Kevin Boutin
email: kevin.boutin@univ-littoral.fr

Sylvie Marylene Gaudron

Jérémy Denis

Frida Ben

Rais Lasram

Boutin Kevin

Gaudron Sylvie Marylene

Denis Jérémy

Ben Rais

Lasram Frida

Kévin Boutin

Potential marine benthic colonisers of offshore wind farms in the English channel: A functional trait-based approach

Keywords: offshore wind farms, colonisation, benthic species, biological traits, functional diversity, English Channel

come

Introduction

It is now evident that greenhouse gas emissions from human activities are responsible for global warming. According to the Sixth IPCC report, total net anthropogenic greenhouse gas emissions continued to increase from 2010-2019, as did cumulative net emissions since 1850.

Mean annual emissions from 2010-2019 were higher than those in previous decades (IPCC, 2022). To reduce greenhouse gas emissions and meet the demand for energy, renewable energy became a relevant alternative and continues to develop.

In the context of the European Green Deal, which aims to make Europe a climateneutral continent by 2050, the European Union has set several targets to transition energy use, such as having 32.5% of renewable energy in total energy consumption and reducing greenhouse gas emissions 40% by 2030. In Europe and around the world, such as China and the United States of America, the development of offshore wind turbines is a response to the need for renewable energy in the energy mix (de Castro et al., 2019). The influence of this type of infrastructure on the marine environment is complex from technical, legal, societal, and environmental points of view for all stakeholders. This renewable source of marine energy must be integrated into ecosystems that are already subject to multiple human disturbances (e.g. climate change, overexploitation of resources, pollution). Installing and operating OWFs (Offshore Wind Farms) can have many ecological impacts on the marine environment, including wildlife populations, habitats, water quality, and nutrient cycles [START_REF] Degraer | Offshore Wind Farm Artificial Reefs Affect Ecosystem Structure and Functioning: A Synthesis[END_REF][START_REF] Galparsoro | Reviewing the ecological impacts of offshore wind farms[END_REF]. For example, noise pollution and sea bottom destruction can occur immediately during installation of OWFs, whereas other ecological impacts can occur over longer periods, such as the colonisation of benthic species on new structures, known as the "reef effect" [START_REF] Wilhelmsson | Fouling assemblages on offshore wind power plants and adjacent substrata[END_REF].

The reef effect is the colonisation of wind turbines and other artificial substrates (e.g. OWFs, shipwrecks, harbours, oil and gas platforms) by benthic species, which has a large influence on marine biodiversity [START_REF] Svane | On the Problems of Epibioses, Fouling and Artificial Reefs, a Review[END_REF][START_REF] Petersen | Offshore Windmill Farms: Threats to or Possibilities for the Marine Environment[END_REF][START_REF] Kerckhof | Early development of the subtidal marine biofouling on a concrete offshore windmill foundation on the Thornton Bank (southern North Sea): first monitoring results[END_REF][START_REF] Langhamer | Artificial Reef Effect in relation to Offshore Renewable Energy Conversion: State of the Art[END_REF][START_REF] Dannheim | Benthic effects of offshore renewables: identification of knowledge gaps and urgently needed research[END_REF][START_REF] Degraer | Offshore Wind Farm Artificial Reefs Affect Ecosystem Structure and Functioning: A Synthesis[END_REF]. During the operational phase, wind turbine foundations and their scour protection layers create new habitats that are quickly colonised, mainly by larvae of benthic species such as gastropods, bivalves, crustaceans, and polychaetes [START_REF] Wilhelmsson | Fouling assemblages on offshore wind power plants and adjacent substrata[END_REF]Zupan et al., 2023).

Installing an OWF modifies local marine habitats, which implies changes in community assemblage due to the installation of artificial hard substrates on natural soft sediment [START_REF] Kerckhof | Early development of the subtidal marine biofouling on a concrete offshore windmill foundation on the Thornton Bank (southern North Sea): first monitoring results[END_REF][START_REF] Kerckhof | About "Mytilisation" and "Slimeification": a decade of succession of the fouling assemblages on wind turbines off the Belgian coast. Memoirs on the Marine Environment Environmental impacts of offshore wind farms in the Belgian part of the North Sea: making a decade of monitoring, research and innovation[END_REF][START_REF] Dannheim | Benthic effects of offshore renewables: identification of knowledge gaps and urgently needed research[END_REF]. The OWF increases the rapid and abundant colonisation of benthic marine species via larval dispersal, as most of these species have a bentho-pelagic life cycle. At first, the scientific community thought that the new community followed the same temporal dynamics as a colonised natural habitat [START_REF] Kerckhof | Early development of the subtidal marine biofouling on a concrete offshore windmill foundation on the Thornton Bank (southern North Sea): first monitoring results[END_REF][START_REF] Kerckhof | About "Mytilisation" and "Slimeification": a decade of succession of the fouling assemblages on wind turbines off the Belgian coast. Memoirs on the Marine Environment Environmental impacts of offshore wind farms in the Belgian part of the North Sea: making a decade of monitoring, research and innovation[END_REF]. First, the pioneer stage of early colonisers lasts for 2 years after the turbines are installed. The early colonisers are opportunistic, and the species composition depends on the type of foundation [START_REF] Kerckhof | About "Mytilisation" and "Slimeification": a decade of succession of the fouling assemblages on wind turbines off the Belgian coast. Memoirs on the Marine Environment Environmental impacts of offshore wind farms in the Belgian part of the North Sea: making a decade of monitoring, research and innovation[END_REF]. Next, an intermediate stage, 3-5 years after installation, has high species richness [START_REF] Kerckhof | About "Mytilisation" and "Slimeification": a decade of succession of the fouling assemblages on wind turbines off the Belgian coast. Memoirs on the Marine Environment Environmental impacts of offshore wind farms in the Belgian part of the North Sea: making a decade of monitoring, research and innovation[END_REF][START_REF] Degraer | Offshore Wind Farm Artificial Reefs Affect Ecosystem Structure and Functioning: A Synthesis[END_REF]. Finally, the climax stage, 6 years after installation, has biomass dominated by mussels and anemones [START_REF] Kerckhof | About "Mytilisation" and "Slimeification": a decade of succession of the fouling assemblages on wind turbines off the Belgian coast. Memoirs on the Marine Environment Environmental impacts of offshore wind farms in the Belgian part of the North Sea: making a decade of monitoring, research and innovation[END_REF][START_REF] Degraer | Offshore Wind Farm Artificial Reefs Affect Ecosystem Structure and Functioning: A Synthesis[END_REF]. But a recent study challenges this theory, discussing the unstable nature of the community even after 11 years (Zupan et al., 2023). The difficulty of understanding and anticipating succession at the community level could be overcome by both longer-term and large-scale research, where biological interactions are included into the analysis.

Colonisers can influence the diversity of the community [START_REF] Walker | Interactions among Processes Controlling Successional Change[END_REF]Connell and Slatyer, 1997). Some species can help increase its species richness, such as the filter-feeding blue mussel (Mytilus edulis), which is considered positive engineer that facilitates establishment of other species [START_REF] Connell | Mechanisms of Succession in Natural Communities and Their Role in Community Stability and Organization[END_REF][START_REF] Kerckhof | About "Mytilisation" and "Slimeification": a decade of succession of the fouling assemblages on wind turbines off the Belgian coast. Memoirs on the Marine Environment Environmental impacts of offshore wind farms in the Belgian part of the North Sea: making a decade of monitoring, research and innovation[END_REF].

Conversely, other species are considered negative engineers, such as the plumose anemone (Metridium senile), which inhibits establishment of other species by predating their freeswimming larvae [START_REF] Connell | Mechanisms of Succession in Natural Communities and Their Role in Community Stability and Organization[END_REF][START_REF] Kerckhof | About "Mytilisation" and "Slimeification": a decade of succession of the fouling assemblages on wind turbines off the Belgian coast. Memoirs on the Marine Environment Environmental impacts of offshore wind farms in the Belgian part of the North Sea: making a decade of monitoring, research and innovation[END_REF]. This biofouling provides an additional food resource for higher trophic levels within the local marine food web. For example, the foundation of a wind turbine can contain up to 2 t of mussels (Shields and Payne, 2014), which in turn attracts predators. On some OWF, such as a Belgian OWF in the North Sea, the climax community is dominated by the plumose anemone and the blue mussel (i.e. 'slimeification' or 'mytilisation', respectively) [START_REF] Krone | Epifauna dynamics at an offshore foundation -Implications of future wind power farming in the North Sea[END_REF][START_REF] Kerckhof | About "Mytilisation" and "Slimeification": a decade of succession of the fouling assemblages on wind turbines off the Belgian coast. Memoirs on the Marine Environment Environmental impacts of offshore wind farms in the Belgian part of the North Sea: making a decade of monitoring, research and innovation[END_REF].

Installing an OWF can influence species richness of the local community assemblage as well as ecosystem functioning. In the past few decades, the development of trait databases (e.g. FishBase, Polytraits, Arctic Traits) has supported the development of the functional traitbased approach in ecology [START_REF] Martini | Functional trait-based approaches as a common framework for aquatic ecologists[END_REF]. Instead of understanding and classifying species based only on their taxonomy, it does so based on their functional traits, including morphological (e.g. maximum body size), life-history (e.g. mode of reproduction, life span), physiological (e.g. maximum growth rate, feeding regime) and behavioural (e.g. mobility), which determine their role and impact in an ecosystem. Analysing these traits can increase understanding of mechanisms that underlie community assembly, species interactions, and ecosystem functioning [START_REF] Naeem | Disentangling biodiversity effects on ecosystem functioning: deriving solutions to a seemingly insurmountable problem[END_REF][START_REF] Petchey | Functional diversity: back to basics and looking forward[END_REF][START_REF] Nock | Functional Traits[END_REF][START_REF] Degen | Trait-based approaches in rapidly changing ecosystems: A roadmap to the future polar oceans[END_REF].

The functional trait-based approach can address a wide range of ecological issues, including climate change and human impacts. It can be used to compare how functioning differs between assemblages and can highlight initial responses to changes in the functional structure that traditional diversity analysis cannot detect [START_REF] Mouillot | A functional approach reveals community responses to disturbances[END_REF]. Installing human-made structures, including OWFs and the structures they are built on (e.g. foundations, cables), may encourage colonisation of species not present in the local soft-bottom marine habitat that have novel functional traits. This could increase functional diversity and change ecosystem functioning by increasing the functional niche space. The functional trait-based approach can help identify which species are colonising these new habitats and how their functional traits may influence the local ecosystem. We considered the future OWF of Dunkirk (northern France) as a case study to predict consequences of installing OWFs in the eastern EC. The Dunkirk OWF (planned for 2028) is particularly interesting because it is located in the transition zone between the eastern French EC, where no OWF currently exists (but seven are planned), and the southern North Sea. Our goal was to identify potential colonisers and their functional trait profiles. To this end, we compared benthic communities in the EC on natural (e.g. rocks, gravel, pebbles) and artificial hard substrates (e.g. shipwrecks, harbours) (HSEC) to those on OWFs in the North Sea and Irish Sea (OWF), and on oil and gas platforms in the North Sea (O&GP). This was done using traditional community-structure analysis and the functional trait-based approach. The objectives of this study were as follows:

1. Describe the community structure of the three hard-substrates habitats (i.e. HSEC, OWF, and O&GP) and their similarities.

2. Develop a traits profile of the species that colonise each of these three habitats, with emphasis on the dominant traits of species that colonise OWFs.

3. Compare functional characteristics (e.g. functional diversity, species richness) of the three community assemblages to predict the community of the artificial reef created by installing the Dunkirk OWF.

Material and methods

Data collection

The first step in the study was to compile the literature on colonisers of the three habitats of interest (OWF, O&GP, HSEC), and to be able to compare their communities with each other. Data on species community composition were collected from the EC, Irish Sea and the North Sea since the Dunkirk OWF will be located at the transition between these two biogeographic provinces. The literature review identified 7 OWFs (i.e. C Power, Belwind, Egmond aan Zee, Princess Amalia, Horns Rev, Hywind, and North Hoyle) for which lists of colonising species were available, in 13 references and 1 shared data set (Supplementary Material Table A). For O&GP, 28 platforms had lists of colonisers available in 5 references (Supplementary Material Table A). Finally, for HSEC we identified three types of hard substratesnatural hard substrates (e.g. rocks, gravel, pebbles), artificial reefs, and shipwrecksusing 8 references (Supplementary Material Table A). A literature review was performed using Google Scholar and ISI Web of Science, where 28 references have been identified with species lists of colonisers. In these references, species were collected and/or identified via scuba diving, scrape sampling, ROV imagery and Rallier du Baty dredge. We selected only macrofauna (> 1 mm) for our study. We used the WORMS database to verify that all benthic species cited in the literature were identified by the correct species name. A list of species presence [START_REF] Langhamer | Artificial Reef Effect in relation to Offshore Renewable Energy Conversion: State of the Art[END_REF] or absence (0) was then created and transformed into a data frame for each habitat. A for information on the habitats).

Community structure analysis

We built a list of species for each of the three hard-substrates habitats (OWF, O&GP and HSEC). As the characteristics of these three habitats are potentially different (age, shore distance, depth...), we carried out an analysis of the community structure and we made the hypothesis that OWF and O&GP would have closer characteristics compared to HSEC. To this end, we combined the three lists into a single presence/absence data set (Supplementary Material Table B) and calculated a matrix of the Bray-Curtis dissimilarity index using the vegdist function of the vegan package of R software (R Core Team, 2022). We then performed a PERMANOVA (999 permutations, Bray-Curtis dissimilarity index [START_REF] Mcardle | Fitting multivariate models to community data: a comment on distance-based redundancy analysis[END_REF]) on the dissimilarity matrix using the Adonis function of the vegan package. To illustrate similarities among colonisers of the three habitats, we performed hierarchical ascending classification on the dissimilarity matrix using the Ward method, using the hclust function of the stats package of R. Finally, we used a Venn diagram to identify which species the three habitats shared in common.

Functional trait-based approach

After comparing the communities structure between the three hard-substrates habitats, we compared the functional traits of the main colonisers of these three habitats in order to explore whereas it follows the same trend. Based on [START_REF] Degen | The Arctic Traits Databasea repository of Arctic benthic invertebrate traits[END_REF], seven biological traits were selected: one morphological trait (i.e. maximum body size), four lifehistory traits (i.e. mode of reproduction, type of larval development, mode of larval dispersal, and life span), and two behavioural traits (i.e. mobility and feeding regime of juveniles/adults) (Table 1). Some functional traits give information on the state of the community (successional stage and stability) such as maximum body size and longevity.

Other functional traits such as the mode of reproduction, the type of larva and its diet give insights into their potential dispersal strategy and then, colonisation abilities of artificial substrates at a larger scale. Each trait was divided into 3-5 categories, resulting in 27 categories (Table 1). The biological traits were obtained from the literature (Supplementary Material Table C) and from databases (e.g. Polytraits, Marlin, Biotic, Encyclopedia of life). We used a fuzzy coding approach to allocate each species to the categories of a given biological trait (Chevenet et al., 1994), attributing 0 or 3 when a species had no affinity or complete affinity, respectively, with a category. A species could have affinities with multiple categories for a given trait, but the sum of all categories always equalled 3. We then created a data set that contained the main species in each habitat with their fuzzy coded biological traits. Due to the large number of species, an occurrence index (Ir) was calculated for each habitat:

(1)

A species was selected for functional trait-based analysis when it was cited in at least 30% of the references for the targeted habitat. Overall, 68, 56, and 28 species were included in the biological trait matrix for HSEC, OWF, and O&GP, respectively (Supplementary Material Table D). All trait matrices were at the species level and double-checked for accuracy.

To test for independence between trait categories and habitats (HSEC, OWF, O&GP), the fuzzy code values for each category were summed and then transformed into a percentage. This is repeated for each of the three habitats [START_REF] Bolam | Differences in biological traits composition of benthic assemblages between unimpacted habitats[END_REF][START_REF] Zhulay | Functional Pattern of Benthic Epifauna in the Chukchi Borderland, Arctic Deep Sea[END_REF]. Percentage values were used to test the independence using a Chi² test on R.

Significant differences were assessed using Pearson's Chi² post-hoc test in R. In order to obtain a functional profile, we calculated a cumulative score of the functional categories with a threshold greater than or equal to 50%, thus identifying the most represented functional categories for each of the three habitats.

Functional diversity and structure

To take the functional trait approach a step further, trait diversity and community structure were studied using statistical tools. Two functional diversity indices were calculated to better understand the functional characteristics of each habitat's community. First, the mean functional richness (FRic) was estimated as the percentage of the functional volume of each habitat's community derived from a multidimensional functional space [START_REF] Mouchet | Functional diversity measures: an overview of their redundancy and their ability to discriminate community assembly rules[END_REF], which revealed how much of the functional niche space was filled by the species present [START_REF] Degen | Trait-based approaches in rapidly changing ecosystems: A roadmap to the future polar oceans[END_REF]. The second index was Rao's quadratic entropy (RaoQ), which measures trait dissimilarity and ranges from 0 (i.e. low functional diversity: species in the community have similar functional trait profiles) to 1 (i.e. high functional diversity: species in the community have unique functional trait profiles) [START_REF] Botta-Dukát | Rao's quadratic entropy as a measure of functional diversity based on multiple traits[END_REF]. The two functional indices were calculated using the dbFD function of the FD package [START_REF] Laliberté | A distance-based framework for measuring functional diversity from multiple traits[END_REF] of R. The functional spaces were constructed using principal coordinate analysis (PCoA), which encapsulated unique trait combinations of species by substrate [START_REF] Laliberté | A distance-based framework for measuring functional diversity from multiple traits[END_REF], performed on species-by-trait and habitats-by-species data sets (Supplementary Materials E and F).

To visualise which trait influenced the functioning of each hard substrate, we performed multiple factor analysis (MFA) [START_REF] Escofier | Multiple factor analysis (AFMULT package)[END_REF] of species using trait data sets in which species were grouped by habitat (Supplementary Material G). MFA is a modified PCoA that can consider categorical data and thus gives equal weight to traits that have different numbers of categories [START_REF] Mclean | Trait similarity in reef fish faunas across the world's oceans[END_REF]. Associations between traits and substrates were assessed based on the contributions of trait values to the two first axes. MFA was performed using the MFA function of the FactoMineR package of R. Principal component analysis was then performed using data from the MFA to obtain a correlation circle of the functional traits using the fviz_contrib function of the factoextra package of R.

Finally, the functional space of each habitat was plotted using the coordinates of the species in the overall functional space provided by the MFA.

The overlap of functional polygons between the three hard-substrates habitats was calculated using a Monte Carlo method, usually performed to study niche regions (Swanson et al., 2015). The Bayesian probabilistic method estimates size and pairwise polygon overlap without considering sample size (e.g. number of main species per habitats in our study).

Overlaps were estimated from the species coordinates of the two first axes of the PCoA for each of the main species. Average overlap between functional polygons with 95% Bayesian intervals based on 10,000 iterations in bivariate dimension. The analyses were performed using the nicheROVER package (Lysy et al., 2021) of R.

The functional diversity indices and MFA visualisation were repeated on trait matrices by removing species with direct development (trait L3, Table 1) due to their absence from the main species list of O&GP colonisers (but not from the entire species list) but not in HSEC and OWF species' lists. Opportunist/Scavenger FH5 Carnivore

Results

Community structure analysis of hard substrates

The literature review of colonisers identified 384, 265, and 559 species for OWF, O&GP, and HSEC, respectively (Supplementary Material Table B). A total of 14 phyla were represented, of which 4 dominated (i.e.  58% of species in each habitat): Arthropoda, Annelida, Mollusca, and Cnidaria (Fig. 2). The PERMANOVA revealed that habitat had a significant (P < 0.05) effect on species communities (Supplementary Material H). The hierarchical classification showed that the community of HSEC (Height = 0.741) differed from those of O&GP and OWF (Height = 0.576), which were more similar to each other.

The Venn diagram indicated 84 species in common among all three habitats, with OWF and HSEC having the most (n = 73) and HSEC and O&GP having the fewest (n = 29) (Fig. 3).

Biological trait profiles of hard substrates

When categories of each of the seven biological traits were compared among the habitats, at least one of the categories differed among habitats, except for the mobility trait (P > 0.05) (Fig. 5, Supplementary Material I). For the reproduction trait, category hermaphrodite was represented less in O&GP than in the other two habitats. Benthic, direct larval development, and the feeding mode associated to direct development mode were not represented in O&GP.

The percentage of planktotrophic larvae was higher in OWF and O&GP than in HSEC. For the life span trait, category < 2 years dominated in OWF but not in the other two habitats. Life span category 2-5 years was absent in O&GP. For the diet of the colonisers, category suspension feeder was represented less in O&GP than in the other two habitats, and category carnivore was represented less in HSEC than in the other two habitats. The percentage contributions of the most represented categories of the seven biological traits varied among habitats (Supplementary Material Table J). For HSEC and O&GP, the categories represented most for maximum body size were 10-50 mm and 100-300 mm.

For OWF, the categories represented most were 10-50 mm and 50-100 mm. For reproduction, category gonochoric dominated in HSEC, O&GP, and OWF For HSEC, O&GP, and OWF, larval development was mainly pelagic and larval diet was mainly planktotrophic, however, lecithotrophic larva was also highly represented in HSEC. For life span, the most represented categories were 2-5 years and 5-20 years for HSEC, 5-20 years and > 20 years for O&GP, and < 2 years and 5-20 years for OWF. For mobility, sessile organisms dominated in HSEC, O&GP, and OWF. For feeding habit, for HSEC and OWF, colonisers were either suspension feeders or carnivores, whereas for O&GP, carnivores dominated

Functional diversity and structure

FRic and RaoQ were highest for HSEC (0.68 and 0.53, respectively) and lowest for O&GP (0.07 and 0.42, respectively).

Table 2. Functional diversity indices (functional richness (FRic) and Rao's quadratic entropy (RaoQ)) based on the biological traits of the main species (n = number of species).

Bold indicates the highest indicator values.

Habitat n FRic RaoQ

Hard substrates in the English Channel 68 0.68 0.53 Offshore wind farms 56 0.54 0.50 Oil and gas platforms 28 0.07 0.42

In the MFA, the first two axes of the correlation circle explained 27.7% (14.8% and 12.9%, respectively) of the variability in the data set (Fig. 6). Eight categories had a high contribution: organisms with pelagic larval development, direct development, a planktotrophic larval diet, and sessile and crawling adult organisms with a life span less than 2 years or 5-20 years. first axes (see Table 1 for definitions of the category codes)

Species were grouped by their biological traits within the functional space created by the MFA. Polygons were drawn for each habitat by connecting the outermost species in the scatterplot (Fig. 7). According to the FRic, the functional volumes of HSEC and OWF were relatively similar in size, whereas that of O&GP was smaller. Overlap analyses revealed that HSEC functional polygon is covered by 35.1% and 91.6% of the O&GP and OWF functional polygons respectively. O&GP functional polygon is covered by 96.9% and 94.5% of HSEC and OWF functional polygons respectively. Finally, OWF functional polygon is covered by 85.3% of HSEC and 27.1%

of O&GP functional polygons respectively (Supplementary materials L).

Discussion

Installation of OWFs is known to influence marine ecosystems, such as by for instance causing the reef effect [START_REF] Wilhelmsson | Fouling assemblages on offshore wind power plants and adjacent substrata[END_REF] or stepping-stone effect [START_REF] De Mesel | Succession and seasonal dynamics of the epifauna community on offshore wind farm foundations and their role as stepping stones for nonindigenous species[END_REF], or by rendering habitats more complex (i.e. transition from soft substrates to hard substrates) [START_REF] Degraer | Offshore Wind Farm Artificial Reefs Affect Ecosystem Structure and Functioning: A Synthesis[END_REF]. As an example to anticipating the impact of colonisation by benthic organisms on artificial man-made structures, we applied our method to the English Channel marine ecosystem, in relation to the French energy transition objectives, that plans to install seven OWFs within the EC in the next decade. This requires predicting the influence of OWFs on marine ecosystems, particularly on benthic communities in the EC. The present study focused specifically on the reef effect of benthic species and showed that community structure was more similar between the two human-made structures (OWFs and O&GP), whereas functional diversity was more similar between the communities of OWF and HSEC.

Beyond the French case, our results could be of interest for the whole English Channel.

Comparison of communities in the three habitats

The list of colonisers highlighted similarities and differences in community structure among the three habitats: the species composition of HSEC differed from those of OWF and O&GP, which were more similar to each other. However, the community structure analysis was based only on the presence/absence of species in each habitat, and thus provided a qualitative overview of the composition of assemblages. Natural and artificial substrates have been compared [START_REF] Coolen | Benthic biodiversity on old platforms, young wind farms, and rocky reefs[END_REF][START_REF] Pinto | Shipwrecks fouling community: Similarities with natural rocky reefs at different distances and wave exposure regimes[END_REF] to identify parameters that can explain differences in their communities. Several hypotheses were explored, such as the substrate's type (e.g. rock vs. steel), complexity (e.g. surface area, rocks, crevices [START_REF] Atilla | Effects of habitat complexity and hydrodynamics on the abundance and diversity of small invertebrates colonizing artificial substrates[END_REF][START_REF] Coolen | Reefs, sand and reef-like sand: A comparison of the benthic biodiversity of habitats in the Dutch Borkum Reef Grounds[END_REF]). Zupan et al. (2023) showed that the age and type of substrate had significant effects on species composition. The type of substrate (concrete, steel and complexity) is a well-known factor in the marine environment according to multiple colonisation experiments with different types of substrates that influenced the assemblage of colonisers [START_REF] Taniguchi | Effects of habitat complexity on benthic assemblages in a variable environment[END_REF][START_REF] Burt | Coral recruitment and early benthic community development on several materials used in the construction of artificial reefs and breakwaters[END_REF][START_REF] Gaudron | Colonization of organic substrates deployed in deep-sea reducing habitats by symbiotic species and associated fauna[END_REF]Osman, 2015). The type of substrate could explain the differences in species composition of HSEC vs.

those of OWF and O&GP as HSEC samples are often located on seabed, while OWF and O&GP samples are usually taken at mid-water depth. A recent study showed the impact of depth on marine species richness and diversity in benthic colonisers (Coolen et al., 2022).

Another hypothesis is that biofilm that develops on hard substrates can influence the substrates that larvae choose during colonisation [START_REF] Hadfield | Biofilms and Marine Invertebrate Larvae: What Bacteria Produce That Larvae Use to Choose Settlement Sites[END_REF]. It can also influence metamorphosis during the transition from larval to post-larval stages (Shitema, 2012). Thus, it would be interesting to study the biofilm composition of hard substrates to identify whether it can explain community differences. [START_REF] Tan | Differences in Intertidal Microbial Assemblages on Urban Structures and Natural Rocky Reef[END_REF] compared biofilm composition on natural (i.e. rocky shores) and artificial (i.e. seawall) substrates, and observed no difference in biofilm composition, but did observe a difference in the relative abundance of biofilm organisms. Other environmental factors could explain the differences in species composition of HSEC vs. those of OWF and O&GP. For example, depth is known to influence species richness on hard substrates, with maximum richness from 15 or 25 m to 75 m in depth [START_REF] Clarke | Spatial patterns of diversity in the sea: bryozoan species richness in the North Atlantic[END_REF][START_REF] Van Der Stap | Marine Fouling Assemblages on Offshore Gas Platforms in the Southern North Sea: Effects of Depth and Distance from Shore on Biodiversity[END_REF][START_REF] Coolen | Benthic biodiversity on old platforms, young wind farms, and rocky reefs[END_REF]. Distance to shore can also impact species diversity [START_REF] Van Der Stap | Marine Fouling Assemblages on Offshore Gas Platforms in the Southern North Sea: Effects of Depth and Distance from Shore on Biodiversity[END_REF][START_REF] Reeves | Barnacle settlement and growth at oil and gas platforms in the northern Gulf of Mexico[END_REF]. However, the spatial aspect should be considered, as OWF and O&GP were not present in the EC during our study.

Although species assemblages of OWF and O&GP (mainly in the North Sea) differed from that of HSEC, 84 taxa were common to all three habitats. These species are likely to colonise the future Dunkirk OWF and, more broadly, all OWFs installed in the EC in the near future.

Interestingly, 73 taxa were common to HSEC and OWF, which increases the number of potential colonisers of the Dunkirk OWF to 157. From a broader perspective, this means that a fraction of benthic organisms already present in the area where the offshore parks are located will potentially colonise them. The use of the functional profile of colonisers could then allow identifying this fraction of colonisers thanks to their functional traits. But this method is likely to overestimate the colonisers potential, because the number of taxa observed in the literature was always less than 157 (e.g. 78 species by [START_REF] Kerckhof | A comparison of the first stages of biofouling in two offshore wind farms in the Belgian part of the North Sea. Offshore wind farms in the Belgian Part of the North Sea: Heading for an understanding of environmental impacts[END_REF], 63 by [START_REF] Kerckhof | Early development of the subtidal marine biofouling on a concrete offshore windmill foundation on the Thornton Bank (southern North Sea): first monitoring results[END_REF], 121 by Karlsson et al. (2021), 85 by [START_REF] Vanagt | Development of hard substrate fauna in the Princess Amalia Wind Farm Monitoring 3.5 years after construction[END_REF], 70 by [START_REF] Leonhard | Hard bottom substrate monitoring Horns Rev offshore wind farm[END_REF], and 55 by [START_REF] Bouma | Benthic communities on hard substrates within the first Dutch offshore wind farm (OWEZ)[END_REF]). In this study, the case of the future OWF of Dunkirk is particularly interesting because it is located in the transition zone between the eastern French EC, where no OWF currently exists (but seven are planned), and the southern North Sea where numerous OWF are already implemented. The methodology and the results obtained for the French case study could be of interest to any other future OWF.

Biological traits of species on hard substrates

Over the past decade, the functional trait-based approach has been widely adopted and seen as a complementary to species-based approaches [START_REF] Degen | The Arctic Traits Databasea repository of Arctic benthic invertebrate traits[END_REF]. Biological trait analysis of colonisers of the three habitats highlighted that gonochoric reproduction, pelagic larval dispersal, and sessile juveniles/adults were the categories represented most in each of the three habitats. However, dominant traits differed among the habitats, including maximum body size, larval diet, life span, and adult feeding. Colonisers were smallest for OWF (i.e.

maximum body size of 50-100 mm), mostly intermediate for HSEC (i.e. 10-50 or 100-300 mm), and largest for O&GP (i.e. 100-300 or 10-50 mm). A similar trend was observed for life span, which was shortest for OWF colonisers (i.e. < 2 or 5-20 years), intermediate for HSEC (i.e. 2-5 or 5-20 years), and longest for O&GP colonisers (i.e. 5-20 or > 20 years).

According to the literature, the maximum body size and life span of colonisers provide information on the stage of the community [START_REF] Bolam | Macrofaunal production and biological traits: Spatial relationships along the UK continental shelf[END_REF][START_REF] Bremner | Species' traits and ecological functioning in marine conservation and management[END_REF]Cain et al., 2014;[START_REF] Costello | Biological and ecological traits of marine species[END_REF][START_REF] Emmerson | The importance of body size, abundance, and food-web structure for ecosystem functioning[END_REF][START_REF] Micheli | Low functional redundancy in coastal marine assemblages[END_REF][START_REF] Norkko | Size matters: implications of the loss of large individuals for ecosystem function[END_REF][START_REF] Van Der Linden | The performance of trait-based indices in an estuarine environment[END_REF]. As OWF colonisers were smaller and had a shorter life span, the OWF community could be considered fast growing, highly productive, and less sensitive to disturbance, which indicates a younger community. Due to their larger body size and longer life span, O&GP colonisers could be considered slow growing, less productive, and more sensitive to disturbance. Biological traits of the HSEC community could be intermediate because the substrates are of different types (i.e. intertidal rocky shore, pebbles, shipwrecks, concrete) and ages (i.e. 4 to ca. 80 years). The first theory about benthic community succession on offshore marine structures was that it follows the same rules as that in other ecosystems, with pioneer, intermediate, and climax stages [START_REF] Kerckhof | Early development of the subtidal marine biofouling on a concrete offshore windmill foundation on the Thornton Bank (southern North Sea): first monitoring results[END_REF]. et al., 2023) showed that after 11 years communities are still changing and two other theories are put forward, first several stable or climax communities theory (Sutherland, 1974) and the repeated successional pathway of the cycle climax theory (Oshurkov, 1992). Therefore, the age of the community should be considered when using a functional trait profile. Pioneer species are generally small due to harsh abiotic conditions and relatively low nutrient availability [START_REF] Macarthur | The Theory of Island Biogeography[END_REF][START_REF] Thornton | Island Colonization: The Origin and Development of Island Communities[END_REF][START_REF] Dykman | Functional traits provide new insight into recovery and succession at deep-sea hydrothermal vents[END_REF], whereas species at the climax stage are relatively larger, with slower growth, and influence the establishment of other species [START_REF] Hirata | Succession of sessile organisms on experimental plates immersed in Nabeta Bay, Izu Peninsula, Japan. I. Algal succession[END_REF][START_REF] Tilman | Plant Strategies and the Dynamics and Structure of Plant Communities[END_REF], Teixido et al., 2004). Therefore, according to their functional profiles, OWF assemblages in the present study were in the transition between pioneer and intermediate stages of succession, whereas O&GP assemblages were at the climax stage. These observations for a mean age of the OWFs (3 years) and O&GP (21 years) during sampling agree with the succession observed by [START_REF] Degraer | Offshore Wind Farm Artificial Reefs Affect Ecosystem Structure and Functioning: A Synthesis[END_REF]. Our results suggest that O&GP can be used as long-term predictions of communities of OWF colonisers at the climax stage, information during the younger stages are needed to fully support this statement.

Our results also revealed relevant information on feeding habits. In the study of [START_REF] Degraer | Offshore Wind Farm Artificial Reefs Affect Ecosystem Structure and Functioning: A Synthesis[END_REF], offshore hard substrates were generally dominated by suspension feeders, but our study showed that carnivores dominated in OWF and O&GP. This could be due to having used a qualitative approach instead of a quantitative approach based on biomass or abundance, which were not available for this study. The main functional traits of species in a targeted habitat could be used to predict colonisation of human structures. More concretely, the functional profile of OWF colonisers defined in the present study could be used to identify which potential colonisers already living in the EC could colonise the seven future OWFs based on their functional traits.

Functional diversity and structure

The functional diversity indices showed greater functional similarity between the assemblages of OWF and HSEC, which differed from those of O&GP. HSEC had the highest functional diversity indices, but those of OWF were higher than those of O&GP, which had the smallest functional volume (perhaps mainly due to the absence of species with direct larval development within the main species list) and thus seemed to be an unstable habitat [START_REF] Tilman | Functional Diversity[END_REF]. For HSEC and OWF, arthropods and molluscs were the main species with direct larval development. Although not on the list of main species used for functional trait analysis, arthropods with direct larval development were present in O&GP (e.g. in Amphipoda, Decapoda, and Isopoda Orders), but they were not identified to the species level.

Taxonomic resolution can influence the results of functional analysis of a community.

According to [START_REF] Poff | Functional trait niches of North American lotic insects: traits-based ecological applications in light of phylogenetic relationships[END_REF], family-level resolution can result in loss of information, particularly for families with genera that have multiple trait characteristics. Thus, genus-level resolution could detect biological or ecological responses more accurately. While the species level is the highest resolution and can detect the smallest biological or ecological responses, it is also sensitive to redundancy due to congeneric species that are functionally equivalent and thus considered ecologically equivalent [START_REF] Wiggins | Some Relationships between Systematics and Trophic Ecology in Nearctic Aquatic Insects, with Special Reference to Trichoptera[END_REF]. This most accurate level was able to detect subtler biological and ecological responses than using family or genus, which are less accurate [START_REF] Poff | Functional trait niches of North American lotic insects: traits-based ecological applications in light of phylogenetic relationships[END_REF]. However, identifying taxa to the species level can also be negative because it may result in excluding many individuals that cannot be identified, as in our study, which may have biased comparison of the ecological functioning of the three habitats. Repeating the biological trait analyses in this study after removing species with a direct development trait showed the same trends as the original biological trait analyses (i.e. smaller functional indices and volumes for O&GP than for the two other habitats) (Supplementary Material K).

Overall, HSEC seems to be the most stable and resilient of the three habitats studied. (2023) recently challenged the idea that OWFs will tend to a stable climax stage as their longest monitoring program, the current state of knowledge requires further studies on longterm colonisation of artificial substrates.

Conclusion

Installing an OWF creates a new habitat that benthic organisms can colonise. Focusing on functional traits helped to identify species responses to environmental disturbances and their effects on ecosystems [START_REF] Carmona | Traits Without Borders: Integrating Functional Diversity Across Scales[END_REF], which is relevant for studying the influence of OWFs on ecosystems. Our case study indicated how this new artificial substrate could influence benthic communities and their functioning. As functional traits can be used across species and geographic ranges [START_REF] Bernhardt-Römermann | Functional traits and local environment predict vegetation responses to disturbance: a pan-European multi-site experiment[END_REF], we compared different communities that form many habitats (i.e. OWF, O&GP, and HSEC) in different areas (i.e.

EC, North Sea, and Irish Sea). Based on functional trait profiles, we identified 157 taxa that could colonise future OWFs built in the EC. Qualitative analysis of OWFs in the North Sea showed that their functional diversity is relatively similar to that of hard substrates already present in the EC during the intermediate successional stage of the community. It would be interesting to replicate this approach using abundance and biomass data and to apply it to all of the species sampled to quantify the functional diversity of OWFs.

Figure 1 .

 1 Figure 1. Locations of the three hard substrate habitats (oil and gas platforms, hard substrates in the English Channel, and offshore wind farms) with a species list found in the literature (see Supplementary Material TableAfor information on the habitats).

Figure 2 .

 2 Figure 2. Percentage of each species colonising the three habitats, by phylum. (HSEC: hard substrates in the English Channel, O&GP: oil and gas platforms, and OWF: offshore wind farms)

Figure 3 .

 3 Figure 3. Venn diagram of the taxa shared among the substrates for all species inventoried (HSEC: hard substrates in the English Channel, O&GP: oil and gas platforms, and OWF: offshore wind farms)

Figure 5 .

 5 Figure 5. Percentage of each category of the seven biological traits selected (A) maximum body size, B) reproduction, C) larval development, D) larval diet, E) life span, F) mobility, and G) feeding habit) for the three habitats (HSEC: hard substrates in the English Channel, O&GP: oil and gas platforms, OWF: offshore wind farms)

Figure 6 .

 6 Figure 6. Correlation circle resulting from the multifactorial analysis, showing the percentage of contribution (contrib) of all 27 categories of the 7 functional traits to the two

Figure 7 .

 7 Figure 7. Functional polygons of the three habitats, top left is the overlap of hard substrates in the English Channel (red), oil and gas platforms (green), and offshore wind farms (blue), species are represented by points. Dimensions 1 and 2 explained 14.8% and 12.9% of the variance, respectively.

  [START_REF] Degraer | Offshore Wind Farm Artificial Reefs Affect Ecosystem Structure and Functioning: A Synthesis[END_REF] identified these three stages of succession on wind turbines on the Belgian coast in the North Sea, with the pioneer stage from 0-2 years, the intermediate stage from 3-5 years, and the climax stage from 6 years after installation. But a recent study (Zupan

  At the mean age of OWF (i.e. 3 years) our study indicates a high functional diversity supported by the functional indexes values and high overlap values of the functional polygons. OWF had a functional diversity similar to those of the communities already present in HSEC. AsCoolen et al. (2022) andZupan et al. (2023) demonstrated that the greatest specific richness and diversity were reached around 6 years, the maximum functional similarity between OWF and HSEC could be reached at this period. Conversely, using O&GP as a long-term reference indicates that community functional diversity may decrease on OWFs during years. This agrees with[START_REF] Kerckhof | About "Mytilisation" and "Slimeification": a decade of succession of the fouling assemblages on wind turbines off the Belgian coast. Memoirs on the Marine Environment Environmental impacts of offshore wind farms in the Belgian part of the North Sea: making a decade of monitoring, research and innovation[END_REF], who observed that mussels and anemones dominated long-term communities colonising wind turbines. Because Zupan et al.

Table 1 .

 1 The biological traits and their categories used in the functional trait-based approach to identify the main species colonising hard substrates

	Biological trait Category Definition
	Maximum body	S1	Small (< 10 mm)
	size	S2	Small-medium (10-50 mm)
		S3	Medium (50-100 mm)
		S4	Medium-large (100-300 mm)
		S5	Large (> 300 mm)
	Reproduction	R1	Asexual (e.g. budding, fission)
		R2	Gonochoric
		R3	Hermaphrodite
	Larval	L1	Pelagic
	development	L2	Benthic
		L3	Direct (no larval stage)
	Larval diet	LD1	Planktotrophic
		LD2	Lecithotrophic
		LD3	Direct (no larval stage)
	Life span	A1	Short (< 2 years)
		A2	Short-medium (2-5 years)
		A3	Medium-long (5-20 years)
		A4	Long (> 20 years)
	Mobility	MO1	Sessile
		MO2	Burrower
		MO3	Crawler
		MO4	Swimmer
	Feeding habit	FH1	Deposit feeder
		FH2	Suspension feeder
		FH3	Herbivore
		FH4

  The larger functional volumes of HSEC and OWF were explained by species with direct larval development, such as, for

HSEC, the molluscs Buccinum undatum, Nucella lapillus, Calliostoma zizyphinum, and Musculus discors; the crustaceans Melita palmata and Phtisica marina; and the echinoderm Amphipholis squamata; and for OWF, the crustaceans Idotea pelagica, Monocorophium sextonae, Stenothe marina, S. valida, P. marina, Jassa herdmani, J. marmorata, and Caprella linearis.

Acknowledgements KB is supported by a Ph.D. fellowship funded by the Université Littoral Côte d'Opale and EDF Renouvelables. The authors thank the WindServ project and France Energie Marine for financial support; S. Degraer, F. Kerckhof, Y. Muller, I. Richard, and C. Perron for sharing data; and C. Hennion and N. Spilmont for their expert advice.

Funding

This study was funded by the Université Littoral Côte d'Opale and EDF Renouvelables. The authors declare no financial or personal conflicts of interest. This work has also benefited from the grant "ANR-21-EXES-00 11" as part of the IFSEA Graduate School, which originates from National Research Agency under the Investments for the Future program as well as from CPER IDEAL.


F Jomard

R Gillet

M Bouras

I Stenger

J Barjon

HAL is

Ionic analysis of phosphorus doped-diamond homoepilayers grown with different carbon isotopic abundances F. Jomard 1 , R. Gillet 1 , M. Bouras 1 , I. Stenger 1 , J. Barjon 1 , Marie-Amandine Pinault-Thaury 1* 1 Groupe d'Etude de la Matière Condensée (GEMaC-UMR8635), CNRS, Université de Versailles St-Quentin-En-Yvelines (UVSQ), Université Paris-Saclay, 45 av des Etats Unis, 78035 Versailles Cedex, France *marie-amandine.pinault-thaury@uvsq.fr Diamond has exceptional properties that make it a promising material for many applications in several fields. For several decades, many studies have been carried out to study the nature and the impact of impurities in diamond films synthesized by chemical vapor deposition (CVD). Doping impurities can be added in a controlled manner into the gas mixture during the growth process and incorporated into CVD diamond films. Among them, phosphorus is a donor when it replaces carbon of the crystal lattice. To date, it gives the highest n-type electronic conductivities. Nitrogen is also a well-known impurity in synthetic diamond. Coupled with vacancies (missing carbon atoms in the lattice, denoted V), it forms interesting N-V complexes for optically active centers, such as colored centers or single photon sources.

Recently, phosphorus donors in homoepitaxial diamond have been shown to increase the coherence time of N-V centers [1], paving the way for new applications in quantum technology. This breakthrough was achieved thanks to the progress made on the quality of CVD diamonds and in particular techniques allowing the elimination or reduction of undesirable defects such as the nuclear spins of the isotope 13 of carbon ( 13 C), obtained in a low range of doping in phosphorus (< 1x10 17 at/cm 3 ) [2]. For several years, GEMaC studies n-type diamond through the synthesis of phosphorus-doped diamond films thanks to microwave plasma assisted CVD. Recently, a gas line dedicated to methane isotopically depleted in 13 C ( 13 C/ 12 C = 0.01% instead of 1.10% for natural methane) has been installed. Using standard growth conditions, homoepilayers were synthetized on commercial HPHT Ib (100) diamond substrates with a gaseous mixture of methane either isotopically depleted in 13 C, or of natural isotopy. Samples were analyzed by secondary ion mass spectrometry (SIMS). Compared to the layer grown with natural isotopic carbon, nitrogen is detected in the 13 C-depleted layers which have higher thicknesses and higher phosphorus contents. These results suggest nitrogen contamination of the layer from the new gas line. The ionic analysis also gives the isotopic ratio of carbon in the layers grown with natural methane or 13 C isotopically depleted methane. The carbon-12 isotopic purity reaches 99.99966% (i.e. 0.00034% in 13 C) in 13 C-depleted homoepilayer against 99.989% for natural isotopic homoepilayer (i.e. 0.011% in 13 C). To our knowledge, this value is currently a record.

[1] E.D. Herbschleb et al. Nature Communications, 10, 3766 (2019).

[2] A. Watanabe et al., Carbon, 178 (2021), 294-300.

Dr. Marie-Amandine Pinault-Thaury is a researcher of the French National Center for Scientific Research (CNRS), working at the "Groupe d'Etude de la Matière Condensée" (GEMaC) laboratory. The GEMaC lab is a joint research unit (UMR) between CNRS and the University of Versailles Saint-Quentin-en-Yvelines (UVSQ). It is located in Versailles, close to Paris (France), on the site of the Faculty of Sciences of the UVSQ. Dr. Marie-Amandine Pinault-Thaury coheads the Semiconductors Axis. She is also in charge of the diamond synthesis and of the ion analysis of materials (through an open facility focused on secondary ion mass spectrometry, SIMS). She is an expert in epitaxy and physical study of semiconductors. Since more than 15 years, she studies diamond, especially its doping and the influence of the impurities/defects on its physical properties. Ten years ago, she has discovered a new growth window allowing the full incorporation of phosphorus in donor sites in (100) oriented diamond. More recently, in 2019, she evidences a breakthrough towards bipolar diamond devices with phosphorus ntype doping on (113) oriented diamond.


M A Pinault-Thaury

Mohamed Bouras

Raid Gourad

Karine Isoird

Fuccio Cristiano

Josiane Tasselli

Grégory Grosset

Yohan Spiegel

Rémi Gillet

François Jomard

Lo

Locally Ion Implantation and Annealing Effects in Diamond

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

Locally Ion Implantation and Annealing Effects in Diamond M. Bouras 1 , R. Gourad 2 , K. Isoird 2 , F. Cristiano 2 , J. Tasselli 2 , G. Grosset 3 , Y. Spiegel 3 , R. Gillet 1 , F. Jomard 1 , M-A. Pinault-Thaury 1* 1 GEMaC-CNRS/UVSQ, Université Paris-Saclay, Versailles, France 2 LAAS-CNRS, Université de Toulouse, CNRS, UPS, Toulouse, France 3 Ion Beam Service, ZI Peynier Rousset, rue Gaston Imbert, F-13790, France *marie-amandine.pinault-thaury@uvsq.fr Diamond has demonstrated interesting properties for high power applications. However numerous technological obstacles make difficult the fabrication of power devices on diamond. Diamond doping in-situ gas phase is today the most efficient technique. In fact, the possibility to dope locally by ion implantation is indispensable for establishing a diamond manufacturing chain in particular to achieve the highest possible doping.

In 2014 successful incorporation of implanted phosphorus in (100) diamond donor sites show promising perspectives to process convinced implanted n-type doping [1]. However, the absence of dopant electrical activation after implantation and thermal annealing is a technological obstacle to be removed to achieve localized n-type and p-type doping.

In this work, we focus our attention on boron over-doped implanted diamond layer. We performed implantation on (100)-oriented diamond single crystals by high temperature beam line ion implantation and by beam line followed by a co-implantation plasma immersion ion implantation (PIII). The boron depth profiles in the implanted diamonds are measured by secondary ion mass spectrometry (SIMS). They confirm an almost constant concentration of implanted species at a 200 nm depth (box-profiles): 1.6×10 20 B/cm3 for high temperature implantation. Plasma immersion ion implantation (PIII) add a boron concentration peak of 2-3×10 20 B/cm3 at diamond extreme surface. Transmission Electron Microscopy (TEM) images performed on as implanted samples indicate damages on diamond crystal induced by implantation, but no amorphization. After high thermal annealing at 1700°C during 30 min, SIMS analysis evidences the loss of the boron surface peak obtained by PIII while diamond recrystallization is observed by TEM together with an increase of the diamond surface roughness.

The comparison between the four-probes measurements on as implanted samples and after annealing shows a decrease of the measured sheet-resistance. This demonstrates a benefit of thermal annealing on the electrical activation of implanted boron. Hall measurements will complete these first results to evaluate the efficiency of both boron implantation and annealing conditions.

[1] Barjon et al. Physical Review B 89 (2014) 045201