glorioso and Juan de Nova also tended to be determined by turnover (95%). However, the nestedness-resultant component remained important between Europa and Glorioso (0.18) and between Europa and Juan de Nova (0.19), but it was negligible between Glorioso and Juan de Nova (0.07). The ordination plot, used for the visualization of multivariate dispersion in community composition, clearly demonstrates the difference in composition among reefs (see Fig. 3).

For the taxonomic beta diversity, the ordination plot produced three distinct groups that mainly separated sites from the three reefs (see Fig. 3). The ordination plot revealed a difference in taxonomic structure between Europa and the two other reefs (see barycentre locations on Fig. 3). For functional beta diversity, the ordination plot did not produce clearly separated groups among reefs, illustrating the low functional beta diversity among reefs, particularly between Glorioso and Juan de Nova (Fig. 3). Functional beta diversity between Europa/Juan de Nova and Europa/Glorioso was 0.33 and 0.39, respectively, and 0.19 for Juan de Nova/Glorioso. The main differences in functional diversity among reefs appear to be due to differences in species mean height and fixation strength (see Table 2, Fig. 4). More generally, community-level weighted means of trait values were quite similar among reefs, explaining the lower value of functional beta diversity compared to taxonomic beta diversity (see Fig. 4, Table 2). This result was also confirmed by the shape Fig. 3 Illustration of taxonomic (top row) and functional (bottom row) dissimilarity and their partitioning component between each site using a PCoA. Sβtot: taxonomic beta diversity, Sβtur: taxonomic turnover, Sβnes: taxonomic nestedness-resultant, Fβtot: functional beta diversity, Sβtur: functional turnover, Sβnes: functional nestedness-resultant. Color code: Europa is orange, Glorioso is blue, and Juan de Nova is pink similarity in functional spaces of the three reefs and position of species within the functional space (see Fig. 5, Fig. S2).

At the scale of sites (within reefs), the overall taxonomic and functional beta diversity ranged from 0.30 to 1 (0.89 ± 0.08) and from 0.35 to 1 (0. 64 ± 0.17), respectively (Fig. 2). On average, the taxonomic beta diversity among sites did not differ from random expectation (mean P value = 0.43 ± 0.35, 0.45 ± 0.36, and 0.45 ± 0.39, for Europa, Glorioso, and Juan de Nova, respectively). Similarly, the functional beta diversity did not differ from random expectation (mean P value = 0. 52 ± 0. 28, 0. 27 ± 0.26, and 0. 34 ± 0.26, respectively).

However, results were highly variable (strong standard deviation) with P value ranging from 0.001 to 0.999 for both beta diversity facets among sites. The overall taxonomic and functional beta diversity among sites for the three reefs was mainly determined by turnover, reaching in average 96% and 67%, respectively.

For assemblages among sites, the taxonomic and functional beta diversities were explained by the three variables: geomorphology, depth and swell exposure (see Table 3, Table S2). The PERMANOVA results showed that swell exposure and geomorphology best explained the taxonomic beta diversity (0.11 < R 2 < 0.15 and 0.09 < R 2 < 0.15, respectively) and the functional beta diversity (0.11 < R 2 < 0.16 and 0.09 < R 2 < 0.19, respectively; see Table 3). Depth, despite significant P value, poorly explained the functional differences in assemblages (0.03 < R 2 < 0.1) (Table 3). Due to its very low value, the nestedness-resultant component was very poorly explained by environmental variables (see Table S3).

Discussion

The floras of the three islands were mostly a subset of the regional diversity, representing 23.5% of the species richness of the Mozambique Channel [START_REF] Mattio | Marine flora of the Iles Eparses (Scattered Islands): a longitudinal transect through the Mozambique Channel[END_REF], although they appeared individually quite contrasted. Relatively few species were shared between Europa and Juan de Nova (41 spp.) and Europa and Glorioso (50 spp.), whereas Juan de Nova and Glorioso appeared more similar (78 spp. in common) [START_REF] Mattio | Marine flora of the Iles Eparses (Scattered Islands): a longitudinal transect through the Mozambique Channel[END_REF]. Each reef has its own dynamics, due to their different geographical position in the Mozambique Channel, and regional biogeographic affinities (see discussion in [START_REF] Mattio | Marine flora of the Iles Eparses (Scattered Islands): a longitudinal transect through the Mozambique Channel[END_REF]. The unique geological history of each reef has also shaped contrasting geomorphologies [START_REF] Jorry | Modern sediments and Pleistocene reefs from isolated carbonate platforms (Iles Eparses, SW Indian Ocean): a preliminary study[END_REF]. All of these factors would be expected to drive distinct patterns of species communities and functional traits portfolio for each reef. Our results revealed at least two scenarios which speak against this assumption.

First, a low functional beta diversity was observed between Glorioso and Juan de Nova despite the presence of different sets of species between the three reefs. However, when comparing the beta diversities of the two reefs against null models, our results did not provide the evidence of functional trait-based community assemblies. In other words, the observed beta diversity was indistinguishable from a random assignment of species and functional traits. The low functional beta diversity may suggest a functional convergence, which could be the result of similar environmental conditions. The two reefs are a part of the same ecoregion, where biogeographic forces are relatively similar [START_REF] Quétel | Iles Eparses (SW Indian Ocean) as reference ecosystems for environmental research[END_REF]. Although these two reefs have different geological histories, they have relatively similar habitats and environmental conditions, which could explain that they host macroalgal communities with similar functional diversities. Overall, this finding beta diversity finding supports the idea that, despite distinct species composition, macroalgal communities can provide similar functional portfolio and, therefore, similar ecological functions (see [START_REF] Guillemot | Functional redundancy patterns reveal non-random assembly rules in a species-rich marine assemblage[END_REF] for similar results on fish communities, Fig. 5).

Second, the reef of Europa, which is geomorphologically and geologically different to the two other reefs [START_REF] Quétel | Iles Eparses (SW Indian Ocean) as reference ecosystems for environmental research[END_REF], and harbors specific habitats such as mangroves, was expected to show distinct taxonomic and, to a lower extent, functional composition [START_REF] Poupin | Crustacea Decapoda of Glorieuses Islands, with notes on the distribution of the coconut crab (Birgus latro) in the western Indian Ocean[END_REF]. Our results Fig. 4 Community-weighted means of functional trait among the three reefs (Europa, Glorioso, and Juan de Nova). Boxplots represent the distribution of the CWM value for each modality of each functional trait. For codes of the different modalities, see Table 1 confirmed this assumption with the values of taxonomic and functional beta diversities higher than expected for a null model. Hence, the singularity of environmental conditions and habitats at Europa is likely the driver of its distinct taxonomic composition and to a lesser extent, functional trait diversity. Most seaweeds are poor dispersers, because their spores and zygotes are typically short-lived and negatively buoyant [START_REF] Kinlan | Propagule dispersal in marine and terrestrial environments: a community perspective[END_REF]. Then, many seaweed species have restricted geographic ranges and molecular data indicate that several allegedly widely distributed species in fact represent cryptic species with narrow distributions (e.g., [START_REF] Zuccarello | Multiple cryptic species: molecular diversity and reproductive isolation in the Bostrychia radicans/B. moritziana complex (Rhodomelaceae, Rhodophyta) with focus on North American isolates[END_REF][START_REF] Saunders | Applying DNA barcoding to red macroalgae: a preliminary appraisal holds promise for future applications[END_REF][START_REF] Gabriel | Beneath the hairy look: the hidden reproductive diversity of the Gibsmithia hawaiiensis complex (Dumontiaceae, Rhodophyta)[END_REF]. This limited dispersal could explain the high taxonomic beta diversity observed among the three reefs. Despite singularity of their environmental variables (particularly Europa), the three reefs share similar climate conditions that could lead to a convergence in functional traits explaining the low functional beta diversity and similar CWM.

At small spatial scales, macroalgae species and functional beta diversity were high among sites mainly due to a strong turnover. In average, both beta diversities did not differ from the null expectation. However, the P value was extremely variable (from 0.001 to 0.999) advocating for a complex and multiple processes combining effect of the environmental gradient, limiting similarity and stochastic effects on the structure of macroalgal communities. This means that environmental variables, competition, and stochasticity may be ruling the beta diversity patterns. This hypothesis was confirmed by the results of the Fig. 5 Functional space and distribution of species inside the functional space of Europa, Glorioso and Juan de Nova (orange, blue, and pink, respectively). Circles represent species and are proportional to their respective occurrence at the three reefs. Large circle = species has been collected at the three reefs, medium circle: species has been collected at two reefs, and small circle: species has been collected at one reef only. From the bottom in clockwise direction, the black dots for Champia compressa, Corallinales sp., Halimaeda melanesica, Padina sp., and Cladophora sp3 mark vertices species. When some species have the same functional trait, the corresponding dot has been moved slightly for visual purposes (i.e., randomly jittered) PERMANOVA analysis which highlighted the influence of environmental variables on taxonomic and functional beta diversities. However, an important proportion of the beta diversities were not fully explained by the environmental variables alone. Several others potential factors could explain this result. First, the sampling strategy of the initial project was designed to maximize records of diversity (species inventories) with low replication within similar habitats [START_REF] Mattio | Marine flora of the Iles Eparses (Scattered Islands): a longitudinal transect through the Mozambique Channel[END_REF]. Second and more importantly, a number of environmental variables were not considered in this study, such as biotic (coral cover, biomass of herbivorous fishes, etc.) and abiotic (nutrients and water movement) variables, which have been shown to influence the structure of macroalgal communities in the other studies [START_REF] Burkepile | Impact of herbivore identity on algal succession and coral growth on a Caribbean reef[END_REF][START_REF] De'ath | Water quality as a regional driver of coral biodiversity and macroalgae on the Great Barrier Reef[END_REF][START_REF] Keith | Global diversity of marine macroalgae: environmental conditions explain less variation in the tropics[END_REF]). These variables were not recorded systematically in the initial study design [START_REF] Mattio | Marine flora of the Iles Eparses (Scattered Islands): a longitudinal transect through the Mozambique Channel[END_REF] and could not be used in the present study. In addition, small-scale processes (competition and herbivory) were difficult to assess. Functional traits, such as the capacity to produce repellent molecules, could be a minor contributor to explain the variability among sites but could possibly explain the distribution of macroalgae at very small scale within sites. Competition is a key process determining the composition and structural changes of benthic communities in coral reefs, particularly interactions between corals and macroalgae [START_REF] Mccook | Competition between corals and algae on coral reefs: a review of evidence and mechanisms[END_REF]. Negative effects of algae on coral health occur at very small scale by direct physical effects such as shading or smothering [START_REF] Jompa | Coral-algal competition: macroalgae with different properties have different effects on corals[END_REF], and by chemically and microbially mediated mechanisms [START_REF] Thurber | Macroalgae decrease growth and alter microbial community structure of the reefbuilding coral, Porites astreoides[END_REF]. Future studies should increase the sampling effort in each habitat, measure a larger range of environmental variables, and extend the study to other benthic species. Revealing functional traits that influence most interactions among macroalgae and other reef species could bridge the gap in knowledge between small-scale processes and macro-ecology.

In addition, future work should investigate the influence of season on taxonomic and functional beta diversity. Environmental variability [START_REF] Segar | Convergent structure of multitrophic communities over three continents[END_REF]) may lead to changes in the onset of a function; for example, the supply of inorganic nutrients may alter or enhance productivity [START_REF] Wenger | 15 Effects of sedimentation, eutrophication, and chemical pollution on coral reef fishes[END_REF]. Finally, our study does not consider the species abundance and/or their biomass, but only used the presence-absence data. There is strong evidence that dominant species/functional entities have a significant effect on ecosystem functioning [START_REF] Gagic | Functional identity and diversity of animals predict ecosystem functioning better than species-based indices[END_REF]. Abundance and biomass data would allow to weigh the contribution of each species [START_REF] Grime | Benefits of plant diversity to ecosystems: immediate, filter and founder effects[END_REF][START_REF] Villéger | New multidimensional functional diversity indices for a multifaceted framework in functional ecology[END_REF] to better assess their respective responses to forcing variables and/or their importance for ecosystem functioning. However, considering our first objectives, which were fairly descriptive, this first analysis based on the presence-absence data provides a base for further investigation. Parameters are as follows: degrees of freedom (df), sums of squares (SumsSqs), and pseudo-coefficient of determination for GLM (R 2 ); the significance of the pseudo F-Model was tested using a permutation test (9999 permutations); significant results (P value < 0. By providing insights into the functional diversity of macroalgal communities, our work provides a baseline of the natural distribution and function of macroalgae in isolated coral reef ecosystems of the Mozambique Channel. Fundamental knowledge on species variability and functional community composition is essential for adequate management of the coral reef ecosystem of the Îles Éparses. The high dissimilarity in species composition and to a lesser extent in functional composition among reefs, and the dominance of turnover within reefs and among reefs, calls for the conservation of a large number of different sites at the three reefs (i.e., a single reef cannot replace a global protection of the three reefs). This supports the conservation strategy already established in the Îles Éparses which includes all regional marine diversity [START_REF] Chabanet | Coral reef monitoring in the Iles Eparses, Mozambique Channel (2011-2013)[END_REF].

Finally, understanding the dynamics of communities in a changing world critically relies upon the robust quantification of functional differences among species [START_REF] Madin | A trait-based approach to advance coral reef science[END_REF]. We argue that progress in macroalgal ecology research is hindered by the limited number of species for which trait data are available compared to terrestrial flora [START_REF] Buzzard | Regrowing a tropical dry forest: functional plant trait composition and community assembly during succession[END_REF] or other taxonomic groups in coral reefs [START_REF] Parravicini | Global mismatch between species richness and vulnerability of reef fish assemblages[END_REF]. At the moment, no significant database with uniform terminology exists for macroalgae. Our work is a first step toward using functional diversity in macroalgae ecology; functional traits are a proxy of the "real" functions of species and information is still missing for some species. More knowledge about the phenotypical and physiological variations in life-history traits such as productivity, calcification, and production of molecules will further our understanding of the dynamics of these assemblages and their function in the coral reef ecosystem. For instance, information about reproduction could be an essential trait to understand functional biogeography of macroalgae, but information about this trait was too scarce to be used in this study. Within the European Marine Observation Data Network (EMODnet) Biology project (www.emodn et-biolo gy.eu), a trait matrix is upcoming for European algal diversity. Traditionally, abundance of opportunistic macroalgae and species shift in floristic composition has been used successfully as descriptors of human-induced eutrophication [START_REF] Blanfuné | The CARLIT method for the assessment of the ecological quality of European Mediterranean waters: relevance, robustness and possible improvements[END_REF]. Future studies should explore linkages between the disturbance and functional composition of macroalgae communities, as it may be more predictive than taxonomic indicators (see Teresa and Casatti 2017, on fish).

Fig. 1

 1 Fig.1Location of the Îles Éparses in the SW Indian Ocean (a) and sampling sites (black dots) at Europa (b), Glorioso (c), and Juan de Nova (d). Mapping data were extracted from the Millennium Coral Reef Mapping Project[START_REF] Andréfouët | Atlas des récifs coralliens de l'Océan Indien Ouest Atlas of Western Indian Ocean Coral Reefs Centre IRD de Nouméa[END_REF]. Different colors indicate geomorphological classes. At Europa, the site that appears inland is a mangrove site

Table 1

 1 Functional traits of macroalgae and their modalities

	Traits	Modalities	Main functional significance
	Life-history traits
	Growth	S: Slow	Food web (primary producer)
		F: Fast	Contribution to seascape
	Mean height	Small species: < 2 cm Medium species: 2-5 cm Large species: > 5 cm	CO 2 bio-fixation Ability to create habitat (nurseries, recruitment) Tolerance to disturbance
	Longevity	A: annual
		P: perennial
	Primary productivity	1: < 2 mgC/g dw/day
		2: 2-8 mgC/g dw/day
		3: 9-20 mg C/g dw/day
		4: > 40 mg C/g dw/day
	Calcification	No: non-calcified macroalgae	Reef construction and stabilization
		Low: < 50% dw CaCO 3 Medium: 50-80% dw CaCO 3 High: > 80% dw CaCO 3	Sand formation Capacity to create habitat and new surface for benthic colonization Defense against herbivory
	Ecological traits
	Substratum	No: epiphyte	Contribution to seascape
		HS: hard substratum (corals, dead corals, rubbles)	Substratum consolidation
		S: soft substratum (sand or sediments) HS/S: hard and soft substrata	CO 2 bio-fixation Resistance to environmental condition
	Fixation strength	Low: weak fixation	Canopy resilience
		Medium: intermediate strength of fixation
		High: strong fixation
	Interactions	Epiphyte: interactions with macroalgae	Coral resilience
		1: < 25% contact (erect thalli)	Ability to create habitat
		2: 25-50% contact (tangled mat or shelf-like forms like	Defense against herbivory
		procumbent, decumbent, or anastomosing)
		3: 50-100% contact (tangled mat or shelf-like forms like
		procumbent, decumbent, or anastomosing)
		4: 100% contact (crustose species)
	Ability to proliferate

  . Several species belonging to many different groups have been reported to proliferate, including mostly large brown macroalgae like Dictyotales (Lobophora spp., see[START_REF] Vieira | Matching names and clades in the brown algal genus Lobophora (Dictyotales, Phaeophyceae): an effort to integrate type specimens in modern taxonomy[END_REF] for a review) or Fucales (Turbinaria spp. and Sargassum spp.,Stiger and Payri 1999a, b;[START_REF] Andréfouët | The timing and the scale of the proliferation of Sargassum polycystum in Funafuti Atoll[END_REF]), but also green (Caulerpa spp.

, Ulva spp., Codium spp., Lapointe et al. 2005; Machendiranathan et al. 2016) and red macroalgae (e.g. Asparagopsis taxiformis,

Table 2

 2

	Community-weighted means (the most common		Europa	Glorioso	Juan de Nova
	values) of functional traits at each reef	Growth Mean height	Fast Small	Fast Large	Fast Medium
		Longevity	Perennial	Perennial	Perennial
		Primary productivity	2	2	2
		Calcification	No	No	No
		Substratum	Hard substratum	Hard substratum	Hard substratum
		Fixation strength	Medium	Medium	High
		Interaction	2	1	1
		Ability to proliferate	No	No	No
		Repellent molecules	Yes	Yes	Yes

Table 3

 3

	Relationships between
	environmental variables
	(geomorphology, depth, and
	swell exposure) and taxonomic
	and functional beta diversity of
	macroalgae
	Model summaries and parameter estimates for the permutational multivariate analysis of variance (PER-
	MANOVA)

  05) are indicated in bold

	Beta	Reefs	Variables	df	SumsSqs	F	R 2	P value
	Sβtot	Europa	Swell exposure	2	0.895	1.322	0.152	0.039
			Depth	1	0.723	2.134	0.123	0.002
			Geomorphology	2	0.888	1.312	0.151	0.022
		Glorioso	Swell exposure	2	0.993	1.598	0.113	0.003
			Depth	1	0.812	2.615	0.092	0.001
			Geomorphology	3	1.099	1.179	0.125	0.108
		Juan de Nova	Swell exposure	2	1.261	2.030	0.132	0.001
			Depth	1	0.934	3.005	0.098	0.001
			Geomorphology	2	0.829	1.335	0.087	0.051
	Fβtot	Europa	Swell exposure	2	0.821	0.821	0.152	0.114
			Depth	1	0.353	0.353	0.110	0.018
			Geomorphology	2	0.663	0.663	0.182	0.019
		Glorioso	Swell exposure	2	0.666	1.452	0.117	0.016
			Depth	1	0.436	1.901	0.068	0.027
			Geomorphology	3	1.067	1.550	0.186	0.040
		Juan de Nova	Swell exposure	2	0.746	1.232	0.17	0.014
			Depth	1	0.470	1.554	0.056	0.111
			Geomorphology	2	0.753	1.244	0.031	0.989

Acknowledgements

The BIORECIE research program was led by the Centre National de la Recherche Scientifique, the Institut d'Ecologie et Environnement (CNRS-INEE) with the financial support from the Institut National des Sciences de l'Univers (INSU), the Institut de Recherche pour le Développement (IRD), the Agence des Aires Marines Protégées (AAMP), the Fondation pour la Recherche sur la Biodiversité (FRB), the Terres Australes et Antarctiques françaises (TAAF), and the Veolia Environment foundation. We warmly thank Pascale Chabanet for leading the BIORECIE program and offering the unique opportunity to sample in the Îles Éparses. We are very grateful to the military personnel stationed on each of the reefs for providing logistical supports. The crew of the R/V Antsiva greatly helped for the sampling of the three reefs. We acknowledge three anonymous reviewers and Editor Dr. Roleda for their comments that helped clarifying several aspects of the study.

Author contributions Authors whose names appear on the submission have contributed sufficiently to the scientific work and, therefore, share collective responsibility and accountability for the results.

Compliance with ethical standards

Conflict of interest The authors declare that they have no conflict of interest.

Human and animal rights statement This article does not contain any

with human participants or animals performed by any of the authors. All necessary permits for sampling and observational fields have been obtained by the authors from the competent authorities (TAAF) and are mentioned in the acknowledgments. We took care not to disturb wildlife or the surrounding environment more than necessary to gather the samples.


Ulrich Mansmann

Clara Locher

Fabian Prasser

Tracey Weissgerber

Ulrich Sax

Martin Posch

Evelyne Decullier

Ioana A Cristea

Thomas P A Debray

David Moher

John P A Ioannidis

Joseph S Ross

Christian Ohmann

Florian Naudet

Implementing clinical trial data sharing requires training a new generation of biomedical researchers

Keywords: Clinical trials, individual patient data, open science, data sharing, training

Data sharing enhances the value of medical research and builds trust in clinical trials, but more biomedical researchers need to be trained in these approaches, which include meta-research, data science and ethical, legal and social issues.

Clinical trials form foundational evidence to inform contemporary medical decision making. They provide evidence widely used by regulatory bodies, health technology assessment agencies, and are considered the gold standard for assessing treatment effects. The value and trustworthiness of medical research may be enhanced by sharing of patient-level clinical trial data together with the code on which analyses are based (1,2) as well as other materials such as the protocol, case report form, and data dictionary.

Embedding clinical trial data sharing into such a broader framework offers the opportunity for external re-analysis, which enables conclusions to be re-examined, verified or, occasionally, corrected, thereby building trust. Data sharing also allows individual participant data (IPD) metaanalysis and other strategies that build upon previous data and code, such as secondary analyses and methodological work. Data sharing should accelerate discovery, reduce false discovery rates, and potentially discourage misconduct and research waste, as well as allowing more value to be drawn from the original research investment. Data sharing honours the generosity of clinical trial participants, because it maximises the utility of the data they provide (3), and is widely viewed as a positive feature by stakeholders involved in clinical trials, including trial participants (4).

Clinical trial data sharing experts are therefore urgently needed. A new generation of such experts can be nurtured by incorporating interdisciplinary methodological approaches to clinical trial data sharing into the curriculum of existing medical PhD and Clinical Scientist programs around the globe.

Limited sharing

Over the past decade, data sharing platforms have been launched to promote clinical trial data sharing, including Clinical Study Data Request (CSDR), the Yale University Open Data Access (YODA) Project, and Vivli. Guidelines have been developed to verify digital repository trustworthiness (5). Regulatory authorities such as the European Medicines Agency (EMA) and the US Food and Drug Administration launched initiatives on clinical trial data transparency (6).

Although their implementation is a work in progress, EMA's policy 0070 on "publication of clinical data for medicinal products for human use" includes plans to publish the IPD [START_REF]EMA 2019[END_REF]. The pharmaceutical industry also adopted policies for sharing IPD [START_REF] Sudlow | [END_REF]. Many public funders (9) and medical journals (10) support, and sometimes even mandate, data sharing, including Wellcome Trust, the British Medical Journal and Public Library of Science. Academic and commercial communities are developing best practices on how to organize and perform data sharing. Despite these positive developments, the practical implementation of clinical trial data sharing is disappointing. Over the 2017-2019 period, about 16% of pivotal trials submitted to the EMA provided IPD for re-analysis (11). Data sharing policies are poorly implemented by journals and rarely adhered to. In surgical journals no change was observed in data sharing before (2/65 trials) and after (2/65 trials) the International Committee of Medical Journal Editors adopted a data sharing policy (12).

There is a lack of adequate incentives to fully implement clinical trial data sharing. Scientific productivity is currently favoured over transparency in promotion and tenure criteria in biomedical sciences faculties in academic medicine (13). Some trialists may be sceptical about data sharing; with some re-users labelled as "research parasites" (14). Researchers and data-providers may also lack the adequate support and/or financial resources and face technical barriers, such as a lack of secure infrastructure to handle requests, or prepare and share their data sets. There can be technical hurdles, such as additional effort that is often needed to harmonize variables across data sets. Trialists may also face regulatory difficulties in sharing their data, as health data are sensitive and require adequate privacy protection. In addition, some poor-quality data requests may make the data generator reluctant to share the data. These challenges limit the impact of data sharing efforts, providing a compelling need to improve data sharing processes in clinical trials.

New professional activities for experts can help overcome cultural and practical barriers and improve clinical trial data sharing efforts. The next generation of biomedical researchers should be trained in their specific domains, and the entire lifecycle of clinical trial data sharing (Figure 1). The scarcity of such knowledgeable experts to-date presents a key bottleneck in accelerating data sharing efforts, as well as hindering the adequate use of shared data. Contemporary training approaches are usually focused on individual components of clinical trial data sharing, whereas an interdisciplinary approach is needed. Such training should focus on implementing clinical trial data sharing and assessing its impact, both by preparing and reusing the data.

A training curriculum

Organising data sharing activities both at the study level (requesting, preparing, sharing data and re-using the data) and at a global level (adopting and optimising data sharing policies) requires an inter-and transdisciplinary approach that includes clinical trials regulations, ethical, legal, and social issues, informatics, data science, biostatistics, and meta-research, as well as domain expertise across different medical fields.

Those who establish best practice for clinical trial data need training in principles, governance, skills, and operations. Such training should include best practices, measuring impact, and practical exercises for the use of shared data.

Best practice

A coherent training curriculum should encompass the many topics related to best practices in clinical trial data sharing. Best practice in preparing an existing data set for sharing requires standards including the FAIR (15,16) and TRUST Data Principles (5), privacy protection of trial participants, efficient anonymization, reporting of studies, and governance processes to access data. Best practice in re-using a shared data set include the access and utilization of the data. This requires skills in handling data formats, managing deployment processes (such as data sharing platforms such as YODA or federated and distributed analyses that are needed when data cannot leave the host institution), implementing secondary studies such as IPD metaanalysis (17,18), clinical trial planning and biostatistical methods development. Obviously, skills in open science and reproducible research practices are paramount as transparent reporting is needed to ensure that results can be properly interpreted and reproduced. Scientists with awareness of these topics should be ready to collaborate with the right experts, all of whom needed for a successful project set-up.

Impact

While best practices for clinical trial data sharing are coming progressively into effect, it is necessary to assess whether they achieve the intended impact. Therefore, the training curriculum should encompass the various aspects related with understanding and studying the impact of clinical trial data sharing. Training should enable those who perform clinical trials to assess how various stakeholders, including trial participants, understand and accept data sharing (4). Furthermore, researchers must understand the cost associated with data preparation and data curation and its implications.

At the more global level, impact studies should assess how clinical trial data sharing influences knowledge generation. This includes the study of indicators of transparency, openness, and reproducibility for clinical trials. Such activities require the use of automated screening tools (19) to identify studies relying on shared data and monitor their conduct, transparency and reporting. This part of the curriculum requires teaching skills on a wide range of meta-research approaches, such as umbrella reviews, surveys, observational studies, and simulations (19).

Datathons for data literacy

Biomedical researchers are usually trained with theoretical lectures and practical exercises.

Although these activities help to develop familiarity with key data sharing concepts, more interactive methods such as datathons should be used to acquire practical skills. A datathon is an intense workshop that asks participants to utilise the data provided to develop and answer topic-driven questions or to develop innovative approaches to analyse the data.

During these events, participants gather to solve practical problems through the application of data science tools and techniques, working together in teams to generate insights and potential solutions. Participants in a datathon can attempt to make a novel clinical finding from a single RCT dataset, as for the Systolic Blood Pressure Intervention Trial (SPRINT) Challenge (20). Each team defines an interesting research question requiring data re-use and explores the question using the datasets. This secondary analysis of clinical trial data could investigate subgroup effects or rare safety events, or explore reproducibility issues (21), or implement an IPD meta-analysis (17).

Participants can benefit from the input of experts within the project as well as external advisors such as patients and clinicians. Beyond teaching skills, datathons may also teach values by promoting transparency, honesty and collaboration in an environment where ideas can be shared openly and implementation can become more efficient. Such multi-team analyses stands in contrast to the overly optimistic and unrepresentative results from a single statistical analysis (22).

Funding requirements

All organizations that conduct and report clinical trials need to train a new generation of scientists who are able to understand the challenges related to clinical trial data sharing and to implement open science practices that maximize their value, transparency and reproducibility. Funding will be needed, as will buy-in from stakeholders in curricular and strategic development, as well as management in academia and industry. 1. Each clinical trial data sharing platform needs experts for a complex, thorough, and efficient review process. Experts will have their own specific field, such as medicine, biostatistics, interdisciplinary data science, intellectual property, privacy protection, ethical, legal, and social issues, but also need an overarching understanding of the disciplinary nature of this topic.

2. The peer review of research papers that come from clinical trial data sharing should reflect the interdisciplinary approach and complexity. Editors or editorial staff should boost clinical trial data sharing within their journals' activities. Requiring data and analysis scripts for reviews will initiate basic processes to share clinical trial data. Reproducibility editors can steer the verification of published results based on the data used.

3. Academic institutions, such as trial centres at academic hospitals, need well-trained staff, including data managers and data engineers. These staff can set up and contribute to clinical trial data sharing activities, especially for anonymization requirements.

4. Research funders, as well as research management, in academia, industry, governments, and regulatory bodies must be trained in the complex issues of clinical trial data sharing.

5. Future medical researchers, as well as data scientists in medicine, will need basic training on clinical trial data sharing so that they can conduct their own research using shared datasets.

6.

Training in meta-research for academics, professional institutions and funders will maximise the impact of data sharing.

  Typically, clinical trial data sharing represents a complex task with many parts which are not reflected in the traditional priorities for research funders, although funders prioritize open science. UNESCO has named open practices in science as one of their priorities (23), and the French Plan for Open Science has a specific working group dedicated to clinical trial data sharing. The University of Cambridge has a well-established data champions programme (24), training research volunteers who advise their peers on best practices related with research data management, including data sharing. Canada has funded 18 data champions programs (25), some of which focus on clinical research, including clinical trials. The technical university of Delft counts data champion activities towards career advancement (22).These initiatives align with DORA (26) and Hong Kong Principles (27), which aim to reform research assessment in academia by explicitly recognizing and rewarding research integrity and reproducible research practices. Additional professional opportunities for clinical trial data sharing arise in universities, research institutions, and pharmaceutical companies, settings in which clinical trials are funded, conducted and reported (Box 1). (27). Only through training a new generation of data sharing experts can the full potential of clinical trial data be realized for the advancement of medical research and the benefit of patients.

Box 1 :

 1 Opportunities for experts in clinical trial data sharingAccepted manuscript / Final version

Figure 1 :

 1 Figure 1: Elements of data sharing

Author contributions

All authors contributed to the concept that the manuscript presents. Ulrich Mansmann and Florian Naudet wrote the manuscript that was carefully and critically proofread by all authors. All authors have given their consent to the publication of the manuscript.

Conflict of Interest:

Ulrich Mansmann


Suzanne Lesage
email: suzanne.lesage@upmc.fr

Joanne Trinh
email: joanne.trinh@neuro.uni-luebeck.de

Special Issue "Parkinson's Disease: Genetics and Pathogenesis"

Parkinson's disease (PD) is a common and incurable neurodegenerative disease, affecting 1% of the population over the age of 65. Although the disease remains defined clinically by its cardinal motor manifestations and pathologically by substantia nigra neuronal loss in association with intraneuronal Lewy bodies, the molecular mechanisms that lead to neurodegeneration remains elusive. It is becoming increasingly clear that genetic factors contribute to its complex pathogenesis. More than 23 loci and 13 genes, including LRRK2, SNCA, GBA1, PRKN, PINK1, and PARK7/DJ-1 clearly linked to inherited forms of Parkinsonism have been identified to date. The knowledge acquired from their protein products has revealed pathways of neurodegeneration that can be shared by Mendelian and sporadic Parkinsonism, including synaptic, lysosomal, mitochondrial and immune-mediated mechanisms of pathogenesis. This special issue "Parkinson's Disease: Genetics and Pathogenesis" collects 12 high-quality papers, including seven original research articles, and five reviews, that seeks to deepen the knowledge of multiple aspects related to Parkinsonism.

Two reviews by Jia et al. [START_REF] Jia | Monogenic Parkinson's Disease: Genotype, Phenotype, Pathophysiology, and Genetic Testing[END_REF] and Elsayed et al. [START_REF] Elsayed | Mapping the Diverse and Inclusive Future of Parkinson's Disease Genetics and Its Widespread Impact[END_REF] provide a comprehensive overview of the current knowledge of PD genetics in the genotype-phenotype relationship and associated pathophysiology with a focus on genetic testing, its current challenges and limitations. In addition, Jia et al. [START_REF] Jia | Monogenic Parkinson's Disease: Genotype, Phenotype, Pathophysiology, and Genetic Testing[END_REF] discuss the role of heterozygous mutations in genes associated with autosomal recessive PD and the impact of digenism (i.e. dual LRRK2 and GBA1 mutation carriers) on the clinical outcomes. It is now recognized that important genetic differences exit according to ethnicities and regions. The inclusion of ethnic diversity in PD genetics research, by including under-represented PD populations, is essential to provide novel insights regarding the generalized genetic map of the disease. It will also improve our understanding of the disease biology and pathogenesis and health care of PD patients. In the future, global efforts will play a key role in exploiting the genomic data, to identify rare genetic cause of PD or to replicate important gene discoveries. Furthermore, newer global initiatives such as the Global Parkinson's disease program (GP2) [START_REF]Global Parkinson's Genetics Program. GP2: The Global Parkinson's Genetics Program[END_REF] will offer greater representation of underrepresented populations from different ethnic groups and geographical regions. A third review by Kim et al. [START_REF] Kim | Human Induced Pluripotent Stem Cell Phenotyping and Preclinical Modeling of Familial Parkinson's Disease[END_REF] covers the most common mutations in PD-related genes, such as LRRK2, SNCA, GBA1, PRKN, PINK1, and PARK7/DJ-1, the function of these protein products and the consequences of their mutations on the pathophysiological mechanisms leading to PD. Further consequences of these mutations have been emphasized with the use of induced pluripotent stem cells (iPSCs) for a disease-in-a-dish approach and genetic animal models.

To identify potential early predictive biomarkers in PD, Mangone and colleagues [START_REF] Mangone | Relationship between Substantia Nigra Neuromelanin Imaging and Dual Alpha-Synuclein Labeling of Labial Minor in Salivary Glands in Isolated Rapid Eye Movement Sleep Behavior Disorder and Parkinson's Disease[END_REF] investigated the presence of immuno-stained misfolded -Synuclein in minor salivary gland biopsies in relation with substantia nigra pars compacta (SNc) damage measured by magnetic resonance imaging. They included 27 idiopathic PD, 16 with isolated rapid eye movement sleep disorders, a prodromal form of -synucleinopathies and 18 healthy controls. The authors concluded that the -Synuclein detection in minor salivary gland biopsies lacks sensitivity and specificity and does not correlate with SNc damage. In a second original paper, Usenko et al. [START_REF] Usenko | Comparative Transcriptome Analysis in Monocyte-Derived Macrophages of Asymptomatic GBA Mutation Carriers and Patients with GBA-Associated Parkinson's Disease[END_REF] compared the gene expression profile in monocyte-derived macrophages from five PD patients and four asymptomatic relatives carrying either heterozygous GBA L444P or N370S mutations and four healthy controls. They found dysregulated genes in GBA-PD patients, independent to the nature of GBA mutations compared to the other two groups, these genes being involved in neuronal functions, inflammation and zinc metabolism. In particular, altered expression of DUSP1 encoding the mitogen-activated protein kinase 1 (MKP-1) phosphatase implicated in the regulation of apoptosis, endoplasmic reticulum stress, cell cycle and autophagy can be considered a potential biomarker for GBA-related PD. Taking advantages of newer technologies, Pantaleo et al. [START_REF] Pantaleo | Machine Learning Approach to Parkinson's Disease Blood Transcriptomics[END_REF] used whole blood transcriptome data and advanced Machine Learning approaches for future selection and classification of 390 early (drug-naïve) PD patients versus 189 agematched healthy controls. The authors identified a set of around 500 genes implicated in a certain number of significant functions and pathways, some of which have already been linked to the pathogenesis of PD, such as oxidative stress, inflammation and vesicular dysfunction, as well as associations between PD and diseases such as diabetes mellitus or inflammatory bowel disease. The narrative review by Prasuhn and Brüggemann [START_REF] Prasuhn | Gene Therapeutic Approaches for the Treatment of Mitochondrial Dysfunction in Parkinson's Disease[END_REF] highlights the importance of one of the known PD-associated pathways, that is mitochondrial dysfunction as a molecular cause in monogenic and idiopathic PD. They focus on gene therapeutic targets and challenges necessary to translate molecular findings into potential clinical applications, highlighting different treatment strategies.

Epigenetic modifications are responsible for functional gene regulation during development, adult life and ageing and have also been implicated more recently in neurodegenerative diseases, such as PD. Regulation of genes responsible for monogenic forms of PD may be involved in sporadic PD. Lanoré and colleagues [START_REF] Lanore | Does the Expression and Epigenetics of Genes Involved in Monogenic Forms of Parkinson's Disease Influence Sporadic Forms?[END_REF] reviewed the epigenetic mechanisms regulating gene expression, including DNA methylation, histone modification and epigenetic changes by non-coding RNAs. An example is SNCA, encoding -Synuclein, with the understanding of its regulation being a longstanding central focus for the community working on PD. The accumulation of this protein in the Lewy bodies or neurites, the identification of mutations in the coding regions of the gene or multiplications (duplications or triplications) of the whole gene in familial PD and the strong association of single nucleotide polymorphisms (SNPs) with sporadic PD indicate the importance of this protein in the pathogenesis of the disease. Interestingly, SNCA contains several transcriptionally activated histone modifications and associated potential transcription factor binding sites in the noncoding regions of the gene that strongly suggest alternative regulation pathways. Thus, it has been reported that DNA methylation of SNCA may modulate its expression, particularly, hypomethylation in intron 1 of SNCA was observed in several brain regions or in peripheral tissues of sporadic PD patients and an increased SNCA expression. On the other hand, in postmortem midbrain samples, an enrichment of three histone modification marks, such as H3K4me3, H3K27ac and H3K27me3, was reported in SNCA regulatory regions. Finally, micro-RNAs (miRNAs), such as miR-7 and miR-153, as well as miR-34b/c bind to the 3'-UTR of SNCA mRNA, destabilizing the mRNA and reducing its levels.

Genome-wide association study (GWAS) have widened our understanding of the genetics of PD and have identified more than 90 genetic loci associated with PD [START_REF] Chang | International Parkinson's Disease Genomics Consortium[END_REF]. Jo and colleagues [START_REF] Jo | Microarray Genotyping Identifies New Loci Associated with Dementia in Parkinson's Disease[END_REF] performed a GWAS on dementia in 318 PD patients with dementia, 326 PD patients without dementia and 648 healthy controls, all of Korean origin. The data analysis led to the identification of the new loci of MUL1 associated with dementia in PD, suggesting an essential role of mitochondrial dysfunction in the development of dementia in patients with PD. Two other loci containing ZHX2 and ERP29 were also found to be associated with dementia in PD. In the original research publication, Koch et al. [START_REF] Koch | Validity and Prognostic Value of a Polygenic Risk Score for Parkinson's Disease[END_REF] used the development of polygenic risk scores (PRSs) as a means to summarize the effect of the genetic background upon an individual's disease risk in a single number. The authors were able to replicate the performance of the PD-PRS developed by Nalls and colleagues [START_REF] Nalls | Identification of novel risk loci, causal insights, and heritable risk for Parkinson's disease: a meta-analysis of genome-wide association studies[END_REF] in an independent dataset, suggesting that the PRS may be a meaningful research tool to investigate and adjust for the polygenic component of PD but this tool is not meaningful for individual risk prediction.

Emerging studies revealed that expansions or intermediate repeats of simple short DNA sequence can cause or act as risk factors for different neurological diseases, including PD, depending on the number of repeats. In the original paper by Kobo et al [START_REF] Kobo | C9orf72-G4C2 Intermediate Repeats and Parkinson's Disease; A Data-Driven Hypothesis[END_REF], stratified analysis in 1106 Ashkenazi PD patients and 600 ethnically matched-controls suggests that intermediate-size hexanucleotide repeats (20-60 repeats) in c9orf72 are a risk factor for PD in individuals without common Ashkenazi Jewish founder mutations in LRRK2, GBA, or SMPD1 compared with those with these mutations. The authors propose a model in which the risk for PD may be driven not only by the number of the repeats, but also by the genotypes of 44 informative single nucleotide variants (SNVs) within the risk-haplotype, affecting the c9orf72 RNA expression levels. In the second original research paper, Lüth et al. [START_REF] Lüth | Elucidating Hexanucleotide Repeat Number and Methylation within the X-Linked Dystonia-Parkinsonism (XDP)-Related SVA Retrotransposon in TAF1 with Nanopore Sequencing[END_REF] established a straightforward Nanopore long-read deep sequencing workflow to quantify the hexanucleotide repeat number in the TAF1 SINE-VNTR-Alu (SVA) insertion in patients with X-linked dystonia-Parkinsonism (XDP). In addition, the authors utilized this novel technology to investigate variations within the SVA locus other than the repeat motif and to detect CpG methylation using a Cas9-targeted approach, across a large-22 kb-region containing the TAF1 SVA.

Overall, this special issue highlights the richness of studies bringing recent advances in our knowledge on the genetic architecture contributing to PD. This volume should be an important contribution to the field by improving our understanding of the pathophysiology and thus will help with the efforts to develop targeted therapies and personalized medicine.

Acknowledgments: We would like to thank Dr Poornima Menon for the manuscript reading.

Funding: S.L. acknowledges funding from the Fondation pour la Recherche Médicale (FRM, MND202004011718).

Conflicts of Interest:

The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.


Léa Boillereaux

Simon Le Floc'h

Abderrahmane Kheddar

Franck Jourdan

Development and evaluation of a knee brace for joint stress modulation -A literature review

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

Development and evaluation of a knee brace for joint stress modulation -A literature review Léa Boillereaux, Simon Le Floc'h, Abderrahmane Kheddar, Franck Jourdan

In order to relieve the patients suffering osteoarthritis or other cartilage diseases and to facilitate the rehabilitation after an operation, it is necessary to unload the knee during daily living activities. Doctors usually prescribe the wearing of an unloading orthosis. But are they really efficient ? What are their impact on the tibiofemoral contact forces ?

Possibility to estimate the contact stress : underfeet force sensors + Electromyography + Numerical model (inverse dynamics, musculoskeletic model) Evaluation criteria for braces in the literature : The contact force is not measurable in vivo. Therefore, its reduction by an orthosis cannot be directly evaluated.

However, several researchers have demonstrated a correlation between contact stress and muscle activity. Take into account the size of the device and the pressure applied on skin during the conception.

Fig 3 :

 3 Fig 3 : Evaluation of muscular and ligament forces with different orthosis (3)

Fig 1 :

 1 Fig 1 : Quantitative and qualitative orthosis evaluation methods (1)

Fig 2 :

 2 Fig 2 : Muscle's contribution on the tibiofemoral contact force during the stance phase of the gait cycle (2)

Fig 4 :

 4 Fig 4 : Unloading brace during stance phase of the gait cycle and evaluation of the device with different stiffnesses (K in N/m) (4)