Prof Mathieu Acher
email: @acherm

Learning the Linux Kernel Configuration Space: Results and Challenges

Given a configuration, can humans know in advance the size, the compilation time, or the boot time of a Linux kernel? Owing to the huge complexity of Linux (there are more than 15000 options with hard constraints and subtle interactions), machines should rather assist contributors and integrators in mastering the configuration space of the kernel. In this talk, Mathieu Acher will introduce TuxML an OSS tool based on Docker/Python to massively gather data about thousands of kernel configurations. Mathieu will describe how 200K+ configurations have been automatically built and how machine learning can exploit this information to predict properties of unseen Linux configurations, with different use cases (identification of influential/buggy options, finding of small kernels, etc.) The vision is that a continuous understanding of the configuration space is undoubtedly beneficial for the Linux community, yet several technical challenges remain in terms of infrastructure and automation."

Is taming the Linux kernel configuration space a harder problem than resolving Chess?

  predict the class (BUILD/FAILURE) out of options values • Retrospectively and despite our investment, we found relatively few bugs of Linux -Is it due to the way we sample? -Is it due to the stable version of Linux we chose? -Is it due to the high-quality of Linux, its contributors and its industry-strength, community-based effort? Challenges • Sampling is based on randconfig -randconfig does not produce uniform random samples -hypothesis: the testing "community" has over-fitted randconfig • We need other sampling strategies! -Uniform (but SAT-based techniques should be improved) -Coverage-based sampling (e.g., t-wise) -Knowledge-based sampling • The cost of gathering data is important (15K+ hours of computation) • Incremental build of configurations • Bugs do not transfer well • However, kernel size "knowledge" may transfer -Instead of starting from scratch, we can transfer a prediction model for another version of Linux (ongoing work) Challenges • Kernel CI / 0-day -Our focus: testing configurations in the large -Complementary! -Learning techniques can be used in both contexts -Sharing data

  Julia Lawall and Gilles Muller "JMake: Dependable Compilation for Kernel Janitors." In 47th Annual IEEE/IFIP International Conference on Dependable Systems and Networks, DSN 2017 • Iago Abal, Claus Brabrand, and Andrzej Wasowski "42 variability bugs in the linux kernel: a qualitative analysis". In ACM/IEEE International Conference on Automated Software Engineering, ASE'14 • Jean Melo, Elvis Flesborg, Claus Brabrand, and Andrzej Wasowski "A Quantitative Analysis of VariabilityWarnings in Linux". In Proceedings of the Tenth International Workshop on Variability Modelling of Software-intensive Systems (VaMoS'16) • Sarah Nadi, Thorsten Berger, Christian Kästner, and Krzysztof Czarnecki "Where Do Configuration Constraints Stem From? An Extraction Approach and an Empirical Study" IEEE Trans. Software Eng., 2016 • Minghui Zhou, Qingying Chen, Audris Mockus, and Fengguang Wu "On the Scalability of Linux Kernel Maintainers' Work". In Proceedings of the 2017 11 th Joint Meeting on Foundations of Software Engineering (ESEC/FSE 2017)

	Challenges
	• "Smart" build infrastructure
	• Unify the force!

-Other properties (e.g., warnings, boot, security)

• With devs/contributors in the loop -We need knowledge to validate our learning model -We need knowledge to apply "smart" sampling -We aim to produce actionable knowledge • TUXML needs you! Conclusion (feedbacks welcome!) • Learning From Thousands of Build Failures of Linux Kernel Configurations -Mathieu Acher, Hugo Martin, Juliana Alves Pereira, Arnaud Blouin, Djamel Eddine Khelladi, Jean-Marc Jézéquel -https://hal.inria.fr/hal-02147012 • Learning Very Large Configuration Spaces: What Matters for Linux Kernel Sizes -Mathieu Acher, Hugo Martin, Juliana Pereira, Arnaud Blouin, Jean-Marc Jézéquel, Djamel Eddine Khelladi, Luc Lesoil, Olivier Barais -https://hal.inria.fr/hal-02314830 •


Deewakar Sharma

Arnaud Erriguible

Gurunath Gandikota

Daniel Beysens

Sakir Amiroudine
email: sakir.amiroudine@u-bordeaux.fr

Vibration-induced thermal instabilities in supercritical fluids in the absence of gravity

Keywords: Supercritical fluid, thermo-vibrational instability, Rayleigh-vibrational, parametric instability, piston effect. I

Supercritical fluids (SCFs) are known to exhibit anomalous behaviour in their thermophysical properties such as diverging compressibility and vanishing thermal diffusivity on approaching the critical point. This behaviour leads to a strong thermo-mechanical coupling when SCFs are subjected to simultaneous thermal perturbation and mechanical vibration. The behaviour of the thermal boundary layer (TBL) leads to various interesting dynamics such as thermo-vibrational instabilities, which become particularly ostensive in the absence of gravity. In the present work, two types of instabilities, Rayleigh-vibrational and parametric instabilities, have been numerically investigated under zero-gravity in a 2D configuration using a mathematical model wherein density is calculated directly from continuity equation. Comparison of experimental observations with numerical simulations is also presented. The peculiarity of the model warrants instabilities to be investigated in a more stringent manner (in terms of higher quench percentage and closer proximity to the critical point), unlike the previous studies wherein the equation of state was linearized around the considered state for the calculation of density, resulting in a less precise analysis. In addition to providing physical explanation causing these instabilities, the effect of various parameters on the critical amplitude for the onset of these instabilities is analysed. Furthermore, various attributes such as wavelength of the instabilities, their behaviour under various factors (quench percentage and acceleration) and the effect of cell 2 size on the critical amplitude is also investigated. Finally, a 3D stability plot is shown describing the type of instability (Rayleigh-vibrational or parametric or both) to be expected for the operating condition in terms of amplitude, frequency and quench percentage for a given proximity to the critical point.

INTRODUCTION

Supercritical fluids (SCFs) are a class of fluids which exist beyond the liquid-vapor critical point. They have properties intermediate to those of liquid and gas phases. They manifest certain properties of liquids such as high density and solubility and gases such as high compressibility and low viscosity. One of the most striking features of the supercritical fluids is that on approaching to the critical point, various thermo-physical properties show a singular behaviour [START_REF] Stanley | Introduction to Phase Transitions and Critical Point Phenomena[END_REF], such as diverging isothermal compressibility , thermal expansion ( ), heat capacity at constant pressure ( ) and thermal conductivity ( ), and vanishing thermal diffusivity ( ) and sound speed ( ). This anomalous behaviour of properties of SFCs makes them a promising candidate in various scientific and industrial applications such as efficient refrigeration systems [START_REF] Lorentzen | [END_REF], drilling technologies [3], high performance rocket propellants [4,5] and other industrial applications [6]. Close to the critical point, all the thermo-physical properties can be described using a common parameter called critical point proximity , (where T is temperature and is the critical temperature of the fluid). Each property has a specific exponent and interestingly, this is true for any supercritical fluid. This ubiquitous behaviour arises from microscopic attributes of the macroscopic properties wherein each property can be written as the sum of mean and fluctuating contributions. On approaching the critical point, the fluctuating components dominate the mean behaviour leading to the formulation of universal behaviour of these thermo-physical properties, having the same asymptotic critical exponents for all fluids (Renormalization Group Theory for Ising model [START_REF] Stanley | Introduction to Phase Transitions and Critical Point Phenomena[END_REF][START_REF] Zappoli | Heat Transfers and Related Effects in Supercritical Fluids[END_REF]).

SCFs demonstrate some surprising behaviour too. In the thermal proximity of the critical point, it is expected that diffusion of a thermal perturbation inside a SCF will happen at an extremely slow rate, due to its vanishing thermal diffusivity. However, it was observed [START_REF] Nitsche | Proceedings of the 6th European Symposium on Material Sciences under Microgravity Conditions (ESA SP[END_REF] that in the critical point proximity, thermal relaxation of an SCF (SF 6 in their experiments) happens extremely fast (in a few seconds instead of days as generally expected). This phenomenon of critical speeding up of thermal homogenization, is attributed to the high compressibility of SCFs, has been termed as piston effect [START_REF] Onuki | [END_REF][10][11].The piston effect is the consequence of a wave propagation (caused by thermal expansion in the TBL through the bulk fluid at the speed of sound converting the mechanical energy of the waves into the thermal energy thereby causing an increase in the temperature of the bulk. Similar explanation holds when the boundary is cooled wherein the fluid in the TBL contracts and adiabatic cooling thermalizes the bulk fluid. The time scale on which the thermal homogenization occurs is found to be very small as compared to the diffusion time scale and is termed as piston effect timescale. It is worth mentioning that under the presence of gravity, high compressibility causes SCF to compress under its own weight leading to the density stratification. Moreover, due to the singular behaviour of the properties, even a very small temperature disturbance makes SCF unstable under gravity, which had earlier circumvented the observation of the piston effect.

One of the primary investigations which have drawn attention of several researchers in SCF community pertains to the study of their behaviour under simultaneous thermal quench (quench herein refers to cooling the boundaries of the cell) and mechanical vibrations in weightlessness conditions. This has been motivated by g-jitters experienced by space vehicles and cryogenic reservoirs aboard the International Space Station (ISS). Further, the complex thermo-mechanical coupling leads to the evolution of several intriguing behaviours in the TBL leading to various thermo-vibrational instabilities. Experimental and numerical studies with supercritical CO 2 and SF 6 under weightlessness have reported evidences of such instabilities as described in [12][13][14][15]. Experiments with supercritical have also been reported in literature where micro-gravity conditions were artificially simulated by means of a strong magnetic field [16][17][18][19][20][START_REF] Chatain | SBT-INAC[END_REF]. When supercritical close to the critical point is simultaneously quenched and subjected to mechanical vibrations, finger-like structures were observed normal to the direction of vibration. The authors in Ref. [START_REF] Amiroudine | [END_REF] investigated the problem of simultaneous thermal quench and vibration with a linearized equation of state for supercritical CO 2 . They reported finger-like pattern appearing from the TBL which was attributed to the thermo-vibrational instability. The study was further extended using the same model in [23] wherein different types of instabilities were analysed and quantified in terms of the critical amplitude of vibration.

One of the primary assumptions in the aforementioned numerical studies of thermovibrational instabilities has been the linear equation of state for the calculation of density. This assumption not only limits a higher temperature perturbation but also circumvents an accurate analysis very close to the critical point. As the origin of these instabilities is ascribed to dynamic changes of density field in the TBL, their effective capturing is hence highly affected by precise calculation of the density. In lieu of these considerations and to seek further insights into the physical phenomena, the following aspects, different from the similar previous studies [START_REF] Amiroudine | [END_REF]23] are demonstrated in this work.

 One of the primary features pertains to the use of a mathematical model which directly incorporates the dependence of pressure on temperature and density into the momentum equation facilitating the investigation as close as for supercritical with higher quench percentages.

 A comparison with the experimental observations is also presented wherein the patterns and wavelengths of these instabilities are compared.

 In case of Rayleigh-vibrational instabilities, analysis of the dynamic behaviour of fingers (wavelengths) is presented for various quench percentages and an unexpected behaviour is observed at higher accelerations wherein the wavelength begins to show an increasing trend after initially decreasing with acceleration.

 It is shown that the influence of perturbations arising from the corners is not essential for the onset of parametric instabilities as these have been observed even in case of symmetric boundary conditions at the walls along the direction of vibration.

 The critical amplitude has been investigated for both the instabilities with proximity to the critical point. In case of parametric instabilities, it was shown to depend on cell dimensions along the dimension of vibration.

 By virtue of an analysis closer to the critical point and with higher quench percentage, a higher decreasing trend is found for, a) critical Rayleigh vibrational number with proximity to the critical point, and b) wavelength with quench percentage in case of parametric instabilities.

Finally, a 3D stability diagram highlighting the type of instability to be expected based on quench percentage and frequency is shown.

II. MATHEMATICAL MODEL AND SOLUTION METHODOLOGY

In this section, we present the mathematical model applied to solve the full set of governing equations (see also details in [24,25]). Let us consider a Newtonian fluid characterized by its thermo-physical properties, namely density , isothermal compressibility, and thermal expansion coefficient at constant pressure, . The infinitesimal variations of the pressure ( ) and the density ( with time can be written as follows,

The last equation of the system of Eq. ( 1) corresponds to the conservation of mass. The thermo-physical properties such as and are evaluated using correlations available from the Renormalization Group Theory [START_REF] Zappoli | Heat Transfers and Related Effects in Supercritical Fluids[END_REF]23] as mentioned in Table 1.

The equation for conservation of momentum in a non-conservative form for a Newtonian fluid, assuming Stokes hypothesis , and correspond to the classical shear viscosity and compression (bulk) viscosity or second coefficient of viscosity, respectively) can be written as,

Here is the material derivative, while F and denote the volumetric force and the thermodynamic pressure, respectively. Similarly, the conservation of energy, in terms of temperature (derived from internal energy) can be written as,

Here, is the thermal conductivity and is the dissipation energy with being the tensor of deformation rate (The Einstein summation convention on repeated indices is applied). In the current study, the viscous dissipation is negligible with respect to the other terms and thus the term is dropped off from Eq. (3).

Using Eq. ( 1) and Eq. ( 3), we can write the temporal variation of pressure as, The final system includes the conservation of momentum ( ) (Eq. ( 2)) and energy through the temperature (Eq. ( 3)) along with evolution of pressure field (Eq. ( 4)) and density from last part of Eq. ( 1). The thermodynamic variables, namely, pressure, temperature, velocity and density calculated above are then advected from their total derivatives as, (5) where represents either of the variable the components of or These above set of equations (last part of Eq. 1 and Eqs. 2, 3, 4 and 5) in conjunction with the thermo-physical properties, as described in Table 1, include all the important physics essential to investigate any thermo-fluidic system. In the present study, the term denotes the force per unit volume acting on the fluid due to vibrational acceleration in direction. Here, A is the amplitude of vibration and the frequency is denoted by ( ).

Before proceeding further, it is important to emphasize on some of the interesting features of the methodology presented above: (i) the momentum equation, Eq. ( 8), is completely autonomous as it does not contain any unknown pressure unlike most of the usual cases where specific pressure-velocity coupling algorithms have to be considered, (ii) the density is calculated directly from the continuity equation (Eq. ( 10)) which ensures mass conservation resolvable to the machine precision. Thus, the model can be described without any explicit equation of state (EOS) for the calculation of density, though it appears implicitly through thermo-physical properties and while the coupling for the pressure is implicitly incorporated in the momentum equation through Eq. ( 7).

The governing equations described above solved numerically using home-made CFD code, Thetis, which has already been described and validated for a number of benchmark cases for incompressible fluids [26,27] and compressible fluids [24,[28][29][30]. The fluxes in the equations are discretized using second order centred difference scheme. An exponential grid with a total of 300 300 elements is used with the smallest element being near the wall. The implicit forward in time Euler scheme is employed to discretize the time dependent term with time step of which corresponds to a compromise between accuracy, physical description of the phenomena and CPU time. Further, the direct solver MUMPS [31] is used to solve the discretized system. A step by step numerical procedure for solving them is described in the Appendix.

III. RESULTS AND DISCUSSION

In order to analyse the behaviour of a supercritical fluid under the combined effect of thermal perturbation and mechanical vibration, we consider a square cell (size ) with solid walls filled with supercritical , implying an isochoric process, as shown in Fig. 1. The dimensions of the cell are the same as considered in Ref. [19,20]. The thermo-vibrational instabilities can be categorized as Rayleigh-vibrational (RV) or parametric based on the relative direction of the temperature gradient with vibration. The former instability develops in the direction normal to vibration direction while the latter grows parallel to it. In order to gain insight into the physical mechanism leading to each instability, it is essential to analyse each of them separately. This is attained by imposing appropriate boundary conditions pertinent only to that type of instability. Thus, for RV instabilities, the top ( ) and bottom ( ) walls are quenched while for parametric instability only the vertical walls ( and ) are quenched.

The remaining walls in both the cases are maintained at adiabatic condition. The system is analysed for a wide range of vibration frequencies, varying from 5 to 35 while the proximity to the critical point and the quench percentage, are varied from 5

to 2000 and to , respectively. Further, the system is investigated under weightlessness conditions zero gravity.

We initially present a comparison with experimental observations followed by discussions on various thermo-vibrational instabilities. A.

Rayleigh-vibrational instability

Rayleigh-vibrational instabilities are observed when the direction of temperature gradient is normal to the direction of vibration, which leads to the appearance of finger-like structures in the TBL. In order to illustrate these instabilities, we first present the comparison with experimental observations followed by the physical description of the mechanism leading to these instabilities.

Comparison with experimental observations

The experimental conditions [START_REF] Chatain | SBT-INAC[END_REF] correspond to the heating of all the 4 walls (Fig. 1)

simultaneously while the cell is vibrated with frequency, and amplitude, . In the experiments, temperature is monitored on the walls of the experimental cell.

However, the readings are found to be erroneous because of the induced eddy currents in the leads of the temperature probes in intense magnetic field. Thus, applying temperature boundary conditions from the experiments to the numerical simulations will lead to difference in results. In lieu of these considerations, the temperature at the boundary is adjusted to attain the best agreement between the experimental and numerical observations. Subsequently, the error between experimental and numerical conditions are evaluated and these correspond to error in the initial temperature ( ) while error in the temperature imposed at the boundary, wall temperature ( ). [START_REF] Chatain | SBT-INAC[END_REF] and for thermo-vibrational instabilities ( and ). There exists a difference in experimental and numerical conditions (refer text for explanation).

These finger-like structures correspond to Rayleigh-vibrational instabilities, the mechanism of which is described in the following section.

Mechanism of Rayleigh-vibrational instabilities

We briefly present here the mechanism causing these instabilities. Consider a schematic as shown in Fig. 3 when a cell filled with SCF is at initial temperature and the top wall ( ) is quenched by . Subsequently, a very thin TBL (attributed to the vanishing behaviour of thermal diffusivity ) is formed wherein large density gradients are present due to the diverging behaviour of the thermal expansion ( ) as illustrated in Fig. 3. For the sake of simplicity, the TBL has been enlarged in Fig. 3. Let us consider the entire TBL and bulk fluid as two different regions (layers) as shown in Fig. 3, primarily motivated by different densities in these regions. The vibration of the cell in the direction induces inertial forces in the TBL as well as the bulk. However, by virtue of density difference, in the TBL and the bulk, the difference in inertial force induces a velocity difference, (where is the mean density) and hence a Bernoulli-like pressure difference between these layers. Thereby, an oscillatory relative motion exists which tends to destabilize the system which is, however, stabilized by the effect of diffusive forces (viscous and thermal). With increase in the thickness of the TBL with time, the difference in the inertial forces and thus Bernoulli-like pressure difference will increase thereby overcoming the stabilizing effect, resulting in the appearance of finger-like structures as shown in Fig. 2(a-b). Although the primary effect leading to these instabilities is attributed to the shear between fluid layers, which therefore has a Kelvin-Helmholtz type origin, this instability has been termed as "Rayleighvibrational instability" [START_REF] Gershuni | Thermal Vibrational Convection[END_REF]. It is worth mentioning that owing to the periodicity in the flow direction by virtue of vibration, the finger-like patterns on an average remain at the same place before some adjacent fingers merge (see Sec V.A.4). As described above, there exists a competition between the stabilizing and the destabilizing effects and thus the onset of these instabilities can be described in terms of a dimensionless number, termed as the Rayleigh-vibrational number ( . It is defined as the rise of fluid elements against viscous forces due to Bernoulli-like pressure difference, resulting in a driving force on fluid element of characteristic length, .

The terminal velocity due to this driving force as balanced by viscous force can be described as with convective time scale ( being the dynamic viscosity). The ratio of these two time-scales (diffusion and convection ) is defined as the Rayleigh-vibrational number, (the factor 2 comes from the time average in the high frequency approximation [START_REF] Gershuni | Thermal Vibrational Convection[END_REF]). In case of supercritical fluids, the characteristic length , which represents the diffusion length scale, is very small as compared to the geometrical length scale.

Hence, it is reasonable to consider the thickness of the TBL ( ) as the characteristic length scale following which the Rayleigh-vibrational number in the present case reduces to [START_REF] Amiroudine | [END_REF]. This includes the effect of various parameters: (i) the distance from the critical point, (ii) quench conditions ( ) and (iii) vibrational parameters (frequency and amplitude of vibration). The effect of these parameters on the Rayleigh-vibrational instability is presented below.

Critical amplitude for Rayleigh vibrational instabilities

In the previous section, we described the physical mechanism leading to Rayleighvibrational instability. As there exists a competition between shear and diffusive forces, it is therefore possible to define a critical amplitude ( ) of vibration for a fixed frequency ( ) beyond which these instabilities will be observed. In order to ascertain the critical amplitude, the simulation has been run till and the smallest amplitude at which the instability (waviness in the TBL) appears is chosen to be the critical amplitude at that and quench percentage . The critical amplitude is analysed for two different cases, (i) same proximity but varying frequency, and quench percentage q and, (ii) for the same quench temperature, . In both the cases, the critical amplitude is found to decrease with increase in frequency, quench percentage and decreasing proximity to the critical point. For the sake of brevity, only the results for the latter case have been illustrated in Fig. 4. A significant remark is that physical meaningful results have been obtained as close as with as high as 50%

illustrating the strength and capability of the model to capture the behaviour of a highly compressible system with large property variations.

The above observations can be explained as follows. A higher frequency entails a higher acceleration and thus a larger difference in the inertial forces between layers of different densities when compared to the case of lower frequency. Similarly, a higher quench percentage will result in a higher temperature gradient thereby causing a higher density variation leading to the previous conclusion, for the same vibration parameters ( ). This implies that for the same stabilizing action provided by the diffusive forces, the desired threshold to overcome it will be attained at a lower amplitude for a higher frequency or quench percentage. Furthermore, on approaching the critical point, the diverging behaviour of the thermal expansion results in large density gradients while the vanishing diffusive forces weaken the stabilizing effect. Thus, for the same quench temperature, a higher Bernoulli-like pressure difference is created with decreasing proximity to the critical point causing a lower amplitude for the same vibration frequency as observed in Fig. 4. It is important to mention here that the comparison of critical amplitudes on approaching the critical point based on the same is not appropriate. This is because the same for different proximities to the critical point will induce a different value of and results in two independent parameters ( and ). Thus, it is more reasonable to compare the critical amplitude with proximity to the critical point for the same temperature quench ( ) as described above.

Wavelengths in Rayleigh-vibrational instabilities

The Rayleigh-vibrational instabilities described above lead to the appearance of finger-like structures as shown in Fig. 2. These fingers can be characterized by the distance between them wavelength of the instabilities as marked in Fig. 2. We compare the behaviour of the fingers obtained from experiment and numerical simulations before drawing out further conclusions from the numerical results. This is shown in Fig. 5 for the same temperature quench and as a function of the proximity to the critical point.

The wavelength considered here refers to the average wavelength (dividing the cell dimension by the number of fingers plus one). It can be observed that the wavelengths obtained from numerical simulations show a similar trend and the deviation decreases from 29 % to 10 % on moving away from the critical point.

This is attributed to significant variations in the thermo-physical properties on approaching the critical point which can affect the behaviour, both in experiments and numerical simulations causing a higher discrepancy closer to the critical point. A noticeable observation pertains to the decrease in the wavelength on approaching the critical point. This behaviour is attributed to a higher Bernoulli-like pressure difference when approaching the critical point due to larger density variations in the TBL, keeping all the other factors constant. Consequently, the number of sites at which the TBL becomes unstable will be higher ( minimize the energy, potential and kinetic, through more locations), which results in more fingers and hence lower wavelengths as observed in Fig. 5.

(a) Time evolution of the wavelength

It has been mentioned in [START_REF] Amiroudine | [END_REF]23] that wavelengths do not evolve in time. However, it is observed that after the onset of instability the wavelength remains constant for a certain period of time. Then, under the action of diffusion, adjacent fingers merge, resulting in the change of the pattern of the wavelength. This is illustrated in Fig. 6(a-d) showing the evolution of the wavelength at various times for and .

It can be observed that initially, the distance between the fingers remain constant for a certain time (Fig. 6(a-b)). However, as the time advances, fingers not only grow into the bulk but also become thicker in size due to the diffusion enhanced by vibrational acceleration. When the fingers are close enough to each other, some adjacent fingers can merge with each other, causing an effective reduction in the number of fingers thereby increasing the wavelength. For the sake of explanation, this has been highlighted for one such case in Fig. 6 (c-d).

Figure 6(a-d). Instant velocity-vector plot coloured by temperature contours illustrating the merging of fingers (marked in Fig. 6(b-d)) with time ( ).

In order to further explain the merging process, the instant velocity vectors are plotted for the merging process of two fingers as highlighted in the Fig. 6(a). For the sake of clarity, the velocity vectors near the wall have not been shown. It can be observed that the velocity field (vortices) corresponding to two individual and distinct fingers (Fig. 6(a)) begin to interact with each other as shown in Fig. 6(b). The interaction, in addition to diffusion, is also facilitated by vibrational acceleration in the horizontal direction which causes an increase in the horizontal velocity as fingers grow in the bulk. Subsequently, the vortices tend to overlap and finally merge to form a single finger (Fig. 6(c-d)).

(b) Anomalous behaviour of wavelength with quench

Fig. 7 shows wavelengths as a function of reduced acceleration, for and different quench percentages, q. Here, the wavelengths have been measured just at the onset of instabilities and at the middle of the cell in order to circumvent the influence of boundaries and merging of fingers. It can be seen that the wavelength decreases with the increase in q. A higher q implies a larger temperature gradient in the TBL and therefore a larger density difference. Thus, for the same acceleration, a higher Bernoulli-like pressure difference will exist for a higher implying that the stabilizing diffusive forces will be weakened at more local sites along the TBL in order to minimize the energy. Subsequently, more fingers (or a lower wavelength) with a higher quench percentage is observed for the same acceleration. A similar explanation holds for the decrease in wavelength with acceleration for the same quench percentage (Fig. 7) as a higher acceleration pertains to higher pressure difference and thus more local sites of destabilization. However, a different (anomalous) behaviour in this context can be seen for higher accelerations for both the quench percentages. This unusual behaviour can be qualitatively explained as follows.

As mentioned previously, a higher Bernoulli-like pressure difference, attributed to either a higher acceleration or a larger density variation, will result in more plausible local sites where the TBL will be destabilized. In addition, when these fingers grow into the bulk, they have been found to merge as illustrated in Fig. 6. Now, combining both these observations, with the increase in acceleration, the wavelength at the onset becomes so small (due to the increase in number of sites, covering the complete extent, termed as span hereon, of TBL for onset of instabilities) that as the fingers physically appear and protrude into the bulk, they merge into one another. As a result, a decrease in the effective number of fingers and thus a higher wavelength is observed as in Fig. 7. In order to support this proposed explanation ( anomalous behaviour of wavelength with acceleration is attained once the entire span of TBL is perturbed), we investigate the scenario with two different cell sizes (square cavity of and ) and thus compare the behaviour for different spans of the TBL. Let us donate the acceleration which perturbs the entire span of TBL in the case of and as ' ' and ' ', respectively.

It is phenomenological to ascertain that , as the bigger cell represents a larger extent (span) of the TBL necessitating a higher acceleration for the aforesaid condition. Consequently, for an acceleration slightly higher than the wavelengths in case of smaller cell will increase with acceleration (as per previous explanation) while the usual trend of decrease in wavelength with acceleration can be expected for a bigger cell. In lieu of the proposed explanation, it is therefore anticipated that the threshold acceleration beyond which anomalous behaviour in wavelength will be observed will increase with cell dimensions (as bigger cell represents longer horizontal walls and thus a wider span of the TBL). It can be seen that the expected outcome, as described above, is in coherence with the behaviour of wavelength with cell size as shown in

Ra v as a distance from the critical point

Rayleigh vibrational number was introduced in Sec. V.A.2 and is known to describe the onset criterion for Rayleigh-vibrational instabilities as a function of various thermo-physical and vibrational parameters [START_REF] Amiroudine | [END_REF]. One of the important parameters in is the thickness of the thermal boundary layer ( ) which changes as a function of time. Thus, in order to evaluate the critical , the time at which the TBL becomes unstable is noted from the numerical simulations. It follows that the critical thickness of the TBL is evaluated using . Subsequently, the critical Rayleigh vibrational number can be calculated using the expression, as defined in Sec V.A.2. The authors in Ref. [START_REF] Amiroudine | [END_REF] evaluated for a fixed frequency and amplitude as a distance from the critical point and found it to increase on approaching the critical point. The critical Rayleigh number, , has been described by a power law fit as with two different slopes when close ( ) and far ( ) from the critical point. Similarly, authors in Ref. [23],

analysed for a fixed frequency and amplitude but over a wider range of amplitude and reported a similar behaviour.

In the present work, is analysed as a function of a single parameter, vibration frequency. The amplitude of vibration and quench temperature for each case is varied from to and to 30%, respectively. Thus, based on different combinations of amplitude, proximity to the critical point and quench percentage (and hence the quench temperature), the critical Rayleigh-vibrational number is calculated and is shown in Fig. 9 for two different frequencies, and . It can be seen that indeed increases on approaching the critical point. This is mainly attributed to two factors, the vanishing thermal diffusivity ( ) and the diverging thermal expansion ( ) on approaching the critical point, which increases the diffusion time scale and causes a higher Bernoulli-like pressure difference and thus a lower convective time scale (see Sec V.A.2). Furthermore, similar to the studies of [START_REF] Amiroudine | [END_REF], can be described by a power law fit as with two different slopes when close and far ( ) to the critical point. In the current work, our definition of closeness refers to as near as while maximum distance is restricted to .

B. Parametric instabilities

In this section, we analyse the instabilities when the direction of vibration is parallel to the direction of temperature gradient. It is well established that a two-phase fluid (miscible or immiscible)can exhibit parametric instabilities when subjected to vibrations perpendicular to its interface [18,[START_REF] Kumar | [END_REF]34]. In the present study, when the SCF close to its critical point is quenched and simultaneously subjected to vibrations along the direction of temperature gradient, the TBL becomes unstable leading to the appearance of waves or finger-like structures. This is illustrated in Fig. 10 for and for one time-period of vibration.

Here the direction of vibration ( direction) isalong the temperature gradient when the vertical walls ( and ) are quenched. In the current work, the effect of higher quench percentage and boundary conditions to explain the mechanism of these instabilities has been considered.

In order to understand the physical phenomenon inducing these instabilities, let us consider the schematic as shown in Fig. 11(a) where the SCF, initially at temperature , is quenched on the left wall ( ). The density of the fluid in the TBL will be significantly higher than that of the bulk fluid due to lower temperature therein. Thus, if considering the fluids in the bulk and the TBL as two different fluids (owing to the significant difference in their properties), an equivalent configuration can be represented as shown in Fig. 11(b). This resembles to an arrangement similar to that of two immiscible fluids acted upon by vibration under zero-gravity.

Thus, when the natural frequency of the system matches with the external frequency, wavelike patterns appear as shown in Fig. 10. It can also be observed that the waves appear once at each TBL in one cycle of vibration thereby exhibiting a harmonic type of parametric instability as can be observed in Fig. 10. In continuation with the above explanation, we provide a further insight into the mechanism leading to the onset of parametric instabilities. The authors in Ref. [23] ascribed these instabilities to the formation of vortices. In the following section, we attempt to provide a physical explanation leading to the appearance of these vortices. This will also elucidate the nonuniform appearance of waves along the span of the TBL (waves/instabilities are observed initially near the horizontal walls followed by their appearance at the middle) as can be seen in Fig. 10.

Mechanism of parametric instabilities

As illustrated in Fig. 11, our configuration is equivalent to parametric instabilities in case of two immiscible fluids under zero-gravity. However, as there is only a single fluid present and hence the absence of a real interface, let us call the boundary separating the bulk and the TBL as a 'virtual-interface' for the sake of understanding. Thus, the instabilities will be observed when the virtual-interface is adequately perturbed. In order to explain how this perturbation is obtained, let us consider a case with the left wall ( ) quenched and the cell is vibrating along the direction. Under the same vibrational acceleration, there will exist inertial difference between the lighter fluid (bulk region) and the denser fluid (TBL region) resulting in a pressure difference across this 'virtual interface'. When a fluid element from the bulk impacts the element of the TBL (or vice-versa), the transfer of momentum will therefore yield a significant variation in the velocities of both the regions near the 'virtual-interface'. The inhomogeneities thereby induce flow not only along the direction of vibration but also in normal direction ( direction), thus inducing rotational characteristics with respect to the vibration direction and hence perturbing this 'virtual-interface'. However, similar to the case of immiscible fluids where surface tension and viscous forces act as a means to stabilize these inhomogeneities, only viscous forces provide the necessary stabilizing action in the present case. With the growth in the thickness of the TBL, the vortex strength increases due to higher inertia associated with the thicker TBL, resulting in a stronger perturbation. When the perturbations are able to overcome the stabilizing action of the viscous forces, instabilities are observed as shown in Fig. 11. It has to be mentioned that even though the viscous effects may be very small, as mentioned in [23], their action is sufficient enough to stabilize the small perturbations induced by the velocity field. It is the formation of these vortices that are responsible for the parametric instabilities. The above explanation also suggests that the parametric instabilities are possible even between infinite parallel plates. In order to verify this explanation, the system was investigated with symmetric horizontal wall conditions imposed at walls and (infinite parallel plates-like conditions) for and , for which the results are shown in Fig. 12. The illustrations have been made only near the left wall ( ) for the sake of clarity.

While instabilities observed for symmetrical conditions substantiates our explanation, it is worth noticing that unlike wall conditions, the instabilities appear almost uniformly across the entire span of TBL for symmetrical conditions. This difference can be ascribed to the vortices formed near the corners which is explained as follows. The thermal quench on the vertical walls leads to the formation of the TBL while vibration causes the fluid to move from the TBL towards the bulk and vice-versa. Further, a no-slip condition at the horizontal wall results in the boundary layer velocity profile (Fig. 13(a), ), which distorts due to a heavier fluid from the TBL squeezing in and out of the corner with change in the direction of vibration. Subsequently, vortices are formed, as shown in Fig. 13(b) which act as a seed of perturbation. The rest of explanation follows the same suite as before wherein an instability is observed once the stabilizing effect of viscous forces are overcome. It has to be noted that the perturbation arising due to the corner vortices adds up to the primary mechanism of vortex formation. Therefore, the instability onsets appear earlier near the horizontal wall, propagating towards the middle of the cell (Fig. 10 and Fig. 12). It is to be mentioned that this kind of behaviour (instabilities originating at the boundaries and propagating towards the centre) is analogous to instabilities in Taylor Couette configurations infinite length cylinders or in Rayleigh-Bénard with hot or cold lateral walls.

Critical Amplitude for parametric instabilities

An investigation into the phenomenon leading to the onset of parametric instabilities has been described in the previous section. It can therefore be concluded that for a fixed proximity to the critical point and frequency, there exists a critical amplitude (which represents the critical acceleration) for which the perturbation will grow to overcome the stabilizing action of viscous forces. Similar to the Rayleigh-vibrational instabilities, the critical amplitude for the onset of these instabilities is evaluated for two different cases: (i) fixed with change in and , and (ii) fixed with change of and . The critical amplitude is found to decrease with increase infrequency, quench percentage and approaching the critical point. The results have been shown only for the second case for the sake of brevity in Fig. 14. While a higher entails a higher inertial force, a higher q implies a heavier fluid (along-with the larger density gradient)

and thus a larger difference in the associated momentum. Therefore, the threshold to overcome the stabilizing viscous forces is attained with lower amplitudes for both the aforementioned cases. Similarly, for the same T, the diverging behaviour of compressibility causes a higher difference in inertial forces on approaching the critical point and thus a lower critical amplitude as can be seen in Fig. 14.

Effect of cell size on the critical amplitude

The onset of parametric instabilities as previously described is primarily due to the perturbation in the velocity field near the transition region of the bulk and the TBL. The perturbation will be larger if higher momentum transfer occurs from the bulk fluid to the TBL and vice-versa. This implies that the change in cell dimensions along the direction of vibration can have an effect on the critical amplitude. The argument is supported from Fig. 15 which reports the critical amplitude for and for different cell sizes for and . It can be seen that with all the other parameters held constant, the critical amplitude decreases with the increase in h and can be approximated by a power law. This effect can be explained as follows. The induced perturbation will be of higher strength by virtue of higher momentum associated with higher volume (or mass) in a cell of larger dimensions thereby leading to a lower critical amplitude for the onset of instabilities.

Wavelength in parametric instabilities

The dispersion relation for immiscible fluids given by [START_REF] Kumar | [END_REF] is given by,

Here and correspond to the density of the two fluids while and represent surface tension and wavenumber, respectively. A similar analysis, as in [23], is presented here with higher quench percentage for a given proximity to the critical point ( ). In their work, wavelength was observed to decrease with with an exponent of based on a power law fit. A nearly similar exponent is observed in the current work for ( ) while a higher exponent is observed ( ) for ( value and , respectively) as shown in Fig. 16. This can be ascribed to a higher variation in the density due to higher quench percentage. It results in the dominance of non-linear effects, thereby leading to a higher exponent ), a faster decrease in wavelength than given by Eq. ( 8) which is obtained by using a linear stability analysis.

C. Stability Analysis

One of the primary motivations to analyse SCFs under thermo-vibrational instabilities has been to gain insights into the type of instabilities one may expect at different frequencies and amplitudes of vibration. While these instabilities may be used in certain processes to our advantage, for example mixing, in others, it may be desired to isolate the system to these instabilities. The authors in Ref. [23] presented a plot limited by the use of low q (10%, due to the use of a linear state equation). As the current model makes it possible to analyse the system with a higher quench percentage, a similar plot is presented in Fig. 17 (a-b). It is presented as a function of different q and for two different proximities to the critical point, and .

The plot illustrates that for amplitudes below the lower plane, the system will be stable with respect to both the described instabilities. Similarly, for amplitude bounded by the two planes, Rayleigh-vibrational instabilities will be first observed, while above the upper plane, both instabilities will occur simultaneously. Thus, it can be observed that higher amplitudes are required for the onset of parametric instabilities in both cases. The corresponding illustrations have been presented in Fig. 19 showing various instabilities depending on the operating parameters ( ) as marked in the figure itself. While it can be intuitively ascertained that it is easy to destabilize the fluid layers in parallel due to shear, it can be explained by analytical reasoning based on the mechanism causing both these instabilities. The Bernoulli-like pressure in Rayleigh-vibrational instabilities is observed to grow with the square of the velocity difference while in parametric, owing to the momentum transfer, it will follow a linear relation with velocity. Furthermore, since the momentum transfer occurs between two highly compressible fluids, some of the momentum is also expended in compressing the fluid whereas no such loss can be ascertained in case of Rayleigh-vibrational instabilities.

IV. Conclusion

The current work presents a 2D numerical investigation of thermo-vibrational instabilities in supercritical fluids under weightlessness, primarily Rayleigh-vibrational and parametric instabilities. These are observed when direction of vibration is normal and parallel to the temperature gradient, respectively. The primary feature of the current work pertains to investigation of these instabilities with higher quench percentages, as high as 50% and closer proximity to the critical point ( . This is facilitated by the use of a mathematical model that evaluates density directly from the mass conservation, incorporating the dependence of pressure on density and temperature directly into the momentum equation and thus is capable to take into account the non-linear variations of pressure with temperature and density. A comparison with experimental observations shows a close match demonstrating the strength of the model to investigate system with large property variations.

It is found that it is possible to define, for both the instabilities, a critical amplitude for their onset which decrease with an increase in the quench percentage and frequency of vibration.

The analysis of dynamic behaviour of wavelength in Rayleigh-vibrational configuration shows an interesting observation wherein an increase in wavelength at higher acceleration is observed irrespective of quench percentage. A new trend for Rayleigh-vibrational number covering a wider span in terms of proximity and quench temperatures is also observed. In case of parametric instabilities, it is found that the vibration critical amplitude depends on the cell size. While for low quench percentage, it is observed that the decrease in wavelength with acceleration nearly matches the trend as in the case of Faraday instabilities in immiscible fluids, a faster decreasing trend is observed at higher quench percentage which can be ascribed to dominance of non-linear effects at higher quench percentage. Finally, a stability plot highlighting critical regions in terms of thermo-vibrational parameters (quench percentage, frequency and critical amplitude) is presented wherein it is found that critical amplitude for onset of Rayleigh-vibrational instabilities is lower as compared to that of parametric instabilities.

Step 3: The pressure is updated using Eq. ( 7) utilising the velocity field obtained by solving Eq. ( 8).

Step 4: The updated velocity field is then used to implicitly evaluate the temperature field at by discretizing the energy equation Eq. (3) (in the absence of source term and viscous dissipation) as,

Step 5: The updated velocity field at is further used to evaluate the density at time step using the following relation (integrating the last part of Eq. ( 1)), (10) Step 6: The fields of the variables are then advected from their respective total derivatives (see Eq. ( 5)) through the TVD scheme. The updated values of temperature are then used to evaluate thermo-physical properties as described in Table I to be used in next iteration. The above process is repeated in time by setting the values at time to the values at time

Figure 1 .

 1 Figure 1. Schematic of the test case (square cavity of length).

Figure 2 (

 2 Figure2(a-b) shows the results obtained from our simulation and experimental observations[START_REF] Chatain | SBT-INAC[END_REF] for the parameters described in Fig.1. It can be observed that finger-like structures appear from the top wall ( ) in both the cases (numerical calculations (Fig.2(a) and experimental picture Fig.2(b)). More importantly, the number of fingers is also the same illustrating the capability and accuracy of the numerical model to capture the dynamics of highly compressible SCFs.

Figure 2 .

 2 Figure 2. Comparison between (a) numerical results and (b) experimental[START_REF] Chatain | SBT-INAC[END_REF] and for thermo-vibrational instabilities ( and ). There exists a difference in experimental and numerical conditions (refer text for explanation).

Figure 3 .

 3 Figure 3. Schematic illustration for mechanism leading to Rayleigh-vibrational instabilities.

Figure 4 .

 4 Figure 4. Critical amplitude ( ) for the onset of Rayleigh-vibrational instabilities as a function of frequency and distance from the critical point for two different quench temperatures, and . Distance in terms of proximity varies from to

Figure 5 .

 5 Figure 5. Comparison of wavelengths (average), experimental [21] and numerical, for different proximities to the critical point for same and . Proximities vary from to .

Figure 7 .

 7 Figure 7. Wavelength in Rayleigh-vibrational instabilities for different quench percentage as a function of acceleration reduced by earth acceleration for .

Fig. 8

 8 Fig. 8 which compares wavelengths for % and for different cell sizes ( and ) thereby substantiating the proposed explanation.

Figure 8 .

 8 Figure 8. Wavelength in Rayleigh-vibrational instabilities vs non-dimensional acceleration ( for for two different cell sizes ( and ).

Figure 10 .

 10 Figure 10. Parametric instabilities for one time-period of vibration for . Arrows represent the direction of cell movement at that time instant.

Figure 11 .

 11 Figure 11. Schematic illustration of the mechanism leading to parametric instabilities: (a) Formation of a thin TBL, (b) equivalent configuration representing parametric (Faraday) instability like configuration under an acceleration field.

Figure 12 .

 12 Figure 12. Parametric instabilities near left wall for with symmetric condition on the horizontal walls ( and ).

Figure 13 .

 13 Figure 13. Velocity vector near the corner ( ) with a wall condition on the top plate for illustrating (a) boundary layer velocity profile (b) formation of vortices (scale 1:8x10 5 cm/ms -1 ).

Figure 14 .

 14 Figure 14. Critical amplitude ( ) for the onset of parametric instabilities as a function of frequency distance from the critical point for two different quench temperatures, (for and ) and (for and ).

Figure 15 .

 15 Figure 15. Critical amplitude for parametric instabilities for cells with different dimensions for 2 proximities to the critical point, and for and .

Figure 16 .

 16 Figure 16. Wavelength vs reduced acceleration for with different quench percentages.

Figure 17 .

 17 Figure 17. Stability plot describing critical amplitude for onset of Rayleigh-vibrational and parametric instabilities as a function of quench percentage and frequency.

Figure 18 .

 18 Figure 18. Stability plot illustrating different instabilities based on their operating conditions for .

TABLE 1

 1

				: Thermo-physical properties of	with	[7,23].
	Property		Value
	Critical Temperature (T c ) [K]	33.19
	Critical density ( c ) [kg.m -3 ]	30.11
	Critical Pressure (P c ) [MPa]	1.315
	Isothermal Compressibility (	[ Pa -1 ]
	Thermal expansion at constant pressure	[ K -1 ]
	Specific heat at constant volume (	[ J.kg -1 ]
	Thermal conductivity [ [W.m -1 . K -1 ]
	Thermal diffusivity [	[m 2 .s -1 ]
	Kinematic viscosity [	[ m 2 .s -1 ]
	Speed of sound
	[	[m.s -1 ] (from Mayer Relation)

The increase in on approaching the critical point illustrates the same behaviour, a higher exponent ( ) when near and a lower ( ) when far from the critical point, respectively (exponents obtained by power law fit ~ 0.92-0.99). Lower value of exponents ( and when near and far, respectively) in the work of authors in Ref. [START_REF] Amiroudine | [END_REF] can be attributed to a lower quench percentage considered due to the assumption of a linear equation of state for density calculation. However, a higher quench percentage, as favoured by the proposed mathematical model, makes it possible to account for higher variations especially when approaching the critical point. As a result, it is reasonable to expect a faster increase in the critical Rayleigh vibrational number as described above.

Appendix

The Navier-Stokes equations presented in Sec. II are discretized using finite volume method on a staggered Cartesian grid. The general time-discretization algorithm can be described as follows. The initial conditions for the flow variables ( ) are given in the problem formulation.

Step 1: The momentum equation (Eq. ( 2)) is discretized with forward first order Euler in time.

The pressure reported here is described in detail in the next step.

(6)

Step 2: In order to evaluate the pressure field, Eq. ( 4) is integrated over the time step of simulation, , following which it can be written as, [START_REF] Zappoli | Heat Transfers and Related Effects in Supercritical Fluids[END_REF] It is worth mentioning here that in the above Eq. ( 7), we have simplified However, this simplification is not ascribed to the assumption that the divergence of the velocity field is independent of time. It is more of a numerical simplification, where for the time step , the integral can be simplified using several possible choices such as, , or using Simpsons rule etc. Since no difference in the results is obtained with either choice, we have used the aforesaid approximation. Thus, from Eq. ( 7), the expression for pressure at time step is directly incorporated into the momentum equation, Eq. ( 6)

following which it can be written as,

This highlights a very important step of the developed model wherein the dependence of pressure on density (through ) is directly incorporated in the momentum equation with the implicit contribution of the velocity field.


Dimitri Kalenitchenko

Nadine Le Bris

Erwan Peru

Pierre E Galand
email: pierre.galand@obs-banyuls.fr.

Ultra-rare marine microbes contribute to key sulfur related ecosystem functions

Keywords: rare biosphere, bacteria, functional redundancy, sulfide, diversity, colonization, succession, sulfur cycle

The description of a rare biosphere within microbial communities has created great interest because microbes play a fundamental role in the functioning of all ecosystems on earth.

Despite recent progress in understanding the ecology of the rare biosphere, the concept itself is still discussed and fundamental questions remain. Here, we target the seed bank compartment of the rare biosphere, assess the level of rarity at which microorganisms are still able to colonize an ecosystem and investigate whether rare species are functionally redundant.

Using an original experimental design where wood in aquaria was inoculated with increasingly diluted coastal seawater, we show that bacteria that represented as few as 0.00000002 % of the cells in the environment (or 1 cell in 10 L of seawater) were still able to grow and play key roles within the ecosystem. Our experiment further showed that some bacteria can be replaced by others that have the potential to fulfill the same metabolic tasks. This finding suggests some functional redundancy within bacterial species. However, when ultra-rare bacteria were progressively removed, productivity was reduced, and below a certain threshold some processes were lost, and the function of the ecosystem was altered. Overall the study shows that bacteria that are not detected by high-throughput sequencing approaches are nevertheless viable and able to colonize new ecosystems, suggesting the need to consider ultra-rare microbes in the marine environment.

Introduction

Microbial communities play a fundamental role in the functioning of all ecosystems on earth [START_REF] Falkowski | The microbial engines that drive Earth's biogeochemical cycles[END_REF][START_REF] Mcfall-Ngai | Animals in a bacterial world, a new imperative for the life sciences[END_REF]). In the sea, they mediate key biogeochemical cycles and are involved in nutrient cycling, primary production, organic matter mineralization and ultimately climate regulation [START_REF] Kirchman | Microbial ecology of the oceans[END_REF]). These processes are often conducted by a few dominant and active species that are present in the environment at a given time [START_REF] Pedrós-Alió | Marine microbial diversity: can it be determined[END_REF]. Such a feature is reflected by the representation of the distribution of microorganisms along a skewed rank-abundance curve that shows the presence within a community of a few dominant species and many less abundant organisms [START_REF] Curtis | Estimating prokaryotic diversity and its limits[END_REF]Pedrós-Alió 2012). This long tail of rare microbes contains most of the tremendous diversity of a microbial community [START_REF] Crespo | Probing the Rare Biosphere of the North-West Mediterranean Sea: An Experiment with High Sequencing Effort[END_REF].

This large number of rare species was coined the "rare biosphere" following the first application of high-throughput sequencing to describe marine microbial communities [START_REF] Sogin | Microbial diversity in the deep sea and the under explored "rare biosphere[END_REF]. The rare marine biosphere was first hypothesized to reflect the stochastic and potentially unlimited dispersal capacity of microbes in the ocean. Traces of these dispersed microorganisms would eventually be found everywhere. Furthermore, following Baas Becking's statement that "everything is everywhere, but the environment selects", these microbes would represent a seed bank containing organisms that can grow when the conditions become favorable [START_REF] Jones | Dormancy contributes to the maintenance of microbial diversity[END_REF][START_REF] Lennon | Microbial seed banks: the ecological and evolutionary implications of dormancy[END_REF][START_REF] Pedrós-Alió | Marine microbial diversity: can it be determined[END_REF]. However, it was shown that the rare biosphere represented a more complex picture. It has patterns of biogeography that suggests the occurrence of selection processes [START_REF] Galand | Ecology of the rare microbial biosphere of the Arctic Ocean[END_REF]. Furthermore, some rare microbes are active and at times are more active than the abundant members of the community [START_REF] Campbell | Activity of abundant and rare bacteria in a coastal ocean[END_REF][START_REF] Jones | Dormancy contributes to the maintenance of microbial diversity[END_REF], which indicates that the rare biosphere is not only composed of a seed bank of dormant microorganisms. It thus appears that there are large ecological differences between different compartments of the rare biosphere [START_REF] Alonso-Sáez | The hidden seasonality of the rare biosphere in coastal marine bacterioplankton[END_REF][START_REF] Hugoni | Structure of the rare archaeal biosphere and seasonal dynamics of active ecotypes in surface coastal waters[END_REF]Pedrós-Alió 2012). Despite recent progress in understanding the ecology of the rare biosphere, the concept itself is still discussed, and fundamental questions remain. For instance, some data suggest that some of the observed microbial diversity results from methodological artifacts [START_REF] Kunin | Wrinkles in the rare biosphere: pyrosequencing errors can lead to artificial inflation of diversity estimates[END_REF][START_REF] Lee | Groundtruthing next-gen sequencing for microbial ecology-biases and errors in community structure estimates from PCR amplicon pyrosequencing[END_REF][START_REF] Patin | Effects of OTU clustering and PCR artifacts on microbial diversity estimates[END_REF] or that the observed diversity does not represents viable microorganism but instead reflects free or dead DNA [START_REF] Carini | Relic DNA is abundant in soil and obscures estimates of soil microbial diversity[END_REF][START_REF] Lynch | Ecology and exploration of the rare biosphere[END_REF]. In addition, although sequencing now allows the in-depth probing of the richness of the rare biosphere [START_REF] Crespo | Probing the Rare Biosphere of the North-West Mediterranean Sea: An Experiment with High Sequencing Effort[END_REF], it was recently debated that there may not be as many rare microbes as originally thought [START_REF] Amann | Reply to "The Underestimation of Global Microbial Diversity[END_REF][START_REF] Amann | After all, only millions?[END_REF]Lennon & Locey 2016). However, there have been few if any convincing experiments designed to explore the limits of rarity in natural samples.

The existence of the rare biosphere also begs the question of why there are so many microbial species in the sea. High levels of diversity have been early explained by the presence in the environment of different taxa that are able to conduct the same metabolic processes. The paradigm of functional redundancy has long been assumed in microbial ecology [START_REF] Bell | The contribution of species richness and composition to bacterial services[END_REF][START_REF] Finlay | Microbial diversity and ecosystem function[END_REF], and the assumption is that a change in microbial community composition will not have consequences for microbial-mediated processes [START_REF] Allison | Resistance, resilience, and redundancy in microbial communities[END_REF]. The recent use of metagenomic profiles revealed high functional redundancy for marine microbes at global scale [START_REF] Sunagawa | Structure and function of the global ocean microbiome[END_REF]. Inversely, the fact that some bacterial communities that are distinct in composition show different functions [START_REF] Leff | Consistent responses of soil microbial communities to elevated nutrient inputs in grasslands across the globe[END_REF] indicates that the paradigm of redundancy does not always hold in natural microbial communities, as shown recently in soil ecosystems [START_REF] Fierer | Reconstructing the microbial diversity and function of pre-agricultural tallgrass prairie soils in the United States[END_REF]. In aquatic environments, recent findings showing intrapopulation complementary [START_REF] Garcia | Auxotrophy and intrapopulation complementary in the 'interactome'of a cultivated freshwater model community[END_REF] support the theory of a high level of functional complementary in marine microorganisms illustrated by reductive genomic evolution or genome streamlining [START_REF] Giovannoni | Implications of streamlining theory for microbial ecology[END_REF][START_REF] Morris | The Black Queen Hypothesis: evolution of dependencies through adaptive gene loss[END_REF].

Here, we focus on the seed bank compartment of the rare biosphere, which was conceptualized by [START_REF] Pedrós-Alió | Marine microbial diversity: can it be determined[END_REF], 2012) as rare taxa that are not growing but that become abundant when conditions become favorable, and investigate the extent of its diversity and viability. More precisely, the goal of this study was to determine a threshold of abundance at which rare organisms can still successfully colonize a complex substrate, to test whether the rare species are functionally redundant and to verify whether they can be detected in the environment. We earlier showed that wood incubated in seawater is a useful tool for testing hypothesis about the functional ecology of communities [START_REF] Kalenitchenko | Ecological succession leads to chemosynthesis in mats colonizing wood in sea water[END_REF]. Here, wood incubated in aquaria were inoculated with different dilutions of coastal seawater, and the growth of the bacterial communities was followed both within the wood and on the wood surface, with a special focus on the bacteria involved in the sulfur cycle. These keystone species are responsible for key ecosystem processes in the ocean. They are active during the degradation of large organic falls on the sea floor [START_REF] Bienhold | How Deep-Sea Wood Falls Sustain Chemosynthetic Life[END_REF][START_REF] Kalenitchenko | Temporal and spatial constraints on community assembly during microbial colonization of wood in seawater[END_REF][START_REF] Kalenitchenko | Bacteria alone establish the chemical basis of the wood-fall chemosynthetic ecosystem in the deep-sea[END_REF], the mineralization of organic matter in marine sediments [START_REF] Jørgensen | Mineralization of organic matter in the sea bed-the role of sulphate reduction[END_REF] and biomass production at hydrothermal vents or cold seeps [START_REF] Campbell | The versatile ε-proteobacteria: key players in sulphidic habitats[END_REF][START_REF] Martin | Hydrothermal vents and the origin of life[END_REF]. We chose to target these organisms because of their global importance and because their activity can be conveniently monitored.

Materials and methods

Experimental set up

Wood logs originating from a same pine tree (Pinus pinea) in the Banyuls sur Mer ' Biodiversarium' botanical garden were cut the day before the experiment started. The experimental design consisted of four separate 40-L aquaria that each contained four 15 cm in diameter and 10 cm in length, fresh (non sterile), wood logs [START_REF] Kalenitchenko | Ecological succession leads to chemosynthesis in mats colonizing wood in sea water[END_REF]. We did not want to take the risk of changing the integrity of the chemical composition of the wood by autoclave (possible impact on sugars). The aquaria were initially filled with increasing dilutions of coastal seawater from the SOLA station in Banyuls Bay sampled at 3m depth on 27 January 2015. Seawater filtered through a UF100LL filtration module (Polymem, Castanet-Tolosan, France) with a 0.01 µm pore size membrane was used for the dilutions. The first aquaria was started with 100% (1/1 treatment) off coastal unfiltered seawater, the second with 4 L of coastal water and 36 L of filtered water (1/10 treatment), the third with 0.4 L of coastal water and 39.6 L of filtered water (1/100 treatment) and the last with 100% filtered water (filtered treatment). Wood logs were immersed without water renewal for the first 7 days of the experiment after which, the aquaria water was renewed with piped in coastal seawater filtered through the 0.01 µm pore size filtration module (Polymem) at a flow rate that allowed at least 2 renewals per day. The experiment lasted for 28 days.

One log was removed and sampled from each aquarium after 7 days (7d), 14 days (14d), 21 days (21d) and 28 days (28d). At each sampling time, four replicate 1-cm long cores were extracted from each log using a 4.35-mm-wide increment core borer. Mats growing on the wood surface were sampled when present (21d and 28d) by scratching the entire wood surface with a scalpel blade.

DNA extraction and sequencing

The microbial mat samples were lysed and wood core samples were powdered as described earlier [START_REF] Kalenitchenko | Ecological succession leads to chemosynthesis in mats colonizing wood in sea water[END_REF][START_REF] Kalenitchenko | Temporal and spatial constraints on community assembly during microbial colonization of wood in seawater[END_REF]. The cell lysate was then transferred to the Maxwell ® 16 Blood DNA Purification kit cartridge and processed automatically with the Maxwell ® 16 automated extractor (Promega, Fitchburg, MA, USA).

DNA was also extracted from the original coastal seawater as described previously [START_REF] Galand | Microbial productivity is associated with phylogenetic distance in surface marine waters[END_REF]. See the supplementary material and methods for a full description of the procedure.

A portion of the 16S rRNA gene was amplified using bacteria specific primers, 28F

(5'-TTTGATCNTGGCTCAG-3') and 519R (5'-GTNTTACNGCGGCKGCTG-3'), and then sequenced by a commercial laboratory (Research and Testing Laboratory, Lubbock, TX) on an Illumina Miseq sequencer to produce 2x300bp long, paired-end sequences. The raw sequence data have been deposited in the NCBI Sequence Read Archive (accession no.

SRP099419 and BioProject accession no. PRJNA374511).

Sequence analysis

The 16S rRNA sequences were processed by following [START_REF] Galand | Microbial productivity is associated with phylogenetic distance in surface marine waters[END_REF]. In brief, sequences were paired, producing ca. 500 bp fragments, quality trimmed, and chimeras were removed. Sequences were grouped in operational taxonomic units (OTU) at 97% similarity using the Uclust algorithm [START_REF] Edgar | Search and clustering orders of magnitude faster than BLAST[END_REF]. The taxonomy of the most abundant sequence of each OTU was assigned using the SILVA SSU 123 database [START_REF] Pruesse | SILVA: a comprehensive online resource for quality checked and aligned ribosomal RNA sequence data compatible with ARB[END_REF]). All samples were resampled down to 5094 sequences per sample.

To identify the possible presence of rare species in seawater we used a dataset of sequences from the Banyuls Bay microbial observatory time series. Samples have been gathered twice a month from 2007 to 2014. DNA has been extracted and samples sequenced as described earlier [START_REF] Galand | Microbial productivity is associated with phylogenetic distance in surface marine waters[END_REF]. A total of 7,418,629 sequences were used to search for rare species in the time series. The occurrence of sequences that were not detected in the time series was calculated to be < 1 / 7,418,629, which is < 0.00001 %.

Bacterial diversity was estimated by calculating the Shannon diversity index (H') and the standardized effect size (SES) [START_REF] Kembel | Picante: R tools for integrating phylogenies and ecology[END_REF], which is a standardized measure of phylogenetic diversity. Phylogenetic diversity was computed using the Picante package [START_REF] Kembel | Picante: R tools for integrating phylogenies and ecology[END_REF] in R. To calculate SES, representative sequences from each OTU were aligned using MUSCLE [START_REF] Edgar | MUSCLE: a multiple sequence alignment method with reduced time and space complexity[END_REF], and the alignment was then cleaned to remove nonoverlapping sequence regions. A phylogenetic tree was constructed using FASTTREE [START_REF] Price | FastTree 2-approximately maximum-likelihood trees for large alignments[END_REF]. The observed phylogenetic diversity was compared to the average phylogenetic diversity in a randomly generated community (null model) and divided by the standard deviation of the phylogenetic distances in the null model [START_REF] Webb | Phylocom: software for the analysis of phylogenetic community structure and trait evolution[END_REF]). The null model randomizes community data matrixes with the independent swap algorithm to maintain the species occurrence frequency and sample species richness [START_REF] Kembel | Disentangling niche and neutral influences on community assembly: assessing the performance of community phylogenetic structure tests[END_REF]. Positive SES values indicate greater phylogenetic distance among co-occurring species than expected by chance, whereas negative values indicate small phylogenetic distance.

The Bray Curtis similarity index was computed to compare the community composition between samples with an MDS analysis. The effect of dilution and time factors on composition differences was tested with PERMANOVA in the program PAST [START_REF] Hammer | PAST: Paleontological statistics software package for education and data analysis[END_REF]. To identify OTUs or bacterial orders that had a significant difference in abundance between groups, we used a nested ANOVA with the tools described in [START_REF] Mcdonald | Handbook of Biological Statistics[END_REF].

Differences in diversity (Shannon) were tested with ANOVA. Two outlier samples (1/1: 14d-Replicate1, 1/10/ 21d-Replicate1) were removed from the analysis.

Flow cytometry and most probable number

Heterotrophic prokaryotic abundance in the aquaria water was measured by flow cytometry (Supplementary methods). We used a method that is commonly used in microbiology, called the most probable number method (MPN) [START_REF] Oblinger | Understanding and teaching the most probable number technique[END_REF], to estimate the number of cells belonging to the OTUs that we monitored. This method relies on dilutions and the observation of microbial growth to estimate the number of cells present in a starting solution. To do so, we counted the number of replicate wood samples in which we detected the OTUs of interest at the end of the experiment (28d). We then used an MPN table to estimate the number of cells in the original seawater sampled from Banyuls Bay. Their frequency was calculated by dividing the estimated number of cells by the total number of cell counted by flow cytometry.

Sulfide detection

Continuous monitoring of sulfide was performed using autonomous potentiometric sensors (NKE, Hennebont, France) equipped with lab made Ag/Ag 2 S electrodes (Le [START_REF] Bris | In situ sensors for benthic ecosystem studies[END_REF] to detect when sulfide started to diffuse at the surface of the wood logs. To measure the sulfide through the microbial mats, microsensor profiling was performed using amperometric microsensors (H2S100) and a picoammeter (PA2000) (UNISENSE, Aarhus, Denmark). Sulfide concentrations were profiled vertically, perpendicular to the surface of the wood, with a resolution of 250 µm at each sampling time using a micromanipulator. Calibrations were performed by standard additions of Na 2 S stock solution in seawater as described in [START_REF] Laurent | Sunken wood habitat for thiotrophic symbiosis in mangrove swamps[END_REF] [START_REF] Laurent | Sunken wood habitat for thiotrophic symbiosis in mangrove swamps[END_REF] for the potentiometric electrodes. The amperometric electrode was calibrated at pH of 6, 6.5, 7 and 7.5 using a Titrando pH controller (Metrohm, Herisau, Switzerland). The slope of the electrode response to H 2 S was thus confirmed to be pH independent and was calculated combining the whole calibration series. The total free sulfide concentration (i.e. both H 2 S and HS) is determined from the pH variability at the wood-water interface. To calculate the HS -fraction, we used a pKa 1 * of 6.7 at 13°C and salinity 37 [START_REF] Rickard | Chemistry of iron sulfides[END_REF].

The pH at the wood surface and wood water interface was measured with 1 mm resolution with a mini electrode (1.5 mm diameter) (Diamond General Co., Ann Arbor, USA) coupled with the sulfide microsensor. To prevent sulfide profiles from being disturbed by the larger pH electrode, the tips of both electrodes were 1 cm apart. Triplicates of the combined pH and H 2 S profiles were acquired to determine mean concentration of total sulfide and the corresponding standard deviation, which reflects the heterogeneity of the mat.

Results

Sulfide concentrations

We continuously measured sulfide concentrations inside the wood during the course of the experiment. In the undiluted treatment, sulfide was first detected inside the wood after 13 days of incubation. In the 1/10 dilution, sulfide was detected after 21 days, and in the 1/100 dilution, the electrode potential only showed a small shift from baseline (< 7 mV), which indicated that no significant amount of sulfide built up at the wood surface. In the aquaria with filtered water only, the sulfide electrode potential in the wood did not change over the experiment (Fig. 1a).

Surface mat sulfide profiles obtained with amperometric microsensors also reveal marked differences between the treatments (Fig. 1b). The mats were first visible at 21d, and the maximum sulfide concentration was higher in the undiluted experimental mats than in the 1/10 dilution mats. No mats were visible at the other dilutions. At 28d, the undiluted mat had thicker sulfide layer and higher maximum sulfide concentrations at the wood surface compared to those in the 1/10 dilution treatment (Fig. 1b). No sulfide was detected on the 1/100 and filtered treatments at 28d.

Community diversity

Community diversity measured as the Shannon index showed that at 7d, the communities from the undiluted treatment had significantly higher diversity (ANOVA, p<0.05), followed by the 1/10 dilution, the 1/100 and the filtered treatments (Fig. S1). At 14d, the undiluted, 1/10 and 1/100 samples had similar diversity, whereas the diversity of the filtered treatment community remained low. At 21d, the pattern of diversity did not change markedly, and at 28d, the diversity in the undiluted treatment decreased significantly.

For the phylogenetic diversity, the largest difference between samples was observed at 7d among diluted treatments. The 1/10 communities were the more phylogenetically clustered (lowest SES values), followed by the 1/100 and filtered communities (ANOVA, p<0.05). As time passed, communities became less phylogenetically clustered (increasing SES values), and there were no significant differences between treatments (Fig. S2).

Bacterial community composition inside the wood

Community composition between samples was compared by computing the Bray Curtis dissimilarity index. For undiluted treatment (1/1) at 7d, the bacterial communities were very different from those of the 7d communities in the diluted treatments. Dilution had a stronger effect on community composition than incubation time had (Table S1 andS2). The community composition changed among 7d, 14d and 21d. However, the undiluted 21d and 28d communities were very similar to each other (Fig. 2).

For the 1/10, 1/100 and filtered treatments, the 7d communities were more similar to each other than to the communities from the undiluted treatment, as shown by their close proximity on the MDS plot (Fig. 2). After 7d, the 1/10 communities became more similar to the 1/1 communities, whereas the 1/100 and filtered communities became more similar to each other with time (Fig. 2). In all dilution treatments, the communities changed with time and continued changing after 21d. The diluted communities changed more than the undiluted ones did, as shown by larger distances observed between samples on the plot.

Composition at order level

At the order level, in the diluted treatments, after 7 days (7d), there were significantly fewer Campylobacterales and Flavobacteriales compared to the undiluted bacterial communities (1/1). In the 1/10 dilution, the proportion of Oceanospirillales and Alteromonadales was higher than that in the undiluted treatment. In the 1/100 and filtered treatments, the proportion of Vibrionales was higher (Fig. 3).

After 14 days (14d), the samples from the undiluted treatment (1/1) maintained the same groups as those present at 7 days but the proportion of Aeromonadales and Alteromonadales decreased. The proportion of Campylobacterales increased significantly in the 1/10 dilution. Rhodospirillales and Flavobacteriales sequences strongly increased in the 1/100 and filtered treatments (Fig. 3).

After 21 days (21d), the proportion of Aeromonadales and Alteromonadales continued to decrease in the undiluted treatment (1/1), and 2 new groups increased (Desulfovibrionales and Bacteroidales). Desulfovibrionales and Bacteroidales were also detected in the 1/10 dilution but at lower abundance. There were no significant changes otherwise for the 1/100 and filtered treatments (Fig. 3).

After 28 days (28d), the proportion of Aeromonadales and Alteromonadales kept decreasing in the undiluted treatment. In the 1/10 dilution, Desulfovibrionales and Bacteroidales sequences increased. In the 1/100 dilution, Bacteroidales became more abundant (Fig. 3) but more variable between replicates in the samples from the filtered treatment (Fig. S3).

Dynamics at the OTU level

We identified OTUs representing organisms known to be involved in sulfur cycling in chemosynthetic ecosystems. For sulfate reducers, we identified two OTUs that grew well in the undiluted treatment but not, or poorly, in the diluted treatments (Fig. 4). These two OTUs were affiliated with Desulfovibrio piezophilus (OTU10 and OTU58, with 100% and 96 % identity, respectively, over 442 bases). OTU10 was first detected at 21d in the undiluted treatment and at 28d in the 1/10 dilution. It was only present at trace amounts in the 1/100 and filtered water treatments (Fig. 4a). OTU58 was also detected in the samples at 21d in the undiluted treatment but was not present in the 1/10 diluted treatment nor in the 1/100 or filtered treatments (Fig. 4b).

We also identified potential sulfide oxidizers OTUs that grew better in the undiluted treatment than in the diluted waters (Fig. S4). These OTUs were similar to Arcobacter bivalviorum (OTU6, 100% identity) and Arcobacter sp. (OTU15, 94% identity). OTU6 sequences were detected at 7d in the undiluted treatment. In the 1/10 dilution, sequences appeared mostly at 28d and were less abundant (Fig. S4a). OTU15 was only present in the undiluted treatment and was detected at 21d (Fig. S4b). Some of the OTUs were more abundant in samples from the diluted compared to the undiluted treatment. OTU43 (100% identity over 452 bases to Marinomonas foliarum) was more abundant at 7d in the undiluted and 1/10 dilution treatments but was overall more abundant in the 1/100 dilution, especially from 14d (Fig. S5a). OTU19 (100% identity over 452 bases to Vibrio oceanisediminis) was rare in the undiluted treatment, more abundant and present at all times tested in the 1/10 dilution and most abundant in the 1/100 dilution, especially at 7d (Fig. S5b).

Proportion of sequences and cell counts

OTU10, OTU58, OTU6, OTU15, OTU19 and OTU43 sequences were not detected in the sequences obtained from the original coastal seawater sample from Banyuls Bay. Because we analyzed 23,743 sequences of bacteria from this inoculum water, the frequency of these OTUs represented <0.004 % of the sequences. We further verified whether the sequences were present in a database of 7,418,629 sequences sampled at Banyuls Bay over a period of 9 years. OTU10, OTU58, OTU6, OTU15, OTU19 and OTU43 were never detected, and their occurrence was thus calculated to be < 0.00001 %.

Our flow cytometry counts validated the serial dilution of the Banyuls Bay seawater for the experiment (Fig. S6). We used the most probable number method (MPN) to estimate the number of cells belonging to the OTUs that we monitored (Table S3). Our MPN estimates showed that some OTUs had occurrences as low as 1 cell in 10 L of seawater (OTU15). That small proportion represents 0.00000002 % of the cells present in the aquaria.

OTUs in the microbial mats

We identified OTUs affiliated with Arcobacter sp. in the mats growing on the wood logs (Fig. S7). Mats were visible starting at 21d. In the undiluted treatment, among the sequences that were identified as Arcobacter sp., the OTU Arcobacter1 dominated, followed by the OTU Arcobacter6 and a few sequences belonging to the OTU Arcobacter3 (Fig. 5). In the 1/10 dilution, the Arcobacter sequences belonged mainly to Arcobacter3. In the 1/100 dilution, very few Arcobacter sequences were present. They were represented by Arcobacter31 and Arcobacter3. In the samples from the filtered treatment, there were also few Arcobacter sequences at 21d and 28d; half of those identified belonged to OTU1, and half belonged to OTU3. Arcobacter1 was similar to the OTU6 found inside the wood. The other 3 main Arcobacter OTUs were not detected inside the wood (Fig. 5).

Discussion

Our experiment demonstrated that seawater contains bacteria that are extremely rare but still have the potential to grow and multiply rapidly when they encounter a suitable niche. Our work suggests the existence of ultra-rare bacteria, microbes that are never detected by high throughput sequencing approaches but that are nevertheless viable and able to colonize new ecosystems with the potential to fulfill an important function in the marine ecosystem.

The presence of these ultra-rare microbes can, to date, only be revealed through culturing or enrichment approaches. The organisms that grew in our experimental wood were not detected by sequencing the inoculum water originating from Banyuls Bay. Their occurrence in the inoculum in terms of sequence abundance was thus below 0.004%. These ultra-rare microbes were not found either among sequences from Banyuls Bay collected over 8 years. By taking into account the total number of sequences from this long time series, these ultra-rare microbes would represent < 0.00001 % of the naturally occurring community.

In terms of cell numbers, the flow cytometry counts and the most probable number approach showed that, theoretically, the frequency of ultra-rare microbes was as low as 1 cell in 10 L of seawater or as little as 0.00000002 % of the cells in the aquaria. They were not able to grow below that threshold. Together, our count and sequencing data show a level of rarity that is several orders of magnitude lower than thresholds used earlier to define the rare biosphere in sequencing data: 0.1% (Pedrós-Alió 2012) or 0.01% [START_REF] Galand | Ecology of the rare microbial biosphere of the Arctic Ocean[END_REF]. For the first time, we also provide an estimation of rarity in terms of cell numbers. Theoretically, if PCR or sequencing bias were not considered, one would thus need at least 8,038,282,890 sequences (the number of bacteria present in average in 10 L of Banyuls Bay seawater) to be able to detect the ultra-rare Arcobacter cell (Fig. 6). Thus, current sequencing techniques may not provide exhaustive maps of the microbial diversity even with one million final reads, a number suggested recently to be required to yield quasi-exhaustive mapping of marine bacterial diversity [START_REF] Crespo | Probing the Rare Biosphere of the North-West Mediterranean Sea: An Experiment with High Sequencing Effort[END_REF].

These ultra-rare microbes could have been missed by our sequencing approach if they had been present in the water as resting spores. Spore forming microbes are common [START_REF] Lennon | Microbial seed banks: the ecological and evolutionary implications of dormancy[END_REF] and their DNA sometimes difficult to extract. Among the sulfate-reducing bacteria, the Firmicutes form endospores that can be dispersed through the global ocean [START_REF] Hubert | A constant flux of diverse thermophilic bacteria into the cold Arctic seabed[END_REF]. However, among the bacteria that we identified, Arcobacter and Desulfovibrio are considered non-spore forming bacteria [START_REF] Vandamme | Arcobacter. In: Bergey's Manual of Systematics of Archaea and Bacteria[END_REF] and should be detected by PCR based diversity surveys. The growth of these organisms in our experiments suggests that the ultra-rare biosphere contains living non-dormant bacteria, and such viability shows that they do not represent taphonomic DNA originating from decaying organisms, or extracellular DNA [START_REF] Carini | Relic DNA is abundant in soil and obscures estimates of soil microbial diversity[END_REF][START_REF] Lynch | Ecology and exploration of the rare biosphere[END_REF]. In the context of the ongoing debate around the presence of a "inflated biosphere" originating from PCR or sequencing artifacts [START_REF] Kunin | Wrinkles in the rare biosphere: pyrosequencing errors can lead to artificial inflation of diversity estimates[END_REF][START_REF] Lee | Groundtruthing next-gen sequencing for microbial ecology-biases and errors in community structure estimates from PCR amplicon pyrosequencing[END_REF][START_REF] Patin | Effects of OTU clustering and PCR artifacts on microbial diversity estimates[END_REF], our findings argue for the true existence of the rare biosphere.

In our study, we focused on microorganisms involved in the sulfur cycle. For instance, sulfate reducing bacteria use the sulfate present in seawater as an electron acceptor to obtain energy and release hydrogen sulfide. By measuring the concentration of sulfide, the accumulation rates could be used to indirectly assess microbial activity and thus monitor this key ecosystem process occurring in the wood and wood surface. Our data demonstrate that after diluting the inoculum 10 times, the ecosystem processes were maintained. At a 100 times dilution, however, sulfide was no longer detected. Thus, when ultra-rare microbes were progressively removed, ecosystem processes were maintained but only until a certain threshold of rarity. Below that threshold some processes were lost and ecosystem functioning was impaired. Interestingly, even though sulfide was still detected after the first dilution, it appeared later and the concentration plateau was not reached, with a slower buildup of sulfide at the interface. It might be that at 1/10 dilution, the activity started later because the community had to restore a critical biomass before ecosystem processes could be detected.

Our data suggest, despite the fact that ecosystem functioning was maintained, that activity was reduced when the original community was diluted.

Dilution had the effect of reducing the community diversity and the phylogenetic diversity at the beginning of the experiment. Dilution certainly removed some rare species and probably decreased the abundance of individuals within more abundant species. It affected the composition of the community used as inoculum, which in turn affected the composition of the communities colonizing the wood. As a result, the composition of the wood communities in the diluted treatments differed from those observed in the wood from the undiluted treatment. For instance, one sulfate reducing bacteria (Desulfovibrio,OTU 58) and a potential sulfide oxidizer, Arcobacter (OTU 15), were never detected in the diluted treatments. Interestingly, community diversity later increased with time and the functioning of the community was maintained, as revealed by the production of sulfide. It clearly shows that some microorganisms from the original community were replaced by others with the potential to fulfill the same metabolic tasks. Functional redundancy can be difficult to demonstrate because it requires knowledge about the microbial populations that perform a specific process [START_REF] Allison | Resistance, resilience, and redundancy in microbial communities[END_REF]. Here, a change in microbial community composition did not have any consequences for the microbial-mediated production of sulfide. It is an indication of the functional redundancy within the bacterial species that are involved in the degradation of large organic falls in the sea. Metagenomic data from planktonic marine bacteria recently suggested high functional redundancy at global scale [START_REF] Sunagawa | Structure and function of the global ocean microbiome[END_REF]. However, the recent report that microorganisms in soils did not show a high degree of functional redundancy [START_REF] Fierer | Reconstructing the microbial diversity and function of pre-agricultural tallgrass prairie soils in the United States[END_REF]) could suggest that redundancy may vary depending on ecosystems or, more likely, that the scale of the study is important. It has been emphasized that redundancy has to be tested under common environmental conditions [START_REF] Bradford | The biogeography of microbial communities and ecosystem processes: implications for soil and ecosystem models[END_REF].

In our study, a change in community composition, concomitant with the maintenance of a function, was also clearly visible in the mats growing on the wood. Our results show that at each level of dilution different Arcobacter bacterium were found in the mat. Again, it points toward a certain level of functional redundancy within the genera. In addition, these differences at the species level indicate that when some rare bacteria are lost or reduced in abundance by dilution, other rare microbes can colonize the substrate and use the available niche. Interestingly, some microorganisms that grew in the wood in the diluted treatments were not detected in the woods from the undiluted treatment. For example, Marinomonas (OTU43) and Vibrio oceanisediminis (OTU19) were less abundant or not detected in the undiluted treatment. Dilution probably liberated a niche for these microorganisms that otherwise would have been outcompeted. It should also be noted that a few Arcobacter were present in the lowest dilutions after 21d, even though sulfide was not detected, which possibly reflects the complete consumption of the sulfide produced and that wood could have produced sulfide if the experiment had been longer.

In conclusion, we demonstrate the presence in the sea of very rare but viable bacteria that are key to important ecosystem processes, such as organic matter degradation. These functioning bacteria occurred at concentrations as low as 1 cell per 10 L of water and thus would not be detected by current amplicon based environmental diversity surveys. In the debate on the extent of microbial diversity, we found that the bacterial community richness remains under estimated [START_REF] Crespo | Probing the Rare Biosphere of the North-West Mediterranean Sea: An Experiment with High Sequencing Effort[END_REF]Locey & Lennon 2016). The rare biosphere described to date only represents the emerged part of an iceberg floating in a sea of ultra-rare microbes, which represent an underappreciated source of hidden diversity.

  environment and global change'. We are thankful to Connie Lovejoy for helpful advices and comments on the manuscript. Author contributions. P.E.G. and D.K. designed research, D.K, E.P., N.L.B. and P.E.G. performed research, P.E.G contributed new reagents/analytic tools, D.K, N.L.B. and P.E.G. analyzed data, D.K, E.P., N.L.B. and P.E.G. wrote the paper.

Figure legends Figure 1 .

 legends1 Figure legends

Figure 2 .

 2 Figure 2. Trajectories of the bacterial communities. The similarity between bacterial

Figure 3 .

 3 Figure 3. Proportions of sequences at the order level detected inside woods incubated in

Figure 4 .

 4 Figure 4. Abundance of sequences belonging to two sulfate reducing bacteria identified as

Figure 5 .

 5 Figure 5. Proportion of the 4 most abundant Arcobacter OTUs in the mats colonizing the

  Fig.2

Fig. 4

 4 Fig. 4

Acknowledgment. The work of PEG was supported by the Agence Nationale de la Recherche (ANR) through the projects EUREKA (ANR-14-CE02-0004-01). We acknowledge the support of Fondation Total to the UPMC 'chair biodiversity, extreme marine

Data Accessibility. The raw sequence data have been deposited in the NCBI Sequence Read Archive (accession no. SRP099419 and BioProject accession no. PRJNA374511).