Raphaël Le Bidan
email: raphael.lebidan@enst-bretagne.fr

Christophe Laot

Dominique Leroux

Annie Godet

Real-time turbo-equalization on the TMS320C5509 -Improving the reliability of broadband wireless links

Introduction

Digital transmission over wireless links will typically encounter two major impediments to reliable communications, namely additive noise and intersymbol interference (ISI). Additive noise is a phenomenon of all practical transmission systems and is usually mitigated through the use of channel coding techniques, which add redundancy to the information message and thereby provide the receiver with the ability to detect and/or correct errors. ISI results from some form of time dispersion over the transmission medium. It arises when successive transmitted symbols are smeared in time and thus overlap at the receiver input up to the point that they may be no longer distinguishable as distinct pulses. Over radio links, this time dispersion is the natural consequence of multi-path propagation where the transmitted signal is received after it reflects off buildings or other obstacles. From a frequency domain perspective, the channel transfer function then exhibits frequencydependent attenuations and delays over the transmission bandwidth, hence the alternative name frequency-selective channels (figure 1).

Figure 1: Frequency response of a typical ISI channel

The impairments caused by ISI are greater when successive symbols are spaced more closely in time in order to increase the data rate, and when the bandwidth restrictions become more stringent. The effects of ISI may be so large in some pathological channel conditions as to preclude reliable transmission even in the absence of noise. Considering, for example, the recently approved IEEE 802.16a standard for wireless metropolitan area networks, specially designed to operate in non line-of-sight propagation's conditions, it is not uncommon to encounter highly dispersive channels exhibiting delay spreads that span up to a hundred symbol periods. Appropriate signal processing is then required at the receiver side to combat the distortion caused by ISI. Multicarrier modulation, such as Orthogonal Frequency Division Multiplexing (OFDM), is a well-established technology to eliminate transmission problems with multipath propagation. However, we focus here on the more traditional approach which combines single-carrier transmission with equalization at the receiver unit, a solution dating back to the early days of digital communication. The equalization process may be understood in the broad sense as an attempt to compensate for channel distortions.

Combining equalization and decoding

To be more specific, let us consider the basic transmitter configuration shown at the top of figure 2. Source bits go first through a channel encoder (a convolutional encoder, for instance) which adds redundancy to the transmitted message. The resulting coded message is then interleaved at bit level, and finally modulated for passband transmission over a frequency-selective channel.

Figure 2: Block diagram of the overall transmission scheme

We now turn our attention to the receiver design. In the presence of channel coding at the transmitter, it seems intuitively desirable to take advantage of the errorcorrection capability (the so-called coding gain) offered by the code redundancy in order to improve the equalization process. Classical estimation theory tells us that the optimal receiver minimizing the bit-error rate (BER) should then perform equalization and decoding in a joint manner, by taking simultaneously the constraints imposed by the code, the interleaver and the ISI channel. However, the resulting receiver is known to be intractable in practice since its complexity grows exponentially with message length. Hence, communication system designers usually resort to a suboptimal but nonetheless more practical two-stage approach where equalization and decoding are performed separately (as done, for example, in GSM mobile phones). A major breakthrough occurred in 1995 with the pioneering work of Douillard et al on Turbo-Equalization [START_REF] Douillard | Iterative Correction of Intersymbol Interference : Turbo-Equalization[END_REF]. The turbo-equalizer establishes an iterative exchange of probabilistic "soft" information between the equalizer and decoder, so that each function benefits from the result of the other task (figure 2). The resulting iterative receiver has been shown to significantly outperform the previous approach, while maintaining a reasonable complexity with respect to the optimal solution.

Turbo-equalization is a receiver structure that has evolved over almost a decade of academic research into a mature technology with remarkable performance gains over conventional systems, and for which we now foresee practical applications. The remainder of this article focuses on the real-time implementation of a so-called Minimum Mean-Square Error (MMSE) turbo-equalizer on a Texas Instruments TMS320VC5509 device, a low-cost 16-bit fixed-point DSP typically targeted towards embedded communication applications such as signal processing for mobile handsets. This work was conducted as a proof of concept, driven by the desire to demonstrate that such receivers can be realized in practice with current software / hardware capabilities.

The considered turbo-equalizer

The turbo-equalizer is shown in figure 2 and essentially consists of two main building blocks, a Soft-Input Soft-Output (SISO) equalizer and a SISO channel decoder, separated by a pair of interleaving / deinterleaving functions. Starting with the received signal, the SISO equalizer delivers soft decisions about the transmitted coded bits. A soft decision may be viewed as a real (or quantized) number whose sign gives the hard decision about the bit, and whose magnitude measures the reliability of the decision -a high magnitude meaning a high probability of correct decision. These soft decisions are deinterleaved and sent to the SISO decoder input. On the basis of this information, the decoder then delivers hard decisions on the information message, as well as updated soft decisions on the coded bits. The latter are then interleaved and fed back to the equalizer where they are exploited as a priori information for a new equalization attempt. Iterating the process a few times usually yields remarkable performance gains.

The SISO equalizer considered in this paper is called an MMSE Interference Canceller -Linear Equalizer (MMSE IC-LE). It generalizes the conventional MMSE linear equalizer by exploiting the reliability of a priori information available from the decoder to adapt the equalization strategy accordingly. Specifically, the IC-LE reduces to an MMSE linear equalizer in the absence of particular prior information about the coded bits. In contrast, it switches towards an ideal interference canceller when supplied with perfect a priori information. The latter structure theoretically eliminates all ISI without noise enhancement. The MMSE IC-LE comprises three processing functions, as shown in figure 3. The soft mapper first generates soft estimates about the transmitted symbols from the soft decisions delivered by the decoder. These estimates then enter an interference cancellation structure, together with the received distorted signal samples. The interference canceller is made up of two transversal finite impulse response (FIR) filters whose outputs are subtracted to yield the equalized signal. Finally, the SISO demapper produces updated soft decisions about the coded bits from the equalized samples available at the canceller output. The MMSE IC-LE maintains a reasonable complexity that grows essentially linearly with the dimension of the signal set and the number of interfering symbols. Hence, this SISO equalizer appears as an attractive candidate for single-carrier broadband wireless transmissions in severe multipath environments and, furthermore, seems suitable for a practical implementation. A full description of the MMSE IC-LE is available in [START_REF] Bidan | Implementation of a Low-Complexity MMSE Turbo-Equalizer on the TMS320VC5509[END_REF].

Figure 3: The MMSE Interference Canceller -Linear Equalizer (IC-LE)

The demonstration platform

The demonstration platform is composed of a host PC communicating with a target DSP evaluation module, as depicted in figure 4. The host PC runs a monitoring application which is responsible for the tasks of configuring the transmission link and the DSP board, generating test data at the channel output, sending the resulting signal to the DSP that implements the turbo-equalizer, retrieving the processed data and updating the link metrology (bit-error rate and signal constellation monitoring). The DSP board is a stand-alone evaluation card from Spectrum Digital, Inc. It features in particular a Texas Instruments TMS320VC5509 DSP operating at 120 MHz (240 MIPS), 128 Kwords of on-chip memory, and 4 Mwords of on-board DRAM memory. Communication between the DSP board and the host PC relies on Texas Instruments Real-Time Data eXchange (RTDX) technology. RTDX allows non intrusive data transfers between host and target, with data rates typically ranging from 30 to 50 Kbit/s, the latest improvement (High-Speed RTDX) offering up to 2 Mbit/s.

Figure 4: Overview of the demonstration platform

Receiver implementation

The turbo-equalizer has been designed to operate with signal to noise ratio values in the 0…20 dB range, over channels with delay spreads spanning at most 16 symbol periods. Perfect knowledge of the channel impulse response and noise variance was assumed. We have chosen to implement the turbo-equalizer using the C language in order to speed up the development process and favor code portability. However, the equalizer implementation takes advantage of the assembly hand-optimized functions provided by Texas Instruments Digital Signal Processing Library (DSPLIB) whenever possible, so as to remain compatible with real-time constraints. Data quantization was carefully optimized at each stage of the receiver in order to maintain the highest possible precision while avoiding underflows or overflows resulting from the use of 16-bit fixed point arithmetic. Preliminary simulations were performed with a floatingpoint C model of the receiver in order to find the proper number of bits required to accurately represent the quantities involved in the iterative process. Additional details about the implementation of the SISO equalizer and decoder can be found in [START_REF] Bidan | Implementation of a Low-Complexity MMSE Turbo-Equalizer on the TMS320VC5509[END_REF].

Experimental performance

The performance of the aforementioned receiver was evaluated in the context of a simple transmission scenario relying on a rate-½ 4-states convolutional encoder followed by a precomputed pseudo-random interleaving function and a Quadrature Phase Shift Keying (QPSK) modulator. Several channel models were investigated, including the class of quasi-static channels whose impulse response varies between successive transmitted data bursts.

Our measurements showed that the DSP receiver is able to operate with a maximum rate of 207 Kbit/s per iteration, or equivalently, 41 Kbit/s for 5 iterations. Additional studies demonstrated that the SISO equalizer and decoder account for 53% and 43% of the running time per iteration respectively. We ought to mention that the latter function may benefit from assembly language optimizations by taking advantage of the dedicated Add-Compare-Select instructions provided by the C55x DSP family. The resulting implementation has a code size of 3747 words (1 word accounting for In order to evaluate the performance loss caused by data quantization, comparative simulations were conducted both with the DSP demonstration platform and with an ideal (unquantized) floating-point C implementation of the turbo-equalizer. Bit-error rate measurements showed that our fixed-point DSP turbo-equalizer exhibits virtually no performance degradation in comparison with the floating-point receiver. These results were further confirmed by additional simulations over other channel models.

Finally, figure 5 graphically depicts the performance improvement offered by the turbo-equalization process during the iterations. The image Lenna was transmitted over a severe-ISI channel at a signal-to-noise ratio of 9 dB. It is worth noting that a conventional receiver implementing one-time equalization and decoding (iteration #1) only achieves a moderate bit-error rate of 1.1 10 -1 . In contrast, the image is decoded error-free at the fifth iteration with our DSP prototype.

Figure 5: Illustration of the performance improvement offered by turbo-equalization

Perspectives

This work has demonstrated the possibility of implementing advanced receiver structures in practice, such as low-complexity turbo-equalizers, on mobile terminals. Future work will include rewriting critical code sections in optimized assembly language and adding support for higher-order signal sets, such as Quadrature Amplitude Modulation (QAM). This project also constitutes the first step towards the realization of an FPGA prototype able to operate at data rates compatible with the requirements of broadband wireless transmissions, i.e. several Mbit/s. A flexible solution in this context could involve realizing the computation of the equalizer's coefficients on a general purpose DSP core, and then performing the costly filtering operations directly in hardware. The DSP core may then include other modem functions as well.

Acknowledgments

This work was supported by France Telecom R&D under research grant CRE 011B032, and by the Texas Instruments ELITE University Program.


Thèse en architecture Estelle MORLE, Sous la direction de M. François Fleury, Professeur HDR ENSAL Laboratoire EVS -LAURE (ED 483) UMR 5600 Environnement Ville Société En tant qu'objet artistique, technique et social, l'architecture est par définition au croisement de plusieurs champs disciplinaires dépassant les seules compétences de l'architecte et l'amenant à collaborer avec d'autres spécialités. L'exercice du projet architectural réside dans la synthèse réussie des différentes dimensions qui le composent. Cette nécessaire synthèse dont l'architecte est un garant, est aujourd'hui rendue complexe par les transitions rapides dans les domaines de l'écologie, du social, de l'économie et par l'élévation des exigences, notamment normatives. Ce contexte global de mutation amène les architectes à innover en ouvrant leurs pratiques à de nouveaux champs d'action, notamment au moyen de collaborations interdisciplinaires.

Bien qu'historiquement centrée sur l'individu, la culture française du métier d'architecte laisse place aujourd'hui à de nouvelles pratiques plus coopératives. Dans sa dernière étude des données démographiques et économiques de la profession1 , l'ordre des architectes constate l'émergence des pratiques en association depuis une dizaine d'années, concernant en particulier les jeunes architectes. Ces changements récents dans le milieu professionnel nous obligent à repenser les pratiques d'enseignement principalement centrées sur la compétition, ainsi que les objectifs d'apprentissage.

Ce projet doctoral de recherche en architecture interroge les processus coopératifs et leur articulation avec les mécanismes cognitifs à l'oeuvre lorsqu'ils sont mobilisés dans un projet de recherche-développement d'innovation en architecture. Il interroge la compétence de l'architecte dans l'exercice de synthèse et ses moyens propres pour l'implémenter. Nous nous intéresserons en particulier aux moyens humains (relations interpersonnelles, processus coopératifs et collaboratifs) mis en oeuvre par les architectes dans la perspective de mobilisation positive des autres acteurs qui portent et spécifient les différentes contraintes qui composent un projet, de par leurs connaissances ou leur pouvoir.

Ce travail s'appuie principalement sur l'étude d'un enseignement expérimental mené à l'Ecole Nationale Supérieure d'Architecture de Lyon initié en 2015 et prolongé jusqu'en 2018. Les thématiques abordées concernent la conception de dispositifs architecturaux innovants performants pour l'environnement et intégrant les nouveaux modes de vie des utilisateurs. La situation pédagogique permet l'émergence de plusieurs projets de recherche-développement issus de contextes réels et représentatifs des caractères les plus significatifs des jeux d'acteurs professionnels.

Le matériau principal de l'étude est issu de l'observation des processus à l'oeuvre lors de la conception coopérative des projets d'innovation par les étudiants au sein d'équipes pluridisciplinaires, et au-delà jusqu'à l'exploitation commerciale. Certaines inventions générées dans ce cadre sont poussées jusqu'au dépôt de brevet et la construction de projets démonstrateurs.

L'observation se situe à deux niveaux :

• Observation externe des processus coopératifs au sein des équipes d'élèves architectes via des outils proposés pour les accompagner à concevoir et travailler en équipe. Ces outils favorisent les processus de solidarité par l'autorégulation vis à vis du processus de production du projet.

• Observation participante des processus collaboratifs au sein des équipes pluridisciplinaires (étudiants, encadrants, chercheurs, partenaires professionnels, industriels et institutionnels) via l'analyse des méthodes, outils et processus développés par les différents acteurs au gré de l'avancement du projet jusqu'au terme du développement. Le 'terme' étant entendu comme l'objectif fixé par le projet de mener un ou plusieurs projets jusqu'à la réalisation de bâtiments démonstrateurs des innovations.

En

2012, 36,9% des architectes exerçaient leur activité en tant qu'associé contre 19,7% en 2000. Conseil National de l'ordre des architectes et IFOP, Archigraphie, Évolution des proportions d'architectes par type d'activité, 2000-2012 p 32, édité en 2014


Aurelien De Jode

Romain David

Anne Haguenauer

Abigail E Cahill

Zinovia Erga

Dorian Guillemain

Stéphane Sartoretto

Caroline Rocher

Line Marjorie Selva

Le Gall

Aurélien De Jode

Line Le Gall

Jean-Pierre Féral

Anne Chenuil

Spatial and ecological differentiation among cryptic species of the red algae Lithophyllum stictiforme/L. cabiochiae, main bioconstructors of coralligenous habitats

Keywords:

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

Introduction

Ecosystem engineers are organisms that alter their abiotic environment in such a way that they create or modify habitats, thereby having large effects on the associated species community [START_REF] Jones | Organisms as Ecosystem Engineers[END_REF][START_REF] Crain | Ecosystem engineering across environmental gradients: implications for conservation and management[END_REF]. Thus, phenotypic variation among ecosystem engineering organisms potentially have important consequences on the species community and on the ecosystem [START_REF] Whitham | Community and ecosystem genetics: a consequence of the extended phenotype[END_REF]. The phenotypic variation can arise at the intra specific level by plasticity or genetic differentiation, as well as interspecifically when different engineering species have different ecological traits [START_REF] Badano | Impacts of ecosystem engineers on community attributes: effects of cushion plants at different elevations of the Chilean Andes[END_REF][START_REF] Lamit | Hybridization among foundation tree species influences the structure of associated understory plant communities[END_REF]. In the marine realm, animal organisms acting as ecosystem engineers promote biodiversity of the associated communities [START_REF] Romero | Ecosystem engineering effects on species diversity across ecosystems: a meta-analysis: Ecosystem engineering effects across ecosystems[END_REF]. Algal T Molecular Phylogenetics and Evolution (2019) 137: 104-113 doi: 10.1016/j.ympev.2019.04.005 engineer species also have tremendous impacts on marine biodiversity. Within seascapes, kelp forests are the most conspicuous three-dimensional habitats hosting a high diversity of species [START_REF] Teagle | The role of kelp species as biogenic habitat formers in coastal marine ecosystems[END_REF]. Crustose Coralline Algae (hereafter CCA) are also major engineering organisms and contribute to the three-dimensional structure of several habitats such as coral reefs, maërl beds and coralligenous habitats.

In the Mediterranean Sea, coralligenous habitats are emblematic calcareous biogenic constructions built-up in dim light conditions mainly by calcareous algae (Corallinacea and Peyssonneliacea) and reinforced by calcareous invertebrates (e.g. bryozoans, serpulid polychaetes, scleractinians) [START_REF] Ballesteros | Mediterranean coralligenous assemblages: a synthesis of present knowledge[END_REF]. The resulting framework is complex and harbors various micro-habitats that shelter at least 1600 species [START_REF] Ballesteros | Mediterranean coralligenous assemblages: a synthesis of present knowledge[END_REF], making coralligenous habitats an important biodiversity hot-spot in the Mediterranean Sea [START_REF] Boudouresque | Marine biodiversity in the mediterranean: status of spicies, populations and communities[END_REF]. These habitats provide various ecosystem services (e.g. food provisioning, recreational diving, research material) [START_REF] Paoli | Ecosystem Functions and Services of the Marine Animal Forests[END_REF]Thierry de Ville 'Avray et al., 2019), yet they are threatened by global ocean warming and acidification [START_REF] Martin | Response of Mediterranean coralline algae to ocean acidification and elevated temperature[END_REF][START_REF] Lombardi | Skeletal alterations and polymorphism in a Mediterranean bryozoan at natural CO2 vents[END_REF][START_REF] Martin | One-year experiment on the physiological response of the Mediterranean crustose coralline alga, Lithophyllum cabiochae, to elevated pCO2 and temperature[END_REF][START_REF] Linares | Persistent natural acidification drives major distribution shifts in marine benthic ecosystems[END_REF][START_REF] Rodríguez-Prieto | Light and temperature requirements for survival, growth and reproduction of the crustose coralline Lithophyllum stictaeforme from the Mediterranean Sea[END_REF] and local human activities (e.g. fishing, anchoring or sewage outfalls) [START_REF] Hong | Etude faunistique d'un fond de concrétionnement de type coralligène soumis à un gradient de pollution en Méditerrannée nord-occidentale (Golf de Fos)[END_REF][START_REF] Ballesteros | Mediterranean coralligenous assemblages: a synthesis of present knowledge[END_REF][START_REF] Balata | Variability of Mediterranean coralligenous assemblages subject to local variation in sediment deposition[END_REF][START_REF] Balata | Increase of sedimentation in a subtidal system: effects on the structure and diversity of macroalgal assemblages[END_REF]. The lack of knowledge regarding the biodiversity of these habitats impedes our understanding of their ecological functioning and our capacity to protect them efficiently (SPA/RAC, 2017).

In coralligenous habitats, CCA are considered to be the major engineering group [START_REF] Laborel | Le concretionnement algal "coralligène" et son importance géomorphologique en Méditerranée[END_REF][START_REF] Laubier | Le coralligène des Albères : monographie biocénotique[END_REF][START_REF] Sartoretto | Age of settlement and accumulation rate of submarine "coralligène"(-10 to-60 m) of the northwestern Mediterranean Sea; relation to Holocene rise in sea level[END_REF]; however, the phylogenetic affinities of these CCA among other Corallinales has not been tested yet with molecular systematic tools even though these tools have strongly modified the perception of coralline diversity [START_REF] Bittner | Evolutionary history of the Corallinales (Corallinophycidae, Rhodophyta) inferred from nuclear, plastidial and mitochondrial genomes[END_REF][START_REF] Pardo | A multilocus species delimitation reveals a striking number of species of coralline algae forming maerl in the OSPAR maritime area[END_REF][START_REF] Peña | An integrative systematic approach to species diversity and distribution in the genus Mesophyllum (Corallinales, Rhodophyta) in Atlantic and Mediterranean Europe[END_REF][START_REF] Rösler | Phylogenetic relationships of corallinaceae (Corallinales, Rhodophyta): taxonomic implications for reef-building corallines[END_REF]. In the genus Lithophyllum, L. stictiforme (Areschoug) [START_REF] Hauck | Beitrilge zur Kenntniss der adriatischen Algen[END_REF] and L. cabiochiae (Boudouresque & Verlaque) [START_REF] Athanasiadis | The taxonomic status of Lithophyllum stìctaeforme (Rhodophyta, Corallinales) and its generic position in light of phylogenetic considerations[END_REF] are considered the main coralligenous builders below 20 m depth [START_REF] Sartoretto | Age of settlement and accumulation rate of submarine "coralligène"(-10 to-60 m) of the northwestern Mediterranean Sea; relation to Holocene rise in sea level[END_REF]. However, identification of these two nominal species based on macro-morphological character-istics or anatomical structures is uncertain. Moreover, recent studies using molecular systematic tools [START_REF] Rindi | Evolutionary history and diversity of Mediterranean coralline algae: how much do we know? Core Team, R[END_REF][START_REF] Pezzolesi | Mediterranean Lithophyllum stictiforme (Corallinales, Rhodophyta) is a genetically diverse species complex: implications for species circumscription, biogeography and conservation of coralligenous habitats[END_REF] have revealed the presence of cryptic diversity but did not sup-port distinction between these two species.

Ignoring the presence of cryptic species within a nominal species may have important consequences for biodiversity management. In particular, when cryptic species are ecologically differentiated, environmental changes may result in higher risks of extinction (local or global) than expected for a single generalist species (Chenuil et al., in press). Furthermore, recent studies showed that "L. stictiforme" survival and reproduction were affected by irradiance levels and temperature [START_REF] Rodríguez-Prieto | Light and temperature requirements for survival, growth and reproduction of the crustose coralline Lithophyllum stictaeforme from the Mediterranean Sea[END_REF] and that "L. cabiochiae" photosynthesis was reduced under elevated pCO 2 [START_REF] Martin | One-year experiment on the physiological response of the Mediterranean crustose coralline alga, Lithophyllum cabiochae, to elevated pCO2 and temperature[END_REF]. This highlights the need for studies of biodiversity at both inter-and intraspecific levels to evaluate the potential of adaptation to global change of these ecosystem engineering species.

In this study, we combined barcoding and exon capture sequencing to reveal cryptic species among 438 individuals initially collected as L. cabiochiae/stictiforme found in sympatry along the French Mediterranean coast, providing the opportunity to study the ecological determinants of their co-distribution. We used a fine scale, ecologically contextualized design in order to distinguish spatial effects (resulting from migration and connectivity) from ecological effects (fitness dif-ferences among cryptic species in distinct environments). Light is the most important environmental factor shaping coralligenous commu-nities [START_REF] Ballesteros | Mediterranean coralligenous assemblages: a synthesis of present knowledge[END_REF], thus we recorded environmental variables affecting the irradiance levels received by the community on each site. We analyzed community composition within the species complex (i.e. the relative abundances of the distinct cryptic species) in relation to ecological conditions (location, depth, orientation, slope) to determine if the different species were found in different niches. Population genetic analyses were then carried out in the most abundant of the cryptic species to determine the connectivity matrix among studied locations in order to disentangle pure spatial effects from environmental effects of depth.

Materials and methods

Field sampling and DNA extraction

Samples were collected by scuba diving in 13 different localities along the continental French Mediterranean coast and in Corsica (Figs. 2 & 3,Supplementary Material I). In the Marseille and Toulon area, horizontal transect lines were divided into 5 m segments. For each segment, up to 4 fragments of Lithophyllum spp. of about 3 cm large were collected. To avoid sampling clones of the same specimen, we left a minimum of 1 m between collected specimens. An average of 16 samples was collected at each sampling site. Moreover, 3 physical parameters were recorded in situ: slope, orientation, and rugosity. Slope was divided into 4 levels: (i) "Flat", when the angle formed by the substrate with the horizontal line was between 0° and 18.45°, (ii) "In-clined", for angles between 18.45° and 71.69°, (iii) "Vertical", for angles between 71.69° and 90° and (iv) overhanging, when there is an over-hang at least as large as a person above the observer and covers most of the segment. Orientation was measured with a compass handled by the diver and directed perpendicularly to the substrate wall (in the hor-izontal plane; it could not be defined for horizontal slopes). We con-sidered 8 modalities: North (N), South (S), East (E), West (W) and the four intermediate orientations (Northeast (NE), Northwest (NW), Southeast (SE), Southwest (SW)). Note that a North orientation in our dataset corresponds to a South exposition of the substrate. Rugosity characterizes the size of crevices, holes and faults observed in the segment and was characterized as follows: (i) "Tiny", when holes were smaller than a fist (about 10 cm wide); (ii) "Small", when holes were larger than a fist but smaller than a head; (iii) "Medium" (M): holes and crevices that were approximately head-sized (about 30 cm wide); (iv) "Large" (L): crevices, holes and faults can contain at least the upper body (about 1 m wide with air tanks). Most transects were carried out at a depth of 24-31 m (depth category D1), or 37-46 m (depth category D2). In Banyuls-sur-mer, Villefranche-sur-mer and Corsica transects were not segmented and all individuals were sampled at the same depth category. All CCA were dried, and preserved in silica gel at room temperature in a dark place or in ethanol 96% at 4 °C until DNA ex-traction. A piece of algal tissue was excised and cleaned of epiphytes by scraping the surface with a razor blade. The excised sample was dis-rupted using a TissueLyser II system (Qiagen) with a 3 mm stainless steel bead. DNA was extracted using Chelex 100 chelating resin [START_REF] Walsh | Chelex 100 as a medium for simple extraction of DNA for PCR-based typing from forensic material[END_REF]. Around 20 mg of tissue along with 500 μL of Chelex 10%and 3 μL of Proteinase K (20 mg/mL) were incubated at 60 °C for 90 min. Then sample was heated at 100 °C for about 10 min to deacti-vate the Proteinase K.

Sanger sequencing

Three independent molecular markers were used to identify the species of Lithophyllum: the plastid marker psbA, (primers psbA-F and psbA-R2, [START_REF] Yoon | A single origin of the peridinin-and fucoxanthin-containing plastids in dinoflagellates through tertiary endosymbiosis[END_REF], a fragment of the nuclear 28S (or large subunit) rDNA marker (primers T04 and T15, Harper & Saunders, 2001) and the mitochondrial marker COI (primers GazF1 and GazR1, [START_REF] Saunders | Applying DNA barcoding to red macroalgae: a preliminary appraisal holds promise for future applications[END_REF]. PCR reaction mixes were the same for the three markers, and PCR programs were identical for psbA and 28S (Supplementary Material II). PCR products were verified by electrophoresis migration on 1.5% agarose gel TBEx1 and then sent to Eurofins Genomics for Sanger sequencing using primers Gaz-R1, psbA-F and T04. Fragment sizes were approximately 700 bp for COI and 1000 bp for psbA and 28S. Sequences were checked and aligned using BioEdit software [START_REF] Hall | BioEdit: a user-friendly biological sequence alignment editor and analysis program for Windows 95/98/NT[END_REF]) before further analyses.

Miseq sequencing

In a second step, to determine the lineages of additional individuals with lower sequencing costs, we designed shorter fragments within the psbA and 28S markers to allow high throughput sequencing (Illumina, Miseq paired end 2 × 250 bp) (Supplementary Material II). PCR cycles and reactions mixes were the same for both markers (Supplementary Material II). Amplicons were sequenced, and Miseq Reads were processed as described in [START_REF] Cahill | A multispecies approach reveals hot spots and cold spots of diversity and connectivity in invertebrate species with contrasting dispersal modes[END_REF] with a few exceptions. For the plastid marker, psbA, sorting was done as in [START_REF] Cahill | A multispecies approach reveals hot spots and cold spots of diversity and connectivity in invertebrate species with contrasting dispersal modes[END_REF] for mitochondrial loci with slight modifications: sequences were retained if the total number of reads was ≥20 (i.e. 20× coverage) and the count ratio ≤0.14 (i.e. the most abundant read was at least 7 times more abundant than the second most abundant read). For the 28S nuclear locus, the total number of reads was sufficient for all individuals (at least 66 reads for each). For both markers, forward and reverse reads did not overlap and were attached end to end.

Haplotype networks

For each marker, sequences from Sanger sequencing and Miseq sequencing were aligned visually with Bioedit [START_REF] Hall | BioEdit: a user-friendly biological sequence alignment editor and analysis program for Windows 95/98/NT[END_REF]. Sequence positions found in both Sanger and Miseq sequencing were kept to build an alignment with all sequences of the same size. For each marker, we built haplotype networks from the longer sequence alignment obtained by Sanger sequencing and also, for psbA and 28S, from the shorter alignments including Miseq sequences. Haplotype networks were generated using the median-joining algorithm of the Network software, v.5.0.0.1 [START_REF] Bandelt | Median-joining networks for inferring intraspecific phylogenies[END_REF]. The average proportion of differences and average Kimura distance (K2P, [START_REF] Kimura | A simple method for estimating evolutionary rates of base substitutions through comparative studies of nucleotide sequences[END_REF] between haplogroups were computed from the long alignments (i.e. using MEGA v.4 [START_REF] Tamura | MEGA4: Molecular Evolutionary Genetics Analysis (MEGA) software version 4.0[END_REF]).

Transcriptomics

Individuals were collected in 2015 at the CAS, MEJ, LPD, COU localities by scuba diving, and preserved in seawater during transportation to the lab. Around 2 cm 2 of each individual was immediately cleaned of epiphytes with a razor blade, placed in 1 ml QIAzol lysis reagent (Qiagen) and disrupted using TissueLyserII instrument (Qiagen). The rest was preserved in 96% ethanol at 4 °C and used to determine the haplogroup of each individual following the protocol for Sanger sequencing described above in this paper.

Total RNA isolation was performed according to the manufacturer's instructions, except for overnight precipitation at -20 °C (1/10 vol sodium acetate 3 M pH 5.2, 2 volumes ethanol). Contaminants were eliminated by further cleaning using an RNeasy plus mini kit (Qiagen). RNA integrity was assessed using Agilent 2100 Bioanalyzer system, and concentration and purity using Nanodrop instrument (Thermofisher). Residual DNA was digested using TurboDNAse (Ambion) following the manufacturer's instructions.

RNA-Seq libraries were generated using the TruSeq Stranded mRNA Illumina kit according to the manufacturer's protocol. During this preparation, libraries were individually tagged to allow their pooling before sequencing. The size distributions of libraries' RNA fragments were controlled with a Fragment Analyzer™ Automated CE System from Advanced Analytical Technologies, Inc. (AATI).

The eight libraries were quantified by qPCR following the manufacturer's protocol. Libraries were pooled before sequencing on one lane on the Illumina HiSeq3000 (Illumina Inc., San Diego, CA) as paired-end reads of length 150 bp. Library preparation and sequencing were performed at the Genotoul platform (http://get.genotoul.fr/). Three samples were highly contaminated with 30%, 10% and 7% of their reads mapping against the E. coli genome. Those reads were removed before the assembly step. Assembly of each library was performed using the RunDrap Pipeline with default parameters as described by [START_REF] Cabau | Compacting and correcting Trinity and Oases RNA-Seq de novo assemblies[END_REF].

To build a reference transcriptome, one meta-assembly of the two individuals of the most abundant species (the C1 species) transcriptome was conducted, using the Run Meta Pipeline described in [START_REF] Cabau | Compacting and correcting Trinity and Oases RNA-Seq de novo assemblies[END_REF].

Sequences from each assembly and meta-assembly were blasted using the program blastn version 2.2.26 [START_REF] Altschul | Basic local alignment search tool[END_REF][START_REF] Camacho | BLAST+: architecture and applications[END_REF] contigs with a hit (e-value threshold 0.001) against any of them were removed from further analyses. These species are commonly used in genomic studies and are potential sources of contamination on the genomic platform. Also, their genomes are available allowing to compare our sequences with these potential contaminants.

The meta-assembly of the two individuals of the C1 haplogroup was used as a reference in the following steps and contig names were modified using a custom script. For all individuals, reverse reads were renamed and pooled with forward reads in one file. All reads were mapped on the reference with Bwa mem [START_REF] Li | Aligning sequence reads, clone sequences and assembly contigs with BWA-MEM[END_REF] with default parameters. SNP calling was conducted using the Reads2snp v2.0 script from PopPhyl project [START_REF] Tsagkogeorga | The population genomics of a fast evolver: high levels of diversity, functional constraint, and molecular adaptation in the Tunicate Ciona intestinalis[END_REF][START_REF] Gayral | Reference-free population genomics from next-generation transcriptome data and the vertebrate-invertebrate gap[END_REF]. Open reading frames (ORFs) were detected using Transdecoder 3.0.0 [START_REF] Haas | Transdecoder v[END_REF] and the ORF output file was converted to get.ORF format using a custom script.

Biotinylated RNA probes were designed by and ordered from MYcroarray (Ann Arbor, MI, USA; now Arbor Biosciences). Based on the ORF sequences, 18757 candidate sequences (total size 18.3 Mb) were soft-masked for simple repeats and low-complexity DNA using RepeatMasker (Smit et al., 2013). Any strings of Ns between 1 and 10 bp were replaced with Ts to facilitate probe design; larger strings of Ns were left alone. 120 bp probes with 2× flexible tiling density were designed for all sequences, and dG, GC%, and % soft-masked were ta-bulated. Only probes with (i) dG greater than -9, (ii) 30-50% GC, (iii) 0 softmasked bases were kept and divided in two subsets: the first one contained probes with 1 to 7 SNPs with the reference and the second one the probes with no SNP with the reference.

Among the first probe subset we randomly sampled one probe per ORF for a total of 14403 probes. For each randomly selected probe we extracted the closest and the furthest probe when possible. Finally, we took 2000 probes in the closest, 2000 in the furthest (from the first probe selected in the ORF) and 1617 in the non-polymorphic probes for a total of 20020 probes.

Exon-Capture genotyping

For capture sequencing, total genomic DNA was extracted according a protocol derived from [START_REF] Sambrook | Molecular cloning: a laboratory manual[END_REF], followed by one or two purifications using NucleoSpin® gDNA Clean-up (Macherey-Nagel) (see Supplementary Material III for a detailed protocol).

DNA was fragmented using The Bioruptor® Pico (diagenode) to obtain fragment size of around 250 pb. Dual-indexed NGS Libraries were made using NEBNext® Ultra™ DNA Library Prep Kit for Illumina® kit following the manufacturer's protocol. Two conditions of in-solution target enrichment were performed according to manufacturer's recommendations following the MYbaits v3 protocol (http://www. mycroarray.com/mybaits/manuals.html).

The first condition was 32 libraries in 30 µL reactional volume, repeated 3 times for a total of 128 enriched libraries, whereas the second condition was conducted in 15 µL reactional volume with 16 libraries. Post-capture, libraries were amplified following Mybaits protocol recommendations (Mix KAPA HiFi, PCR at 60 °C, 14 cycles), post PCR purification using Ampure XP, and 1.6 pM DNA was provided for sequencing on one MID flowcell of NextSeq Illumina System, Paired-end sequencing (2 × 150bp).

First, raw reads were split according to their sequencing lane using a custom python script and fastq files were converted to SAM files. We followed the GATK good practices [START_REF] Van Der Auwera | From FastQ data to high confidence variant calls: the Genome Analysis Toolkit best practices pipeline[END_REF] to call SNPs except for the BQSR and VQSR steps because of the lack of reference SNPs data sets. We used ORFs of the C1 haplogroup meta assembly as a reference in all the above steps and SNPs calling was restricted to an area starting 400 bp before the first base covered by the probe to 400 bp after the last base covered by the probe.

To study the inter haplogroup divergence the jointGenotyping step was conducted with all individuals from the Bay of Marseilles. To study the intra C1 haplogroup diversity the jointGenotyping step was conducted with all individuals from the C1 haplogroup. In both cases, obtained SNPs were filtered based on GATK recommended parameters (QD < 2.0, FS > 60.0, MQ < 40.0, MQRankSum < -12.5, ReadPosRankSum < -8.0), then SNPs with minor allele frequency lower than 0.01 were removed. For the inter haplogroup study, SNPs with more than 10% missing value were removed from the dataset. For the intra C1 haplogroup dataset, SNPs with more than 25% missing values or failing HWE in one or more of the 7 populations were re-moved using vcftools [START_REF] Danecek | The variant call format and VCFtools[END_REF], with a p-value threshold of 0.01. Finally, for both datasets one SNP per ORF was randomly ex-tracted using a custom python script and individuals with more than 20% missing genotypes were excluded from the dataset.

Population genomics analyses

First, a neighbor joining tree on multilocus genotypes was built with individuals of the inter clade dataset using the APE package [START_REF] Paradis | APE: analyses of phylogenetics and evolution in R language[END_REF] inR(R Core team, 2017). Individuals were colored according to their haplogroup determined by one of the three barcoding markers. Individuals with undetermined haplogroups were assigned to a species based on their positions in the tree, using the phytools [START_REF] Revell | Phytools: an R package for phylogenetic comparative biology (and other things)[END_REF] package in R (R Core team, 2017). Principal Component analyses (PCA) were conducted on individuals assigned to the C1 species using the adegenet R package [START_REF] Jombart | adegenet: a R package for the multivariate analysis of genetic markers[END_REF][START_REF] Jombart | adegenet 1.3-1: new tools for the analysis of genome-wide SNP data[END_REF]. Calculation of F statistics, diversity indices, and tests of genetic differentiation were carried out with the GENEPOP R package [START_REF] Rousset | genepop'007: a complete re-implementation of the genepop software for Windows and Linux[END_REF].

Clonality

To assess the importance of clonal reproduction in the C1 species we used the functions genet_dist and genet_dist_sim from the Rclone package [START_REF] Bailleul | RClone: a package to identify MultiLocus Clonal Lineages and handle clonal data sets in r[END_REF]. The genet_dist function was used to compute a matrix of pairwise number of alleles differences between our multilocus genotypes (MLG) in each population. The genet_dist_sim function allowed for simulation of a sexual reproduction event between pairs of unique MLGs (outcrossing) or pairs of MLGs (partial selfing) of all our populations and computed two matrices of pairwise genetic distances within the resulting population after 1000 sexual events (one generation each). The first matrix was obtained by simulating sexual reproduction including outcrossing and selfing and the second was obtained by simulating only outcrossing events (no selfing). The three distributions (empirical, simulated with selfing and simulated without selfing) were compared to assess if the distribution of empirical distances can be obtained by sexual reproduction alone. We performed the analysis on 2176 biallelic SNPs without missing values.

Community analyses

All the community statistical analyses were conducted using the PRIMER software version7 [START_REF] Clarke | Change in marine communities: an approach to statistical analysis and interpretation[END_REF][START_REF] Clarke | PRIMER v7: User Manual/Tutorial[END_REF]. Due to the different sampling procedure, the Banyuls-sur-mer, Villefranche-sur-mer and Corsica localities were not used in statistical analyses linking community composition to environmental factors (PERMANOVAs and PERMANCOVAs). However, all the localities were used in the nonmetric Multi-Dimensional Scaling (nMDS) and for the estimation of diversity indices. The final community matrix used for the Marseille area contained 187 rows, corresponding to each segment of marine substrate, and for each row, the number of individuals of each of the 7 species present in this area (corresponding to 7 columns). The final environmental matrix had the same row number and names as the final community matrix, and for each row, the level of each of the environmental variables (depth category, locality, orientation, slope, rugosity). Community data were standardized by the total number of individuals and square-root transformed before computing pairwise Bray-Curtis dissimilarity indices. To calculate diversity metrics for each locality, we summed the abundances of each segment (Table 1). The nMDS was produced using Bray-Curtis similarity indices on the table of abundances per locality.

Due to the lack of replication, the PERMANOVA designs only included 2 factors: locality as a random factor, one other environmental factor as a fixed factor and the interaction term between the two. The PERMANCOVAs designs included the locality factor and the depth (as a numeric variable) or the Photosynthetic Active Radiation (PAR) as covariable. The PAR was calculated for each depth by averaging the values obtained from the SOMLIT recorder in the Frioul locality between 2007 and 2017. Thus, PAR was not directly measured at each location but, according to its depth, each sampling segment was assigned an estimated PAR value. Since the effect of the 'location' factor was considered in the analysis using the PAR covariable, the variable PAR represents the effect that depth has on irradiance attenuation.

Results

Haplotype networks

Sanger (i.e. longer) sequence alignments were respectively 594 bp, 744 bp and 802 bp for the mitochondrial (COI), plastid (psbA) and the nuclear markers (28S rDNA), after primers and lower quality terminal regions were removed. Shorter alignments including Miseq sequences for the psbA and 28S markers were respectively 365 bp and 425 bp. (273 individuals were sequenced for both the 28S rDNA and psbA markers). The number of substitutions separating the distinct haplogroups varied (in long alignments) from 4 to 22 for the most conserved marker which is the 28S rDNA, from 14 to 48 for psbA and from 40 to 77 for COI, the most rapidly evolving marker (Supplementary Material IV). The minimum and maximum Kimura distances were respectively 0.003 (28S rDNA, C6-C7) and 0.105 (COI, C1-C6) (Supplementary Material IV). Since the haplogroups were congruent among markers and found in sympatry, their genetic isolation and their status of cryptic species was established (cf discussion) so in the following sections, they were considered as such.

Figures in Supplementary Material

Capture sequencing

For the inter species dataset, a total of 7068 SNPs were obtained for 122 individuals. Among these individuals, 69 were already classified in one of the 7 species using at least one of the three barcode markers. For all individuals from the Marseille area, species determination based on barcode marker or the multilocus genotype distances between individuals (in number of different alleles) gave the same results (Fig. 1). Among the 53 remaining individuals, 3 clustered together forming the C8 species, and the others were assigned to one of the 7 species according to their position on the neighbor joining tree. The mean Euclidean distances based on genotypes between individuals of the different species ranged from 52.76 between C7 and C8 to 115.42 between C2 and C5 (Supplementary Material VI). The C4 species had the highest intra species mean distances: 24.10. Three clusters were distinguished on the tree: C1, C2 to C4, and all the C5 to C8 species (Fig. 1).

Population genomics for the C1 species

For the individuals of the C1 species, a total of 4744 SNPs were obtained for 75 individuals. The expected heterozygosity by population ranged from 0.1090 in FTF_D1 to 0.1603 in RMO. Significant F IS values were found in 4 populations: FTF_D1, FTF_D2, CAS_D1, CAS_D2 ranging from -0.0096 in CAS_D2 to 0.1260 FTF_D1. The global F ST value was 0.0464 and F ST values between pairs of populations ranged from 0.0077 between CAS_D1 and CAS_D2 to 0.0911 between RMO and LPD. The genetic differentiation for the two pairs displaying contrasted depths was not significant. On the PCA plot (Fig. 4), the individuals were clustered according to their localities (but the PCA did not suggest clonality because all individuals were separated on at least one combination of axes). Individuals were spread in three different clusters from left to right on the first axis (5.71% of the total variability). The second axis represented 3.06% of the total variability and no clear cluster was formed along this axis. The third axis represented 2.67% of variability and separated LPD population from all the others (Fig. 4B). In clonality analyses, all multilocus genotypes (MLG) were clearly dis-tinct and empirical genetic distances distributions match with simu-lated genetic distance distributions obtained under the hypothesis of outcrossing in all populations (Supplementary Material VIII).

Cryptic species diversity and distribution

The species richness among localities ranged from 2 in the COU, CTF and PLN localities to 5 in the CIR and CAS localities. Simpson di-versity indices in localities ranged from 0.1498 at the FTF locality to 0.781 at the VPR locality (Table 1). Lithophyllum cryptic species com-munities were differentiated between localities at different spatial scales (Figs. 2, 3 & Table 2 &3). At large spatial scale, the BPT locality was very distant from all other localities (Fig. 2B) and was the only one where species C1 was absent and where species C5 was present. Then, the VPR locality was isolated from localities of the Marseille area on the nMDS (Fig. 2B) and harbored a high proportion of the C6 and C7 cryptic species as well as the highest species diversity (Table 1). The Corsica community was grouped with communities of the Marseille area (Fig. 2B). At small spatial scale (from the COU locality to the LPD lo-cality), species were not randomly distributed across localities (2 fac-tors PERMANOVA, p(perm) = 0.0001, Table 2 & Fig. 3): the C1 species was ubiquitous and the C2 species was missing in a single locality (COU). Species C5, C7 and C8 were only found in the CAS locality and the C6 species only in the RMO locality. The C4 species was mainly found at the Côte Bleue (COU, MEJ, CSC) with few exceptions (Fig. 3A). Based on the species relative abundances and the nMDS four groups of localities were discernible (Fig. 3): (i) the Côte Bleue (COU, CSC, MEJ) and LPD, (ii) Marseille (FTF, RMO), (iii) the PSO and CTF localities and (iv) the CAS locality was highly distant from all the others.

Cryptic species ecology

In the two-way PERMANOVAs, the random locality factor was always significant, but the fixed environmental factor was never significant (Table 2). However, the interaction between locality and sampling depth category had a significant effect on the Lithophyllum cryptic species community composition (PERMANOVA, p (perm) = 0.014). The community differed between the two depth ca-tegories in the RMO locality (PERMANOVA, p(mc) = 0.0439) and the CAS locality (PERMANOVA, p(perm) = 0.0067). In the RMO locality the C2 and C6 species were found at depth 28 m and the most abundant C1 species was found at all depths. In the CAS locality, the C5 species was only found in the D1 depth category, the C8 species was only found in the D2 depth category (Fig. 3A). In both PERMANCOVAs, the random locality factor and the numeric covariable (i.e. depth, in me-ters, and PAR) were significant (Table 3). Mitochondrial, plastid and nuclear markers, which belong to different genomes, gave consistent results to reveal distinct haplogroups. In case of asexual reproduction mitochondrial, plastid and nuclear genomes are linked [START_REF] Dudgeon | Asexuality and the cryptic species problem[END_REF] thus giving the same information. Inside the C1 species, clonality analyses revealed the absence of duplicated multilocus genotypes. Moreover, the distributions of genetic distances among multilocus genotypes match the distributions obtained with only sexual reproduction (Supplementary Material VIII) suggesting that there are no clones in our dataset. Therefore the consistency of the results obtained with the mitochondrial, plastid and nuclear markers is not likely due to presence of clonal lineages. Those haplogroups were highly divergent for the markers COI and 28S (above 10% of divergence for COI), a level of variation which is generally recognized as interspecific variation for red algae (e.g. [START_REF] Saunders | Applying DNA barcoding to red macroalgae: a preliminary appraisal holds promise for future applications[END_REF][START_REF] Gall | A nuclear phylogeny of the Florideophyceae (Rhodophyta) inferred from combined EF2, small subunit and large subunit ribosomal DNA: Establishing the new red algal subclass Corallinophycidae[END_REF] and more specifically for coralline algae (e.g. [START_REF] Pardo | Insights into species diversity of associated crustose coralline algae (Corallinophycidae, Rhodophyta) with Atlantic European maerl beds using DNA barcoding[END_REF]. In addition, the analyses based on thousands of SNPs confirmed that these seven haplogroups are genetically isolated and highly differentiated even when found in sympatry and even within a single 5 m segment. There is thus no doubt that these haplogroups are reproductively isolated. One may argue that strong inbreeding may create such a pattern (when outcrossing events are rare), and positive F IS values have been reported in other red algae such as C. crispus (Kruger-Hadfield et al., 2011& 2015) and may result from low dispersal capacities leading to inbreeding. Nevertheless, the relatively moderate intra populations F IS values in C1 (Table 4) rule out this hypothesis. We thus established that these haplogroups are separate biological species, i.e. cryptic species of the Lithophyllum stictiforme/cabiochiae complex.

Lithophyllum is the most species diverse genus among the Corallinales with 130 species currently recognized (Guiry & Guiry, 2018); however, the use of molecular systematics to clarify relationships among species of the genus Lithophyllum highlighted our lack of knowledge on the diversity of this genus [START_REF] Basso | The genus Lithophyllum in the north-western Indian Ocean, with description of L. yemenense sp. nov. , L. socotraense sp. nov. , L. subplicatum comb. et stat. nov. , and the resumed L. affine , L. kaiseri , and L. subreduncum (Rhodophyta, Corallinales)[END_REF][START_REF] Hernandez-Kantun | Sequencing type material resolves the identity and distribution of the generitype Lithophyllum incrustans, and related European species L. hibernicum and L. bathyporum (Corallinales, Rhodophyta)[END_REF][START_REF] Rodríguez-Prieto | Light and temperature requirements for survival, growth and reproduction of the crustose coralline Lithophyllum stictaeforme from the Mediterranean Sea[END_REF][START_REF] Peña | Assessment of coralline species diversity in the European coasts supported by sequencing of type material: the case study of Lithophyllum nitorum (Corallinales, Rhodophyta)[END_REF]. Previous studies (e.g. [START_REF] Bittner | Evolutionary history of the Corallinales (Corallinophycidae, Rhodophyta) inferred from nuclear, plastidial and mitochondrial genomes[END_REF][START_REF] Hernandez-Kantun | Sequencing type material resolves the identity and distribution of the generitype Lithophyllum incrustans, and related European species L. hibernicum and L. bathyporum (Corallinales, Rhodophyta)[END_REF][START_REF] Rösler | Phylogenetic relationships of corallinaceae (Corallinales, Rhodophyta): taxonomic implications for reef-building corallines[END_REF] already underlined the necessity of a detailed molecular study of the Lithophyllum genus to unravel potential cryptic diversity. Recently, [START_REF] Pezzolesi | Mediterranean Lithophyllum stictiforme (Corallinales, Rhodophyta) is a genetically diverse species complex: implications for species circumscription, biogeography and conservation of coralligenous habitats[END_REF] unravelled cryptic diversity in the L. stictiforme complex using three barcode markers. Their study showed the presence of at least 13 species at the Mediterranean scale. Our results underline the usefulness of molecular tools to delineate species in this genus, whereas determination of the species in situ or by observing classical macro morphological characters is seldom possible.

Community composition and genetic structure cannot wholly be explained by spatial distances and current patterns

At the global scale of this study, the high difference in composition between the Banyuls-sur-mer (westernmost) cryptic species community and all other communities (Fig. 2) is noteworthy. There are three nonexclusive explanations. (1) The scarcity of suitable habitats for these cryptic species (i.e. rocky substratum found in dim light condition) between the Banyuls-sur-mer (BPT) and the Couronne (COU) localities [START_REF] Martin | Coralligenous and maërl habitats: predictive modelling to identify their spatial distributions across the Mediterranean Sea[END_REF] may impede the stepwise colonization across these areas, even considering several generations, and the high geographic distance separating Banyuls-sur-mer from the other study sites may impede the colonization in a single generation of propagules (mainly spores in CCA). (2) The Rhône flow at the west of the COU locality and the presence of vortex structures in the Lion Gulf may constitute barriers to dispersal. ( 3) The different environmental conditions found in Banyuls-sur-mer may select for different cryptic species: salinity and water temperature are highly variable and turbidity is higher in Banyuls-sur-mer compared to any other sampling site (SOMLIT data: http://somlit.epoc.u-bordeaux1.fr/fr/). At the opposite Eastern end of the study, the Villefranche-sur-mer (VPR) community position on the nMDS could be explained both by its eastern geographical origin and by the fact that it was sampled at shallower depth than the other localities (between 15 and 20 m).

Finally, all other localities were clustered on the nMDS (Fig. 2B) in a group gathering the Marseille Area (except the CAS locality), the CIR and the LDM localities, despite the important geographic distances between them. All together this pattern suggests that geographical distance alone does not provide a sufficient explanation of the distribution of these eight cryptic species at the regional scale. Thus, their abundances may be influenced by complicated current patterns and/or by changing environmental factors across the different sampling sites.

At a closer scale around the bay of Marseille, we know the current patterns in more detail and we can benefit from comparative population genetics studies to investigate whether currents and distance can explain species composition (and genetic structure within species). Globally, the Lithophyllum stictiforme/L. cabiochiae display a good concordance between cryptic species community and genetic structures in the Marseille Area. The frequencies of the eight cryptic species were highly variable among localities within the Bay of Marseille but three clusters were distinguishable based on community similarities (Fig. 3): (i) the Côte Bleue (COU, CSC, MEJ) and LPD; (ii) Marseille (FTF & RMO), (iii) the PSO and CTF localities. The CAS locality community composition was highly distinct from all the others. The genetic diversity structure within cryptic species C1 presented similarities with the community structure pattern with the same 3 spatial clusters: the CAS population was highly differentiated from all the other populations (Fig. 4 & Supplementary Material VII), the LPD and COU populations on one hand, the FTF and RMO populations on the other hand clustered together on the PCA (Fig. 4A).

Homogenization of species (or allele) frequencies among localities requires both (i) migration of the viable propagules among localities and (ii) successful settlement and growth in new localities (depending among other things on the availability of suitable habitats).

The first condition is mainly determined by the propagules' ability to disperse and the hydrodynamics of water masses in the area [START_REF] Cowen | Larval dispersal and marine population connectivity[END_REF][START_REF] Weersing | Population genetics, larval dispersal, and connectivity in marine systems[END_REF]. In CCA, propagules have low dispersal capacities and settle closely to their source of emission [START_REF] Norton | Dispersal by macroalgae[END_REF][START_REF] Opazo | Vertical distribution of spores of blade-forming Sarcothalia crispata (Gigartinaceae) and crustose corallines (Corallinaceae) in the water column[END_REF] which can explain the differentiation among localities observed in this study at both the interspecific and the intraspecific levels. Comparing F ST value in this study (F ST global 0.0464) with those obtained by [START_REF] Cahill | A multispecies approach reveals hot spots and cold spots of diversity and connectivity in invertebrate species with contrasting dispersal modes[END_REF] using data from several invertebrate species sampled in the same geo-graphic area, the C1 species would correspond to the lecithotroph "larval type" species in terms of dispersal capacities. Both population genomics and cryptic species composition patterns showed a

Table 4

Genetic diversity (expected heterozygosity) and F IS of the C1 species calculated in each population and each locality (in yellow). Populations with a very low individual count (< 9) are colored in grey. *Significant results, ** highly significant results.

differentiation between the Côte Bleue, and the east part of the Bay of Marseille. This pattern has been identified in previous studies encompassing 9 animal taxa [START_REF] Cahill | A multispecies approach reveals hot spots and cold spots of diversity and connectivity in invertebrate species with contrasting dispersal modes[END_REF], and a brown alga [START_REF] Thibaut | Connectivity of populations of the Seaweed Cystoseira Amentacea within the bay of Marseille (Mediterranean Sea): genetic structure and hydrodynamic connections[END_REF] and can be attributed to the main currents in the Bay of Marseille that prevent connectivity between these two areas [START_REF] Pradal | Spatial heterogeneity of artificial reefs functioning according to wind-induced lagrangian circulation[END_REF] at least in sessile organisms with low dispersal abilities [START_REF] Cahill | A multispecies approach reveals hot spots and cold spots of diversity and connectivity in invertebrate species with contrasting dispersal modes[END_REF]. The CAS locality presents the highest level of L. stictiforme/cabiochiae cryptic species diversity (Table 1) and is also very distinct from the other localities (Fig. 3 B) in species composition. Moreover, within the C1 species, the CAS population is highly differentiated from the others (Fig. 4 & Supplementary Material VII). This sampling locality is east of the head of the "Cassidaigne" marine canyon and presents very different characteristics from other sampled sites, both in terms of currents and biogeochemical parameters. In particular, this locality is not subjected to upwellings as strong as in the area west of the canyon (such as the RMO locality), is more influenced by the North current and often experiences deep eastward currents [START_REF] Albérola | Circulation in the French mediterranean coastal zone near Marseilles: the influence of wind and the Northern Current[END_REF][START_REF] Pairaud | Hydrology and circulation in a coastal area off Marseille: validation of a nested 3D model with observations[END_REF].

Cryptic species community composition is influenced by environmental factors

Indeed, our combined results in community composition and population genomics established that environmental factors are influential in the composition in cryptic species. The cryptic species community in the RMO and CAS localities were different among depth categories. This was especially true in the CAS locality, where the C5 species was totally absent at deepest sites (the D2 depth category) and replaced by the C8 species (Fig. 2). At a higher taxonomic level, [START_REF] Sartoretto | Age of settlement and accumulation rate of submarine "coralligène"(-10 to-60 m) of the northwestern Mediterranean Sea; relation to Holocene rise in sea level[END_REF] also observed a shift in the frequencies of the main algal builders in coralligenous habitats in the Marseille area across depths: L. cabiochiae was reported as the dominant one in deep waters whereas Mesophyllum alternans was more restricted to shallower waters. Importantly, no significant genetic differentiation was found for the C1 species between the populations from the D1 and D2 depth categories in the CAS locality (Fig. 4 & Supplementary Material VII), suggesting that gene flow between the two depths is not restricted and propagules can travel between the two depth categories. Thus, the differentiation of the communities between depths (found in the PERMANOVA) should be explained by environmental factors varying across depths such as light or temperature. Light is known to have an influence on cor-alligenous assemblages [START_REF] Ballesteros | Mediterranean coralligenous assemblages: a synthesis of present knowledge[END_REF], because CCA only develop at specific values of irradiance [START_REF] Ballesteros | Els vegetals i la zonació litoral: espècies, comunitats i factors que influeixen en la seva distribució[END_REF]. Our study shows an influence of the PAR on the community composition of the cryptic species. It could therefore be interesting to experimentally compare physiological parameters of the distinct cryptic species such as photo-synthesis, growth rate, and carbonate precipitation under different level of irradiances. Differences in temperature (particularly in temperature variability) may also have a role but our depth categories (30 m and 40-45 m) are not very contrasted in relation to temperature, both being below the summer thermocline threshold (around 16-20 m) [START_REF] Harmelin | Environnement thermique du benthos côtier de l'île de Port-Cros (parc national, France, Méditerranée nord-occidentale) et implications biogéographiques[END_REF][START_REF] Haguenauer | Adaptive abilities of the Mediterranean red coral Corallium rubrum in a heterogeneous and changing environment: from population to functional genetics[END_REF]. Finally, experimental studies showed that the interaction between light and temperature impacted survival in L. stictiforme (Rodríguez-Prieto, 2016).

Ecological consequences and conservation implications of the cryptic diversity for coralligenous habitats

Different engineering species harboring different ecological traits [START_REF] Badano | Impacts of ecosystem engineers on community attributes: effects of cushion plants at different elevations of the Chilean Andes[END_REF][START_REF] Lamit | Hybridization among foundation tree species influences the structure of associated understory plant communities[END_REF] or phenotypic variation among individuals of the same species [START_REF] Whitham | Community and ecosystem genetics: a consequence of the extended phenotype[END_REF] influence the diversity and structure of the associated communities. Since the cryptic species of the L. stictiforme/cabiochiae complex are, together with other CCA of the genus Mesophyllum, the main engineers of the coralligenous habitats, the distribution of these cryptic engineering species as well as their intraspecific genetic structure potentially have important consequences on the composition of the benthic assemblages found on coralligenous habitats. CCA are also known to influence the settlement of other invertebrates by producing chemical cues inducing the recruitment of larvae in several habitats (e.g. coral reefs and vermetid reefs) [START_REF] Diaz-Pulido | The impact of benthic algae on the settlement of a reef-building coral[END_REF][START_REF] Spotorno-Oliveira | Coralline algae enhance the settlement of the vermetid gastropod Dendropoma irregulare (d'Orbigny, 1842) in the southwestern Atlantic[END_REF][START_REF] Quéré | Coralline algae disease reduces survival and settlement success of coral planulae in laboratory experiments[END_REF][START_REF] Elmer | Coral larvae change their settlement preference for crustose coralline algae dependent on availability of bare space[END_REF]. To our knowledge, these kinds of interactions between L. stictiforme/cabiochiae and invertebrate larvae (e.g. Anthozoa) have not been studied in coralligenous habitats.

Coralligenous habitats are a major marine biodiversity hotspot of the Mediterranean Sea, yet their protection is still pending mainly because there is still a large gap of knowledge about biodiversity and ecological functioning of these habitats (SPA/RAC, 2017).

Engineer species are priority targets for conservation programs because their protection has a large impact in retaining community and ecosystems integrity and functions [START_REF] Crain | Ecosystem engineering across environmental gradients: implications for conservation and management[END_REF]. The high structure found both at the species and the genetic diversity levels make these cryptic species particularly vulnerable to local threats such as water pollution or mechanical degradation. Protecting coralligenous habitats (or just evaluating their vulnerability) requires taking into account the geographic distribution of the eight cryptic species along the French Mediterranean coast and at smaller spatial scales. Due to the high L. stictiforme/cabiochiae community composition differentiation between the biogeographic regions of Banyuls-sur-mer, Marseille and Villefranche-sur-mer, it is necessary to consider each of these areas as a unique protection unit. In the Marseille area, the CAS locality harbored the highest level of cryptic species diversity and is the only locality where the C5, C7 and C8 species are found; the C4 species is mainly found on Côte Bleue (Fig. 3 and Table 1). Consequently, to have all the cryptic species under protection requires protecting at least the CAS locality and one locality on the Côte Bleue. Our study strongly suggests that these eight cryptic species have different biotope preferences potentially reflecting contrasted physiological abilities. The ocean acidification and warming components of the global change due to human activity are two of the major threats on coralligenous habitats [START_REF] Ballesteros | Mediterranean coralligenous assemblages: a synthesis of present knowledge[END_REF]. Recent studies by Rodríguez-Prieto (2016) and [START_REF] Martin | One-year experiment on the physiological response of the Mediterranean crustose coralline alga, Lithophyllum cabiochae, to elevated pCO2 and temperature[END_REF] showed that the metabolism, reproduction and survival of the L. stictiforme/cabiochiae species complex are affected by irradiance levels, temperature and pCO2. However, in these studies species were identified ignoring the presence of cryptic species and thus missing potential differences of responses of the cryptic species to warming and acidification. It emphasizes the need for more investigations to determine if these different species have different capacities to cope with global change.

Finally, genetic diversity and structure are both key pieces of information needed to design efficient species protection policy. This study is the first that gives an insight into the genetic diversity and structure at the genomic level for the bioengineer algae of coralligenous habitats (C1 species): genetic differentiation occurred at a very small spatial scale resulting from small dispersal capacities of propagules and particularities of the currents in the Marseille area (Fig. 4, Supplementary Material VII). Yet neither the genetic structure at a larger geographical scale nor the impact of selective processes potentially shaping the differentiation between populations living in variable environmental conditions are known. Therefore, investigating genetic diversity and structure in these cryptic species can reveal different capacity (different level of genetic diversity for example) of adaptation to global change which should be considered in conservation policy of coralligenous habitats.

Data statement

Sequences generated by Sanger sequencing are available on Genbank (Accession nos MK838413-MK838443 for 28S, nos MK859621-MK859850 for PsbA, nos MK859851-MK859896 for COI). Sequences generated by Illumina MiSeq are available on Genbank (Accession nos MK861167-MK861439 for 28S and nos MK859377-MK859620 for PsbA). Raw reads from RNA-seq and capture sequencing are available on Genbank BioProject accession nos PRJNA533203 and PRJNA535387 respectively. Raw reads from MiSeq amplicon sequencing are deposited at DataDryad (https://doi.org/10.5061/dryad. dv4mg). Bioinformatics scripts for processing Miseq amplicon sequencing are available in Github (https://github.com/chaby/dana).

Appendix II. PCR programs, reaction mixes and primers used to amplify the three barcoding markers : psbA, LSU and COI The main groups of haplotypes (hereafter haplogroups) obtained for psbA were used as a reference for marker comparisons. Haplotypes were colored according to the psbA haplogroup of the individual bearing them (using the add-on Network Publisher). Permanova design with locality as random effect factor and depth category, slope, orientation and rugosity as a fixed effect factors.

  IV display the networks built from subsets of individuals which had been sequenced for several markers(Fig. networks: 3 sanger, 2 Miseq). Seven haplogroups were identified in the haplotype network built from long psbA sequences: C1, C2, C3, C4, C5, C6 and C7. The individual compositions of these seven hap-logroups perfectly matched with those of seven haplogroups formed by the other markers (with the exception of a single individual, likely a contamination or a labeling error), for both long and short alignments

Fig. 1 .Fig. 2 .

 12 Fig.1. Neighbour Joinning tree based on euclidean distances between individual multiloci genoptype obtained by capture sequencing (7068 SNPs). Individuals are colored according to their haplogroup determined using the psbA marker. Uncolored tips correspond to individuals with no barcoding sequence.

Fig. 3 .

 3 Fig. 3. Distribution of the eight cryptic species around Marseille coastline. A: Map of the Marseille area with pie chart representing the relative abundances of the cryptic species at the different localities and different depth. D1: shallow depth category between 24 and 31 m depth. D2: depth category between 37-46 m. B: nMDS on Bray-Curtis distances between localities at small spatial scale: from the COU locality to the LPD locality. Stress: 0.04.

Fig. 4 .

 4 Fig. 4. Principal Component Analysis (PCA) on the multilocus genotype for individuals of the C1 cryptic species. Individuals are colored according to their population, and D1 and D2 in population names correspond to depth categories. A: first and second axes are drawn. B: first and third axes are drawn.

1 .

 1 The L. stictiforme/cabiochiae species complex encompasses at least eight cryptic species identifiable by barcoding in the French Mediterranean coast

Figure

  Figure S1 Haplotype network for the psbA marker using 230 sequences (Sanger sequencing) of 744 base pairs

Table 1

 1 Community diversity index for each locality. S: total number of species. N: total number of individuals. D: Margalef species richness index. J': Pielou evenness index. H': Shannon index,1-Lambda': Simpson corrected for small samples. N1: Hill number of order one. N2: Hill number of order 2.

	Locality	S	N	D	J'	H'	1-LAMBDA'	N1	N2
	BPT	3	25	0.6213	0.835	0.9174	0.57	2.503	2.208
	CAS	5	67	0.9513	0.7326	1.179	0.592	3.252	2.399
	CIR	5	69	0.9447	0.3603	0.5799	0.2835	1.786	1.388
	COU	2	19	0.3396	0.9495	0.6581	0.4912	1.931	1.87
	CSC	3	28	0.6002	0.6908	0.7589	0.455	2.136	1.782
	CTF	2	37	0.2769	0.909	0.6301	0.4505	1.878	1.78
	FTF	3	51	0.5087	0.2904	0.319	0.1498	1.376	1.172
	LDM	3	34	0.5672	0.4039	0.4438	0.221	1.559	1.273
	LPD	3	20	0.6676	0.865	0.9503	0.5895	2.586	2.273
	MEJ	3	58	0.4926	0.6568	0.7216	0.4168	2.058	1.694
	MOY	3	56	0.4969	0.3145	0.3456	0.1682	1.413	1.198
	PLN	2	28	0.3001	0.8113	0.5623	0.3889	1.755	1.6
	VPR	4	15	1.108	0.9665	1.34	0.781	3.818	3.689

Table 2

 2 Results of the different PERMANOVA designs. Details of the PERMANOVA tables are available in Supplementary Material V.

		Depth category	Slope	Orientation	Rugosity
	Random locality factor	P(perm) = 0.0001	P(perm) = 0.0001	P(perm) = 0.0001	P(perm) = 0.0003
	Fixed environmental factor	P(perm) = 0.2844	P(perm) = 0.7645	P(perm) = 0.7176	P(perm) = 0.7969
	Interaction	P(perm) = 0.014	P(perm) = 0.3684	P(perm) = 0.3765	P(perm) = 0.3407

Table 3

 3 Results

of the different PERMANCOVA designs. Details of the PERMANCOVA tables are available in Supplementary Material V.

  TableS3PCR programs and mix used to amplify the psbA, 28S and COI (bold characters) markers

	Sequencing Technology	PCR Cycles	PCR Reaction MIX
		5 ' 94°	1µL of DNA template, 1.20 µL MgCl2 (stock 25mM),
		38x[30"94°C, 30"50°C, 2'72°C]	4 µL of 5X GoTaq® Flexi Buffer,3.2 µL of
	Sanger	4'72°C	dNTP(1.25mM),
		4'94°C	0.16 µl of each primer, 0.1 of Go-Taq Polymerase (5u/µL),
		40x[40''94°C,40''49°C,1'72°C]	10.18 µL of H20
	Illumina MiSeq PE 2x200pb	2'94°C; 14 × [1'94°C,1'58°C to 45°C (-1°C/cycle), 1'72°C] 25 × [30"94°C, 45"58°C, 45"72°C] 3'72°C	2µL of DNA template, 0.6 of MgCl2 (25mM), 2µL of GoTaq® Flexi Buffer,1.6 µL of dNTP(1.25mM), 0.1 of each primer at 50 µM, 0.05 µl of GoTaq-Flexy Polymerase (5u/µL), 3.55 µL of H20

Table S4

 S4 Primers used to amplify the psbA, and LSU markers for MiSeq sequencing

	Marker	Primer Forward	Primer reverse	Reference
		Illumina adapter	Illumina adapter
	psbA	CTTTCCCTACACGACGCTCTTCCGATCT Primer (modified from psbA500F)	GGAGTTCAGACGTGTGCTCTTCCGATCT Primer (modified from psbA-R2)	Modified from Yoon et al. 2002
		CTCTGATGGyATGCCtYTAGG	TCA TGC ATW ACT TCC ATA CCT A
		Illumina adpater	Illumina adapter
	LSU	CTTTCCCTACACGACGCTCTTCCGATCT Primer	GGAGTTCAGACGTGTGCTCTTCCGATCT Primer	Designed for this study
		CGTGGGTGAGTCGTTCCTAA	TT GCA GTT CTA GTT TGG AGC A

Table S5 Mean

 S5 Kimura distances between individuals from the different haplogroups for the psbA Table S8 Mean Kimura distances between individuals from the same haplogroup for the 28S marker 802 base pairs. n/c: not calculated Table S9 Mean Kimura distances between individuals from the different haplogroups for the COI marker 594 base pairs.Permanova design testing the effect of the depth category factor in the RMO, CAS and FTF localities.Permanova design with locality as random effect factor and slope as a fixed effect factor

	V(Res) Within level 'FTF' of factor 'LOC' 1177,4 34,313 LOxPe 1*V(Res) + 7,1988*V(LOxPe) Or 1*V(Res) + 2,185*V(LOxOr) + 11,363*S(Or) Details of the expected mean squares (EMS) for the model
	C1 1*V(Res) LOxOr 1*V(Res) + 2,9503*V(LOxOr) C2 C3 Unique Res Source EMS Groups t P(perm) perms Res 1*V(Res) LO 1*V(Res) + 9,4821*V(LO)	C4 P(MC)	C5	C6
	C2 D2, D1 1,3056 0.041 Construction of Pseudo-F ratio(s) from mean squares 0,3359 12 0,1936 Ru 1*V(Res) + 3,3034*V(LOxRu) + 16,794*S(Ru)
	C3 C4 C5 C6 C7 Table S6 Mean Kimura distances between individuals from the same haplogroup for the psbA marker 0.035 0.011 0.038 0.017 0.017 0.046 0.036 0.032 0.032 0.053 0.039 0.035 0.037 0.020 0.053 0.033 0.032 0.034 0.019 0.018 744 base pairs. Clade Intra haplogroup Clade Source Numerator Denominator Num.df Den.df Construction of Pseudo-F ratio(s) from mean squares LOxRu 1*V(Res) + 4,1646*V(LOxRu) Intra haplogroup distances C1 0.003 C2 0 C4 0.0004 C5 0.0006 C6 n/c C7 Denominators LO 1*LO 1*Res 9 164 Source Numerator Denominator Num.df Den.df Res 1*V(Res) Resemblance worksheet Groups Denominator Den.df Pe 1*Pe 0,49149*LOxPe + 0,50851*Res 3 29,38 LO 1*LO 1*Res 9 137 Name: Resem4 D2, D1 1*Res 25 LOxPe 1*LOxPe 1*Res 8 164 Or 1*Or 0,74059*LOxOr + 0,25941*Res 7 50,18 Construction of Pseudo-F ratio(s) from mean squares Data type: Similarity LOxOr 1*LOxOr 1*Res 29 137 Source Numerator Denominator Num.df Den.df Selection: All Average Similarity between/within groups Estimates of components of variation LO 1*LO 1*Res 9 114 Standardise Samples by Total D2 D1 Source Estimate Sq.root Estimates of components of variation Ru 1*Ru 0,79323*LOxRu + 0,20677*Res 3 16,62 Transform: Square root D2 93,643 V(LO) 234,17 15,303 Source Estimate Sq.root LOxRu 1*LOxRu 1*Res 11 114 Resemblance: S17 Bray-Curtis similarity D1 91,045 89,067 S(Pe) -45,26 -6,7275 V(LO) 326,9 18,08 n/c V(LOxPe) 13,612 3,6895 S(Or) -25,597 -5,0593 Estimates of components of variation Sums of squares type: Type III (partial) V(Res) 1238,7 35,195 V(LOxOr) 24,426 4,9422 Source Estimate Sq.root Fixed effects sum to zero for mixed terms V(Res) 1203,6 34,693 V(LO) 269,31 16,411 Permutation method: Permutation of residuals under a reduced model S(Ru) -43,184 -6,5714 Number of permutations: 9999 V(LOxRu) 33,946 5,8263 distances C1 0.0002 C2 0 C3 0.0008 C4 0.001 C5 0 C6 0.002 C7 0.003 Table S7 Mean Kimura distances between individuals from the different haplogroups for the 28S marker 802 base pairs. C1 C2 C4 C5 C6 C2 0.013 C4 0.004 0.017 C5 0.011 0.018 0.014 C6 0.007 0.015 0.010 0.005 C7 0.010 0.018 0.012 0.008 0.003 C1 C5 C6 C5 0.103 C6 0.105 0.072 C7 0.104 0.079 0.090 Table S10 Mean Kimura distances between individuals from the same haplogroups for the COI marker base pairs. n/c: not calculated C1 0.0008 C5 0 C6 n/c C7 0.009 Name Abbrev. Type Levels LOC LO Random 10 Depth De Fixed 2 PERMANOVA table of results Unique Source df SS MS Pseudo-F P(perm) perms P(MC) LO 9 48376 5375,1 4,5652 0,0001 9922 0,0001 De 1 4240,6 4240,6 1,2074 0,2844 2990 0,3807 LOxDe** 2 7091,6 3545,8 3,0115 0,014 9958 0,0148 Res 174 2,0487E+05 1177,4 Total 186 2,7029E+05 ** Term has one or more empty cells Details of the expected mean squares (EMS) for the model Source EMS LO 1*V(Res) + 17,073*V(LO) De 1*V(Res) + 14,926*V(LOxDe) + 44,777*S(De) LOxDe 1*V(Res) + 15,14*V(LOxDe) Res 1*V(Res) Construction of Pseudo-F ratio(s) from mean squares Source Numerator Denominator Num.df Den.df LO 1*LO 1*Res 9 174 De 1*De 0,98586*LOxDe + 0,014142*Res 1 2,02 LOxDe 1*LOxDe 1*Res 2 174 Source Estimate Sq.root V(LO) 245,87 15,68 S(De) 16,266 4,0331 V(LOxDe) 156,43 12,507 Average Similarity between/within groups D2 D1 D2 100 D1 84,207 72,102 LO 1*V(Res) + 12,873*V(LO) Pe 1*V(Res) + 3,5381*V(LOxPe) + 19,006*S(Pe) LO 1*V(Res) + 11,008*V(LO) ** Term has one or more empty cells Source EMS Source EMS Total 137 1,8824E+05 Details of the expected mean squares (EMS) for the model Res 114 1,3271E+05 1164,1 Estimates of components of variation Depth De Fixed 2 PAIR-WISE TESTS Term 'LOxDe' for pairs of levels of factor 'Depth' Within level 'CAS' of factor 'LOC' Unique Groups t P(perm) perms P(MC) D2, D1 2,1014 0,0067 8541 0,0076 Denominators Groups Denominator Den.df D2, D1 1*Res 37 Average Similarity between/within groups D2 D1 D2 33,593 D1 34,375 49,993 Within level 'MOY' of factor 'LOC' Unique Groups t P(perm) perms P(MC) D2, D1 2,1203 0,0573 8 0,0439 Denominators Groups Denominator Den.df D2, D1 1*Res 28 Standardise Samples by Total Transform: Square root Resemblance: S17 Bray-Curtis similarity Fixed effects sum to zero for mixed terms Permutation method: Permutation of residuals under a reduced model Name Abbrev. Type Levels LOC LO Random 10 Pente Pe Fixed Unique Source df SS MS Pseudo-F P(perm) perms P(MC) LO 9 38278 4253,1 3,4335 0,0002 9895 Pe 3 1280 426,66 0,33156 0,7645 9977 0,9391 LOxPe** 8 10693 1336,7 1,0791 0,3684 9936 0,3686 Res 164 2,0315E+05 1238,7 Total 184 2,6947E+05 LOxRu** 11 14360 1305,5 1,1214 0,3407 9932 0,335 ** Term has one or more empty cells LO 9 43219 4802,1 3,9898 0,0001 9925 Or 7 6762,8 966,12 0,76861 0,7176 9933 LOxOr** 29 36994 1275,7 1,0599 0,3765 9880 Res Total Ru 3 1653,1 551,05 0,43177 0,7969 9963 0,8235 182 2,6861E+05 LO 9 33460 3717,8 3,1936 0,0003 9923 0,0002 137 1,6489E+05 1203,6 Source df SS MS Pseudo-F P(perm) perms P(MC) 0,352 Unique 0,7303 PERMANOVA table of results 0,0001 0,0001 Source df SS MS Pseudo-F P(perm) perms P(MC) Rugosity Ru Fixed 4 Unique LOC LO Random 10 PERMANOVA table of results Name Abbrev. Type Levels PERMANOVA table of results Orientation Or Fixed Factors 8 4 Name Abbrev. Type LOC LO Random 10 Number of permutations: 9999 Levels Permutation method: Permutation of residuals under a reduced model Factors Fixed effects sum to zero for mixed terms Factors Sums of squares type: Type III (partial) Number of permutations: 9999 Number of permutations: 9999 Permutation method: Permutation of residuals under a reduced model Resemblance: S17 Bray-Curtis similarity Fixed effects sum to zero for mixed terms Transform: Square root Sums of squares type: Type III (partial) Standardise Samples by Total Sums of squares type: Type III (partial) Selection: 10-13;15;17;19-31;40-97;116-150;152-165;176-187 Resemblance: S17 Bray-Curtis similarity Data type: Similarity Transform: Square root Name: Resem4 Standardise Samples by Total Resemblance worksheet Selection: 1-17;19-75;77-119;121-150;152-187 Selection: 1-17;19-150;152-187 Data type: Similarity Data type: Similarity Name: Resem4 Name: Resem4 Resemblance worksheet effect factor Resemblance worksheet Permanova design with locality as random effect factor and rugosity as a fixed Factors Factors Name Abbrev. Type LOC LO Random 10 fixed effect factor Levels Permanova design with locality as random effect factor and orientation as a V(Res) 1164,1 34,119

** Term has one or more empty cells

Details of the expected mean squares (EMS) for the model

Acknowledgments

We are grateful to the Genotoul bioinformatics platform Toulouse Midi-Pyrenees (Bioinfo Genotoul) for providing help, computing and storage resources. This work benefited from equipment and services from the iGenSeq core facility, at ICM (Paris). We thank the Molecular biology service of the IMBE at the Station Marine d'Endoume (A. Haguenauer, C. Rocher, M. Selva), C. Carpentieri (molecular biologist at the Macherey-Nagel company) for helping with DNA purifications, and the Diving Service of the Pytheas Institute for providing samples.

Funding

This work is a contribution to the Labex OT-Med (no. ANR-11-LABX-0061) funded by the French Government 'Investissements d'Avenir' programme of the French National Research Agency (ANR) through the A*MIDEX project (no. ANR-11-IDEX-0001-02).

Samples were obtained thanks to EraNet (SeasEra) CIGESMED-ANR convention no 12-SEAS-0001-01. Financial support was provided by the project DEVOTES (DEVelopment Of innovative Tools for understanding marine biodiversity and assessing good Environmental Status) funded by the European Union under the 7th Framework Programme, 'The Ocean for Tomorrow' Theme (grant agreement no. 308392), http://www.devotes-project.eu.

Author contributions AC, J-PF, RD and ADJ conceived the study. ADJ, ZE, RD, AH, AEC, DG, SS, CR and MS produced the data. ADJ and AC analyzed the data and wrote the paper. ADJ, AEC, SS, LLG and AC contributed to manuscript editing and revisions.

Appendix A. Supplementary material

Supplementary data to this article can be found online at https:// doi.org/10.1016/j.ympev.2019.04.005.

Appendix I. Sampling information for each locality. Latitudes and longitudes are north and east, respectively. below). The coordinates were calculated using the centroid of the four sampling sites that were effectively sampled. The abundances of each site were summed up because of their geographical proximity. Appendix VIII. Frequency distributions of the pairwise alleles differences between MLG in all populations of the C1 species.

Figure S6 Frequency distribution of the pairwise number of alleles differences between MLG for the CCAD1 population (original data in blue), compared with the frequency of pairwise distances after 1000 sexual events (one generation each, outcrossing and selfing) in which neither identical MLG nor somatic mutations are expected (simulated data in green), and with the frequency distribution of the pairwise distances after 1000 sexual events (one generation each, outcrossing), without selfing (in pink).

Figure S7 Frequency distribution of the pairwise number of alleles differences between MLG for the CCAD2 population (original data in blue), compared with the frequency of pairwise distances after 1000 sexual events (one generation each, outcrossing and selfing) in which neither identical MLG nor somatic mutations are expected (simulated data in green), and with the frequency distribution of the pairwise distances after 1000 sexual events (one generation each, outcrossing), without selfing (in pink).

Figure S8 Frequency distribution of the pairwise number of alleles differences between MLG for the COU population (original data in blue), compared with the frequency of pairwise distances after 1000 sexual events (one generation each, outcrossing and selfing) in which neither identical MLG nor somatic mutations are expected (simulated data in green), and with the frequency distribution of the pairwise distances after 1000 sexual events (one generation each, outcrossing), without selfing (in pink).

Figure S9 Frequency distribution of the pairwise number of alleles differences between MLG for the FTFD1 population (original data in blue), compared with the frequency of pairwise distances after 1000 sexual events (one generation each, outcrossing and selfing) in which neither identical MLG nor somatic mutations are expected (simulated data in green), and with the frequency distribution of the pairwise distances after 1000 sexual events (one generation each, outcrossing), without selfing (in pink).

Figure S10 Frequency distribution of the pairwise number of alleles differences between MLG for the FTFD2 population (original data in blue), compared with the frequency of pairwise distances after 1000 sexual events (one generation each, outcrossing and selfing) in which neither identical MLG nor somatic mutations are expected (simulated data in green), and with the frequency distribution of the pairwise distances after 1000 sexual events (one generation each, outcrossing), without selfing (in pink).

Figure S11 Frequency distribution of the pairwise number of alleles differences between MLG for the LPD population (original data in blue), compared with the frequency of pairwise distances after 1000 sexual events (one generation each, outcrossing and selfing) in which neither identical MLG nor somatic mutations are expected (simulated data in green), and with the frequency distribution of the pairwise distances after 1000 sexual events (one generation each, outcrossing), without selfing (in pink).

for the RMO population (original data in blue), compared with the frequency of pairwise distances after 1000 sexual events (one generation each, outcrossing and selfing) in which neither identical MLG nor somatic mutations are expected (simulated data in green), and with the frequency distribution of the pairwise distances after 1000 sexual events (one generation each, outcrossing), without selfing (in pink).