Simon Boivinet

Alain Pellegrina
email: alain.pellegrina@fr.thalesgroup.com

Lucas Ranc

Thomas Morbieu

Sébastien Vidal

Jean-Paul Yehouessi

Philippe Morin

Hugo Lecommandoux

Kevin Robin

Cyril Vinçont

delivered by a Ti:Sa amplifier system seeded with a frequency-doubled fiber laser

severely affected or prevented by a poor pulse contrast. Indeed, it has been shown that it can lead to a deformation and preionization of the target [START_REF] Lundh | Influence of shock waves on laser-driven proton acceleration[END_REF][START_REF] Zeil | The scaling of proton energies in ultrashort pulse laser plasma acceleration[END_REF]. A high contrast is also necessary when the laser pulse is interacting with a gaseous target to avoid uncontrolled plasma evolution due to pre-ionization [START_REF] Sarkisov | Observation of the plasma channel dynamics and Coulomb explosion in the interaction of a high-intensity laser pulse with a He gas jet[END_REF].

Given their characteristics, lasers based on titanium sapphire (Ti:Sa) crystal are exceptional candidates for high-intensity laser chains. Indeed, their large emission cross-section bandwidth and high optical gain allow us to generate ultrashort pulses and amplify them via multi-pass designs. Furthermore, the mature industrial process of large-aperture crystals enables them to reach very high pulse energy. Thanks to these advantages and the technical progress made over the last decade on Ti:Sa-based laser chains [START_REF] Lureau | 10 PetaWatt laser system for extreme light physics[END_REF][START_REF] Matras | First operation above PetaWatt with sub-25 fs pulses[END_REF], 10 PW peak power has been demonstrated [START_REF] Lureau | 10 PetaWatt laser system for extreme light physics[END_REF]. Generating sub-35 fs pulses and amplifying them up to a few joules is routinely done by several Ti:Sa laser manufacturers, and these pulse parameters are now accessible for all scientific facilities. Nevertheless, due to its lack of compactness and high cost, the technology faces issues entering the industrial market. With this in mind, a frequency-doubled femtosecond erbium-fiber laser had been proposed by Herda and Zach as a competitive alternative to the Ti:Sa oscillator [START_REF] Herda | Generation of 32-fs pulses at 780 nm by frequency doubling the solitonically-compressed output of an Erbium-doped fiber-laser system[END_REF]. While the

INTRODUCTION

Electron and ion sources constitute invaluable tools in numerous scientific fields, including medicine [START_REF] Pełka | Applications of free electron lasers in biology and medicine[END_REF], chemistry [START_REF] Möller | X-ray photon correlation spectroscopy of protein dynamics at nearly diffraction-limited storage rings[END_REF], and non-invasive inspection [START_REF] Behrens | Few-femtosecond time-resolved measurements of X-ray free-electron lasers[END_REF]. The free-electron laser (FEL) is one of the well-known electron sources due to its very high versatility in term of wavelength. Indeed, it can cover from microwave to x-rays. However, facilities hosting a FEL have a kilometer scale due the requirement of an electron accelerator usually ensured by synchrotrons. The most promising alternative to well-established electron acceleration as well as electron sources is laser-driven plasma on gas or solid targets. The laser creates and resonantly controls plasma, trapping electrons which are accelerated and simultaneously gain in energy [START_REF] Couprie | Towards compact free electron-laser based on laser plasma accelerators[END_REF][START_REF] Faure | Concept of a laser-plasma-based electron source for sub-10-fs electron diffraction[END_REF]. With this method, the size of the electron and ion sources and accelerator may be shrunk and can be less expensive.

To drive plasmas with the right parameters, the required laser should deliver pulses with duration below 35 fs and peak power of at least few tens of terawatts [START_REF] André | Control of laser plasma accelerated electrons for light sources[END_REF]. However, in the field of physics, these two pulse parameters are not the unique criteria. The pulse contrast is also a crucial parameter; it describes how fast the intensity temporally rises and the level of intensity before the pulse. Particle acceleration from a solid target can be concept is known, to our knowledge, no experimental demonstration has been reported for sub-70 fs pulses so far. This may be because all the solutions based on this architecture require free-space elements [START_REF] Herda | Generation of 32-fs pulses at 780 nm by frequency doubling the solitonically-compressed output of an Erbium-doped fiber-laser system[END_REF], deliver too-low pulse energy [START_REF] Sotor | 24 fs and 3 nJ pulse generation from a simple, all polarization maintaining Er-doped fiber laser[END_REF], or are not designed with PM fiber, leading to frequency-doubling instability [START_REF] Nicholson | High power, single mode, all-fiber source of femtosecond pulses at 1550 nm and its use in supercontinuum generation[END_REF]. To fill the gap, we have developed a new architecture of frequency-doubled all-PM fiber laser delivering 35 fs pulses around 800 nm with an energy of 3.5 nJ [START_REF] Boivinet | Sub-50 fs 3.5 nJ pulses at 792 nm generated by frequency doubling of an all-PM fiber laser for Ti:sapphire injection[END_REF]. However, the proposed design was complex and the use of three amplifier stages did not make it cost-effective enough. Therefore, we recently proposed an original and simpler design delivering pulses centered at 1595 nm with an energy of 30 nJ and a 35 fs duration [START_REF] Boivinet | 1.1 W all-PM fiber laser at 1600 nm delivering 35 fs pulses with 30 nJ energy[END_REF]. We will briefly describe in the following sections the frequency-doubling stage of this latest architecture.

In this paper, we propose a fully comparative experiment for seeding multi-terawatt (TW) Ti:Sa laser chains using a standard 15 fs Ti:Sa oscillator or our 35 fs long frequency-doubled fiber oscillator. To well compare the impact of the seeder on the output parameters, the amplifier chain design and parameters (such as pump power, number pass in regenerative amplifier, or beam diameters) have been kept identical. This test demonstrates the interchangeability of the two oscillators in a double chirped pulse amplification (CPA) Ti:Sa amplifier system, delivering 30 TW even if the two oscillators deliver different pulse duration, energy, and spectral width. To our knowledge, with pulse duration of 33 fs, this is the first demonstration of a 30 TW class Ti:Sa laser injected by a sub-40 fs frequency-doubled fiber oscillator.

FREQUENCY-DOUBLED FIBER LASER

In this Section, we report on the laser architecture of the frequency-doubled fiber oscillator used in the comparative study.

This laser is nearly similar to the one that we recently reported [START_REF] Boivinet | 1.1 W all-PM fiber laser at 1600 nm delivering 35 fs pulses with 30 nJ energy[END_REF]. It is a master oscillator power amplifier (MOPA) design made with only commercially available standard PM fibers (see Fig. 1). The oscillator seeding the amplification chain is a mode-locked laser based on a semiconductor saturable absorber mirror (SESAM) and operating in the solitonic regime. It emits 420 fs long pulses with an energy of 27 pJ at the repetition rate of 40 MHz. At the output of the oscillator, 3 m of dispersioncompensating fiber (DCF) are spliced. Thanks to the normal group velocity dispersion (GVD) of the DCF, the pulses are positively chirped during the propagation. The pulse duration is then 1 ps at the output of the fiber. The nonlinear effects, as selfphase modulation (SPM) along this fiber, broaden the spectrum up to 9 nm. This stretching stage allows us to avoid one normal GVD amplification stage compared to the reported laser in our previous work [START_REF] Boivinet | Sub-50 fs 3.5 nJ pulses at 792 nm generated by frequency doubling of an all-PM fiber laser for Ti:sapphire injection[END_REF]. The pulses are then amplified through an erbium-doped fiber amplifier (EDFA), which is a backward core-pumped amplifier made with 3 m of doped fiber exhibiting a normal GVD. This amplifier, operating in the parabolic regime, broadens the optical spectrum up to 16 nm and shapes the pulse to seed the last amplifier with the right parameters. This last is based on a PM large mode area (LMA) Er/Yb doped double-clad fiber with anomalous GVD and exhibiting a mode field diameter (MFD) of 20 µm; it is 1.5 m long. While the pulses are amplified, the interplay between nonlinear effect and anomalous GVD lead to a nonlinear compression of the pulses. Due to the large mode field diameter, the energy of the highorder soliton may be higher than standard fiber. The amplified and compressed pulses are finally focused with two lenses into a periodically poled lithium niobate (PPLN) crystal to frequencydouble them by second-harmonic generation (SHG). The crystal is inserted in an oven to ensure the temperature stability and temperature-induced phase-matching between the pump and the frequency-doubled signal. The beam diameter is kept larger than 80 µm in order to avoid any intensity-induced damage (beyond 60 GW/cm 2 ). The large spot size and the large size of the clear aperture of the grating structure in the PPLN (1 × 1 mm 2 ) lead to large tolerance for the alignment of the SHG stage.

In our previous work [START_REF] Boivinet | 1.1 W all-PM fiber laser at 1600 nm delivering 35 fs pulses with 30 nJ energy[END_REF], the pulses present large pedestal and satellite pulses due to nonlinear phenomena occurring along the fiber. However, the initial temporal contrast is crucial for the temporal contrast of the Ti:Sa amplifier chain. Keeping this in mind, the pump power of both fiber amplifiers is judiciously controlled to optimize the temporal shape minimizing the pedestal. The resulting pulse energy is only 10 nJ, and the pulses are 39 fs long [see Fig. 2(a)]. The optical spectrum is centered around 1595 nm.

At the output of the SHG stage, the signal average power is 100 mW, corresponding to a pulse energy of 2.5 nJ and a conversion efficiency greater than 25%. The optical spectrum exhibits a large FWHM of 28.8 nm centered at 798 nm [see Fig. 3(a)]. The pulses are linearly chirped with a duration of around 79 fs [see blue curve in Fig. 3(b)]. This chirp is induced by the chromatic dispersion of the optics, as lenses, used to collimate the frequency-doubled signal or the PPLN crystal (having a GVD around 300 fs 2 /mm). However, they are compressible down to 33 fs via paired SF10-prism compressors [see red curve in Fig. 3(b)]. The compressed pulses are nearly Fourier transform-limited because the autocorrelation trace of the Fourier transform of the spectrum, assuming a null spectral phase [see black curve in Fig. 3(b)], is almost overlapping the experimental autocorrelation trace. The trace has small femtosecond pedestal arising from the oscillating spectral shape. We assume this is driven by the shape of the optical spectrum. Indeed, the autocorrelation trace of the Fourier transform of the spectrum also has some pedestals. We have optimized the laser parameters to reach the highest pulse energy and the shortest pulse duration, and to minimize the pedestal.

We have investigated the stability of the pulse durations of the compressed pulse and the average power simultaneously (see Fig. 4). To do this, we have split the signal in two via a non-polarization beam-splitter with a ratio of 10/90. The two parameters have been monitored over 4 h. The average power has a root mean square (RMS) below 0.9%, and the fluctuation of pulse duration is +/-1.2 fs RMS. These are the same magnitude orders to the stability of Ti:Sa oscillator. It should be noted that we have also proved experimentally in Section 3 that the stability of the amplifier remains the same.

We believe that the interplay between the fiber laser architecture, the limited number of free space optics (only four bulk elements) limiting risk of misalignment, and the optical design features such as tolerances (large clear aperture of PPLN crystal compared to input beam diameter) may help to make the laser robust and probably stable over the long term. These features may improve the reliability of the overall system and reduce the maintenance and service. This maintenance time is also reduced considering that the fiber oscillator does not require any water cooling system (as such system needs to be periodically purged and its filters need to be changed).

It should be noted that the pulse compressor is not used in the rest of the comparison experiment. Indeed, the tool compressor has been set to test pulse compression at oscillator output, but is not yet integrated in the oscillator box. However, the compressor of the Ti:Sa laser chain can be optimized to compensate for the part of the GVD generated by the oscillator.

COMPARATIVE STUDY OF THE AMPLIFICATION OF Ti:Sa AND FIBER OSCILLATORS

In this Section, we compare the results obtained at the output of Ti:Sa amplifier chain when a standard seeder (a Ti:Sa oscillator) is interchanged with a frequency-doubled fiber oscillator.

To study only the impact of the seeder change, all the other parameters should remain exactly the same (only swap of the oscillators).

Our study has been performed on a standard QUARK 30 TW laser system from Thales. This system is based on a double CPA architecture using a cross-polarization wave (XPW) filter to improve picosecond contrast, as presented in Fig. 5. Advantageously, XPW nonlinear effect [START_REF] Jullien | 10-10 temporal contrast for femtosecond ultraintense lasers by cross-polarized wave generation[END_REF] broadens the spectrum to reach pulse durations shorter than 35 fs at the end of the amplifier chain.

The first stage of our system is the pulse generation ensured by a femtosecond mode-locked oscillator. For the study, we used a Gecco Ti:Sa oscillator from Laser Quantum (hereafter called Ti:Sa oscillator), or a frequency-doubled fiber laser codeveloped between ALPhANOV and Thales (hereafter called fiber oscillator). The Ti:Sa oscillator delivers pulses at the repetition rate of 80 MHz with a duration compressible down to 15 fs and an energy of 7.5 nJ. Its spectral full width at half maximum (FWHM), recorded with an USB 2000+ spectrometer from Ocean Optics (with a spectral resolution of 0.1 nm), is 103 nm (see blue optical spectrum in Fig. 6). The performance of the fiber oscillator is discussed in the previous part. It should be noted that the laser parameters are slightly different from the ones reported previously. We have lightly adjusted the pump power of the fiber oscillator to reach the largest optical spectrum at the output of the XPW stage. The resulting pulse duration is now 35 fs, but the pulse energy is conserved. The shape of the spectrum has slightly changed (see red curve in Fig. 6), but the FWHM is still 28 nm, almost four times narrower than that delivered by the Ti:Sa oscillator (see Fig. 6). The delivered pulses are linearly chirped at the output of the laser and exhibit a duration of around 79 fs. This chirp is induced by the chromatic dispersion of the optics (as lenses to collimate the frequency-doubled signal). However, we can compress them down to 35 fs. The compressed pulses have a small femtosecond pedestal arising from the oscillating spectral shape. In this study, we do not compress them because it is not required to seed the fs laser chain. It should be mentioned that the fiber oscillator is almost four times smaller, in terms of footprint on the optical breadboard, than the Ti:Sa oscillator (a reduced footprint of 30 × 15 cm 2 for the optical head instead of 65 × 28.5 cm 2 ), and it does not require any water cooling. These two features are for sure very attractive arguments for microscopy applications, but this is also not negligible for the Ti:Sa amplifier. The overall footprint of the QUARK system can be reduced by at least 3.5%. This is for sure not a drastic improvement but still a first step to shrink a bulky system.

The first CPA is composed of an Offner stretcher, a regenerative cavity pumped by a Flash Pump Solid State (FPSS) laser emitting at 532 nm, and a compressor in a Treacy configuration. The spatial beam profile is Gaussian thanks to the regenerative cavity. The amplifier brings the pulse energy from few nanojoules to the millijoule level. This 60 dB gain leads to a spectral narrowing of the seeded pulses and defines the amplification bandwidth (around 30 nm). Therefore, the spectrum of the amplified pulses for the Ti:Sa oscillator is shaped by the amplifier and acquires a Gaussian shape with a bandwidth of 30 nm. The pulses are then only compressible down to 35 fs, limited by the amplification bandwidth of the regenerative cavity. The spectrum of the fiber oscillator almost keeps its shape, but it also experiences a narrowing down to 20 nm. Its compressed pulse duration is increased up to 45 fs.

The compressed pulse is then injected in a two BaF 2 crystal configuration XPW filter [START_REF]High contrast non-linear femtosecond pulse filter[END_REF][START_REF] Jullien | Highly-efficient nonlinear filter for femtosecond pulse contrast enhancement and pulse shortening[END_REF] operating under a lab environment, ensuring reliability and robustness compared to a single-crystal setup. Contrast is improved by 3 orders of magnitude, which is the extinction ratio of the polarizer cube used for the setup. In addition, the spectrum is broadened by a factor of √ 3 and the phase exiting XPW is flat [START_REF] Ramirez | Efficient cross polarized wave generation for compact, energy-scalable, ultrashort laser sources[END_REF]. The spectra obtained from XPW output, shown in Fig. 7(a), are very similar, at 40.4 and 41.5 nm large for the Ti:Sa and fiber oscillator, respectively. However, the spectrum from the Ti:Sa oscillator exhibits larger wings at -10 dB. This should help to recompress the pulse to a shorter duration, and it may also limit the gain narrowing along the last amplification stage. The large spectrum obtained with the fiber oscillator at the output of the XPW stage is almost Gaussian in shape, highlighting a good temporal and phase quality of the seeded pulses (the first CPA stage does not usually induce phase distortion). Indeed, if the pulses had a distorted temporal phase, then the resulting spectrum would not have been a Gaussian shape and would be narrow. To evaluate the long-term stability of the first CPA with the fiber oscillator (the stability with Ti:Sa oscillator is already well-known), we have processed to three spectral measurements spaced two hours apart at the output of the XPW stage during the continuous operation [see Fig. 7(b)]. It is interesting to check the spectral evolution at this point of the amplifier chain because the XPW process is a highly nonlinear process. Any change in terms of temporal phase or spectral shape of the seeded or amplified pulses will lead to a high spectral variation at the output of the XPW stage. The spectra reported in Fig. 7(b) do not exhibit large variation and the spectral shape is conserved. To evaluate the spectral intensity evolution at each wavelength with time, we subtract the initial spectral intensity on each point by the spectral intensity after a given time and divide the initial spectral intensity. The variation of the overall spectrum is around 20%. The spectral intensity variations are not very high considering that the XPW process is a highly nonlinear process enhancing noise, and that the measurement error from the spectrometer is around 10%. Furthermore, the XPW stability behavior is very similar to the one observed with a Ti:Sa oscillator (i.e., spectral intensity variations are below 20%). Therefore, we consider that the first stage of the system seeded by the fiber oscillator is stable enough to seed the second CPA stage.

The second CPA is exclusively based on multi-pass amplifiers in order to reach high gain of more than 40 dB combined with high pulse energy while avoiding pre-pulses generated by cavities. Pulses are stretched again using an Offner stretcher, and amplified through a five-pass pre-amplifier followed by a saturated four-pass amplifier. These amplifiers are pumped by 3 J at 532 nm from an attenuated RHEA 6 J FPSS laser from Thales. Before compression, the last amplifier delivers 1.33 J with energy fluctuations smaller than 1% rms. A sampling system (using uncoated fused silica wedges) allows us to seed a Treacy compressor operating under air to perform full characterization of the beam. Pulse duration measurements have been realized using a TAIGA second-order auto-correlator from Thales. Figure 8 illustrates the autocorrelation trace of the compressed pulses. Autocorrelation of the pulse from the Ti:Sa oscillator is 46.3 fs FWHM. With the fiber oscillator, we obtained duration of 48.6 fs FWHM. Assuming a sech 2 shape, it gives pulse duration of 30.6 fs with the Ti:Sa oscillator and 32.3 fs with the fiber oscillator. It is important to mention that no acousto-optic programmable dispersive filter (AOPDF) has been used to optimize compression, explaining the wings on autocorrelation using the Ti:Sa oscillator. It should be also noted that the final pulse duration with the fiber oscillator is shorter than the seeded one, and it no longer has any pedestal femtosecond thanks to the use of XPW stage.

The measured efficiency of our compressor, including gratings (with efficiency higher than 93%), is equal to 75%. The resulting peak power for both oscillators is then 30 TW. To the best of our knowledge, we demonstrate a higher peak power and the shortest pulse duration delivered by an amplifier system seeded with a frequency-doubled fiber oscillator.

In most particle-acceleration experiments such as laser-driven ion acceleration, the ultra-short pulse duration necessary to reach high peak power is not the unique criteria. Indeed, the pulse contrast is also a crucial parameter. To evaluate this last parameter, we proceed to picosecond contrast measurements with a TUNDRA third-order auto-correlator from Ultrafast Innovation. Its noise level has been measured below 1:10 11 for all measurements by shutting the fundamental and then SHG signal. Figure 9 shows cross-correlation of pulses from both oscillators. We can consider in the first instance that the crosscorrelation traces are quite similar. The pre-pulse peaks at 66, 40, and 18 ps are well known post-pulse replicas coming from tool compressor and diagnostic bench; hence their presence on both Ti:Sa and fiber oscillator third-order correlation traces. Indeed, similar post pulse at -66, -40, and -18 ps with intensity difference of an order of magnitude are also observed. The replicas are not related to cross-correlation measurement, and they can be avoided with the use of a new compressor tool. It is important to mention that no other pre-pulses are observed; this was not self-evident due to the all-PM design, which may lead to some pulse replicas [START_REF] Boivinet | Solutions innovantes pour réaliser des lasers à impulsions ultra-brèves, stables et fiables pour applications industrielles[END_REF]. Amplified spontaneous emission (ASE) of the system before hundreds of picoseconds is kept below 10 -8 . The contrast from -50 to -25 ps is below 10 -7 for the two oscillators. The Ti:Sa oscillator contrast is almost 1 order of magnitude lower than that of the fiber oscillator. The differences in term of ASE contrast may arise from the laser design. Indeed, the architecture of the fiber oscillator is based on concatenation of nonlinear amplifiers [START_REF] Boivinet | Sub-50 fs 3.5 nJ pulses at 792 nm generated by frequency doubling of an all-PM fiber laser for Ti:sapphire injection[END_REF][START_REF] Boivinet | 1.1 W all-PM fiber laser at 1600 nm delivering 35 fs pulses with 30 nJ energy[END_REF] generating ASE because they are designed to pulse-shape ultra-short pulses at the expense of the contrast ratio. While SHG suppress some of picosecond background, it does not remove it totally. However, the contrast is perfect for gaseous targets requiring a contrast better than 10 -6 for a Joule class laser. It is also good enough for solid targets usually requiring a 10 -9 contrast without any pre-pulse. For the contrast from -20 to 20 ps, there are also some differences but they are smaller than 1 order of magnitude. As is it coherent contrast, we assume that these slight differences might be partially corrected by the use of an AOPDF.

CONCLUSION

In conclusion, we have proven that a standard Ti:Sa oscillator with high performance in terms of energy, pulse duration, and spectral width can be replaced by a compact 35 fs frequencydoubled fiber oscillator to seed a Ti:Sa amplifier chain without almost any compromise on the output pulse duration, and with only a small degradation of 1 order of magnitude on the picosecond contrast. Moreover, we have demonstrated for the first time to our knowledge that sub-35 fs pulses with a peak power of 30 TW can be achieved with a frequency-doubled fiber laser seeding a standard Ti:Sa amplifier chain. This means that these kinds of fiber oscillators can compete with Ti:Sa oscillators while being smaller, cheaper, and more robust and reliable than the solid-state lasers. The table top (1.5 m × 4.5 m) double CPA architecture, using robust solutions such as two-crystal XPW under air and well-established, highly reliable fiber oscillators, is paving the way to the rugged and hands-free multi-TW systems necessary for laser plasma-based electron or ion sources.

Disclosures. The authors declare no conflicts of interest.

Fig. 1 .

 1 Fig. 1.Schematic of MOPA architecture: DSF, dispersioncompensating fiber; WDM, wavelength-division multiplexer; EDF, erbium doped fiber; LMA DC EYDF, large mode area double clad erbium/ytterbium doped fiber; MMD, multimode diode.

Fig. 2 .

 2 Fig. 2. (a) Autocorrelation trace of the output pulse at the output of the LMA Er/Yb doped amplifier. (b) Optical spectrum at the output of the LMA Er/Yb doped amplifier.

Fig. 3 .

 3 Fig. 3. (a) Optical spectrum from frequency-doubled fiber oscillator. (b) Autocorrelation traces of the uncompressed (blue curve) and compressed (red curve) pulses from the frequency-doubled fiber oscillator and the Fourier transform of the spectrum (black curve).

Fig. 4 .

 4 Fig. 4. Time average power (black curve) and pulse duration (blue curve) stability measurement over about 4 h.

Fig. 5 .

 5 Fig. 5. Global synoptic of the 30 TW double CPA architecture using XPW filter.

Fig. 6 .

 6 Fig. 6. Optical spectra from the Ti:Sa and fiber oscillators.

Fig. 7 .

 7 Fig. 7. (a) Spectrum from XPW two-crystal setup. (b) Spectra from XPW two-crystal setup with the fiber oscillator over 4 h.

Fig. 8 .

 8 Fig. 8. Autocorrelation trace of the amplified signal from Ti:Sa and fiber oscillators.

Fig. 9 .

 9 Fig. 9. Third-order correlation trace of the amplified signal from the Ti:Sa and fiber oscillators with two different temporal scales obtained with the same measurement.


Charlène Gémard
email: charlene.gemard@cefe.cnrs.fr

Víctor Planas-Bielsa

Francesco Bonadonna

Thierry Aubin

Contextual variations in calls of two nonoscine birds: the blue petrel Halobaena caerulea and the Antarctic prion Pachyptila desolata

Keywords: acoustic communication, vocal plasticity, motivation, frequency shift, seabirds, petrels

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

Background

In animal communication, the information carried by signals is of two types: stable such as signaler attributes and identity (e.g. species, group membership, individual identity, phenotypic characteristics: [START_REF] Searcy | The evolution of animal communication: reliability and deception in signaling systems[END_REF]; or transient such as emotion (e.g. fear, anxiety, excitation: [START_REF] Briefer | Vocal expression of emotions in mammals: Mechanisms of production and evidence[END_REF][START_REF] Briefer | Vocal contagion of emotions in non-human animals[END_REF][START_REF] Briefer | Coding for 'Dynamic' Information: Vocal Expression of Emotional Arousal and Valence in Non-human Animals[END_REF] and motivation (i.e. tendencies to perform a rewarding behaviors such as fighting or mating [START_REF] Morton | On the occurrence and significance of Motivation-Structural Rules in some bird and mammal sounds[END_REF][START_REF] Bradbury | Principles of animal communication[END_REF][START_REF] Briefer | Coding for 'Dynamic' Information: Vocal Expression of Emotional Arousal and Valence in Non-human Animals[END_REF]. The transmission of transient information through vocal signals has been well documented since Darwin hypothesized that vocal signals are indicators of the signaler's emotions (intense but short-living affective reaction to a specific event or stimulus [START_REF] Briefer | Vocal expression of emotions in mammals: Mechanisms of production and evidence[END_REF] and motivation (probability that an animal would perform a certain behavior: [START_REF] Zahavi | The pattern of vocal signals and the information they convey[END_REF]. More-recent studies suggest that information about emotions and motivations of the signaler are carried by acoustic variations: variations between call types may reflect different arousal valences (positive/negative emotion), whereas the variations within call types may reflect the arousal degree [START_REF] Manser | The generation of functionally referential and motivational vocal signals in mammals[END_REF].

Several stimuli elicit acoustic variations within call types, such as food availability [START_REF] Proppe | The effect of schedules of reinforcement on the composition of spontaneous and evoked black-capped chickadee calls[END_REF] or the presence of a conspecific. When facing a potential mate, songbirds tend to vocalize close to their performance limit and exaggerate their sexual motivation by enhancing acoustic parameters linked to their qualities [START_REF] Sossinka | Song types in the zebra finch[END_REF][START_REF] Podos | A Performance Constraint on the Evolution of Trilled Vocalizations in a Songbird Family (Passeriformes: Emberizidae)[END_REF]. For instance, in zebra finches (Taeniopygia guttata), males seeking for mates produce "courtship song" towards females that are faster, longer and composed of more introductory syllables than "solitary song" [START_REF] Sossinka | Song types in the zebra finch[END_REF]. When facing a rival or an intruder, signalers usually vocalize in a way that increases their perceived competitive potential and willingness [START_REF] Todt | Vocal interactions in birds: the use of song as a model in communication[END_REF][START_REF] Vehrencamp | Handicap, index, and conventional signal elements of bird song[END_REF][START_REF] Searcy | Song as an aggressive signal in songbirds[END_REF]. According to Motivational-Structural Hypothesis [START_REF] Morton | On the occurrence and significance of Motivation-Structural Rules in some bird and mammal sounds[END_REF], contestants produce longer vocal signals, characterized by lower frequencies and wider frequency bandwidth [START_REF] Cardoso | Paradoxical calls: the opposite signaling role of sound frequency across bird species[END_REF]. In many songbirds, contestants increase their performance level by singing faster and/or with a broader bandwidth when facing a rival [START_REF] Searcy | Song as an aggressive signal in songbirds[END_REF][START_REF] Linhart | Being angry, singing fast? Signalling of aggressive motivation by syllable rate in a songbird with slow song[END_REF][START_REF] Funghi | Increased syllable rate during aggressive singing in a bird with complex and fast song[END_REF] Much of the available literature about acoustic variations related to the social context focuses on learning birds, especially passerines [START_REF] Catchpole | Bird song: biological themes and variations[END_REF]. Non-learning birds have received comparatively little attention, likely because they have less vocal plasticity than learning birds [START_REF] Kroodsma | The diversity and plasticity of birdsong[END_REF]. Nonetheless, few studies have investigated temporal variations of male calls in a territorial context. In common loons (Gavia immer), males produce "yodels" with more syllables repeated when an intruder enters their breeding territory. The more syllables it contains, the higher the probability of physical fights [START_REF] Mager | Male common loons signal greater aggressive motivation by lengthening territorial yodels[END_REF]. In hoopoes (Upupa epops), aggressive males produce longer strophes (i.e. with more repeated phrases) whereas males with little motivation to fight produce shorter strophes [START_REF] Martín-Vivaldi | Strophe length in spontaneous songs predicts male response to playback in the hoopoe Upupa epops[END_REF]). In the corncrake (Crex crex), males produce calls with syntactic variations encoding the aggressive motivations (Rek 2013, Rek and[START_REF] Ręk | Temporal patterns of broadcast calls in the corncrake encode information arbitrarily[END_REF].

Although temporal variations have been highlighted in non-songbirds, frequency variations in their calls have not been investigated so far. The understanding of vocal plasticity in non-songbirds thus remains an open question.

Burrowing petrels (Procellariidae, Gmelin 1789) are strong candidates to address this question in regards of the seeming implication of vocal signals in sexual selection. In these long-lived seabirds, adults show high mate and nest fidelity through the years. Monogamous pairs take a couple of years to bond, and divorces are rare [START_REF] Warham | The petrels: their ecology and breeding systems[END_REF][START_REF] Warham | Behaviour and vocalizations of Procellaridae, Hydrobatidae and Pelecoididae[END_REF]. After pairing, they lay a single egg per year, without any possibility of replacement clutch, and both male and female assume parental care.

Mate choice is thus crucial. Signals implied in mate choice may be of two modalities: vocal and olfactory (Gémard et al. submitted;[START_REF] Bretagnolle | Acoustic communication in a group of nonpasserine birds, the petrels[END_REF][START_REF] Kroodsma | Odour-based discrimination of similarity at the major histocompatibility complex in birds[END_REF]. Bachelor males and females call all night long from their self-dug burrow or when overflying the colony. Calls are costly sexual signals as they attract predators, such as the brown skua Stercorarius antarcticus which detects and locates its preys using their calls (Mougeot and Bretagnolle 2000). After pairing, adults scarcely call spontaneously as partner and nest recognitions are mainly olfactory [START_REF] Bonadonna | Partner-specific odor recognition in an Antarctic seabird[END_REF][START_REF] Mardon | Species, gender, and identity: Cracking petrels' sociochemical code[END_REF]. Both breeder and bachelor males call after being vocally challenged by same-sex conspecifics [START_REF] Taoka | Sexual dimorphism of chatter-calls and vocal sex recognition in Leach's stormpetrels (Oceanodroma leucorhoa)[END_REF][START_REF] Bretagnolle | Structural variation in the call of the Cory's shearwater (Calonectris diomedea, Aves, Procellariidae)[END_REF][START_REF] Curé | Sex discrimination and mate recognition by voice in the yelkouan shearwater Puffinus yelkouan[END_REF]. It may be a way to defend their burrow from intruders and/or rivals [START_REF] Warham | Behaviour and vocalizations of Procellaridae, Hydrobatidae and Pelecoididae[END_REF].

Petrels' vocal repertoire is limited. It includes up to three major calls according to the genera [START_REF] Bretagnolle | Acoustic communication in a group of nonpasserine birds, the petrels[END_REF]. Males of the genera Halobaena and Pachyptila have one single major call, repetitive and stereotyped, emitted toward males and females [START_REF] Bretagnolle | Acoustic communication in a group of nonpasserine birds, the petrels[END_REF]. Despite this apparent stereotypy, one may wonder whether the motivation state of the caller may be expressed through acoustic variation. These two genera are thus good study models to investigate contextdependent variations in non-songbirds. In our study, we aimed to investigate acoustic variations in male calls elicited by social interactions with a potential mate or a potential rival. To investigate context-dependent variations in non-songbirds, we focused on two petrel species: the blue petrel Halobaena caerulea and the Antarctic prion Pachyptila desolata. We aimed to assess acoustic variations in male calls elicited by social interactions with a potential mate or a potential rival. By playback experiments, we tested in the field the Motivation Hypothesis, i.e. whether sexual and aggressive motivations of the caller is carried by temporal and/or frequency variations in male-directed and female-directed calls as shown in oscines. We expected directed calls to be longer and faster than spontaneous calls based on previous studies in other non-learning bird species. To go further, we hypothesized that male-directed calls are territorial signals. We thus tested the Breeding-Status hypothesis by assessing whether bachelor and breeder males vocally react in a similar way when vocally provoked by another male. Because breeders are attached to their burrow but also defend their offspring, we expected the breeders' vocal reaction to be stronger, i.e. with longer and faster calls, than the bachelors' reaction.

Methods

(a) Studied species and study site

In blue petrels (Halobaena caerulea) and Antarctic prions (Pachyptila desolata), both males and females vocalize at night and maintain a high vocal activity during the entire breeding season (from October to February in blue petrels, from December to March in Antarctic prions [START_REF] Warham | The petrels: their ecology and breeding systems[END_REF].

Bachelor males and females spontaneously call from their burrow and while flying, respectively.

Breeder males also call when vocally stimulated by a same-sex conspecific whereas breeding females scarcely call, even when vocally stimulated by playback [START_REF] Bretagnolle | Acoustic communication in a group of nonpasserine birds, the petrels[END_REF]. For these reasons, we only focused on males hereafter. We conducted the study on 56 male blue petrels (40 bachelors, 16 breeders) and 50 male Antarctic prions (33 bachelors, 17 breeders) in total.

We performed the fieldwork on blue petrels' and Antarctic prions' colonies, on a small sub-Antarctic island within the Kerguelen Archipelago (Ile Verte, 49°51′ S, 70°05′ E), southern Indian Ocean during the birds' breeding season (November 25 to December 12 on blue petrels, and December 23 to January 16 on Antarctic prions). We tested the "Breeding-Status Hypothesis" and the "Motivational Hypothesis" on breeder and bachelor males facing another male during the 2013 and 2017 breeding seasons, and on bachelors facing females during the 2018 breeding season.

(b) Playback construction

For playback experiments, we built 24 playbacks from 24 isolated spontaneous calls of bachelor males and females of both blue petrels and Antarctic prions (nine male and five female blue petrels; five male and five female Antarctic prions) using the signal processing software Avisoft-SASLab Pro v 5.2.11 (Specht 2017). To do so, we recorded spontaneous calls of bachelor males and females in the same colonies in 2013 and 2017. Males were recorded when calling spontaneously from their burrow, using an omnidirectional Sennheiser K6-ME62 microphone (frequency response: 20-20 000 Hz ± 2.5 dB, all uncertainties in SD units unless otherwise stated). Females were recorded when spontaneously calling while flying, using a directional Sennheiser K6-ME66 microphone (frequency response: 40-20 000 Hz ± 2.5 dB). Both microphones were connected to a Marantz PMD 660 digital recorder (sampling frequency: 44.1 kHz, dynamic: 16 bits). In both blue petrel and Antarctic prion, there is a vocal sexual dimorphism mainly based on the call syntax. Male calls played-back consisted of two phrases separated by a silence of 200 ± 60 ms (total duration: 5.5 ± 1.6 s in blue petrel, and 3.43 ± 0.85 s in Antarctic prion), extracted from the call of a male blue petrel or a male Antarctic prion. Female calls played-back consisted of a mean complete female flight call (i.e. three-phrase calls, total duration: 12.4 ± 2.2 s in blue petrels and 6.2 ± 2.1 s in Antarctic prions).

(c) Playback experiments

To limit background noises, we performed playback experiments in quiet weather conditions (wind speed < 4 km.h -1 and no rain). To mimic the natural conditions of a vocal exchange, we carried out playback sessions in dark nights between 22:00-02:00, which is the period of maximal vocal activity in the colony (Mougeot and Bretagnolle 2000).

Prior to each experiment, we randomly located vocally active bachelor males in the colony (40 blue petrels and 33 Antarctic prions) and we located breeder males (16 blue petrels and 17 Antarctic prions) by controlling the monitored burrows of the colony. The recording equipment was composed of an omnidirectional Sennheiser K6-ME62 microphone (frequency response: 20-20 000 Hz ± 2.5 dB) connected to a Marantz PMD 660 digital recorder. The microphone was positioned on the ground, at the burrow entrance. We waited a few minutes before starting the experiment to ensure that the tested individual did not vocally react to our presence, i.e. bachelor males kept a steady call rate and breeder males stayed silent. We recorded spontaneous calls from bachelor males during four minutes. When we detected a silence longer than about 10 seconds between two spontaneous calls, we then broadcasted either a male or a female call, randomly-selected among the built playbacks, at a natural sound pressure level, i.e. maximum SPL at 70 dB (blue petrels: 66.3 ± 9.6 dB, measured on 115 calls from 14 males; and Antarctic prions: 68.1 ± 11.0 measured on 443 calls from 40 males with a sound level meter) using a TASCAM DR-07MKII digital recorder (sampling frequency: 44.1 kHz, dynamic:

16 bits) at the entrance of the burrow. We recorded the vocal reaction during the playback and two minutes after it ended. Because breeders do not spontaneously vocalize [START_REF] Bretagnolle | Acoustic communication in a group of nonpasserine birds, the petrels[END_REF][START_REF] Warham | The petrels: their ecology and breeding systems[END_REF][START_REF] Warham | Behaviour and vocalizations of Procellaridae, Hydrobatidae and Pelecoididae[END_REF], we recorded only male-directed calls using the same male playbacks and the same experimental protocol performed in bachelor males. Each male -bachelor or breeder -was tested only once. To avoid testing males twice, the nest entrance was labelled by a colored marker.

(d) Acoustic analysis

The structure of a petrel call consists of a repetition of distinct phrases, themselves composed of syllables [START_REF] Bretagnolle | Acoustic communication in a group of nonpasserine birds, the petrels[END_REF]. There are four types of syllables discernible by their frequency modulation shape, hereafter mentioned as A, B, C, and D. In blue petrels and Antarctic prions, the number of syllables C varies depending on the individuals (mean ± SD: 4.7 ± 2.1 and 1.8 ± 0.8 syllables, respectively). The first and last phrases are sometimes incomplete, i.e. syllables C and D are missing. Hereafter, we considered only complete phrases in our analyses. In total, we obtained N = 678 phrases of blue petrels (117 on breeders and 561 on bachelors) and 428 phrases of Antarctic prions (71 on breeders and 357 on bachelors).

Tested individuals might return to a spontaneous vocal behavior before the end of the experiment.

To limit bias related to a behavioral change, we restricted our analyses to the last spontaneous calls before playback and the first directed calls after playback.

Although vocalizations are often described at the call or phrase levels in the literature, syllable types might be subjected to particular social or environmental cues [START_REF] Proppe | The effect of schedules of reinforcement on the composition of spontaneous and evoked black-capped chickadee calls[END_REF]. We thus aimed to describe the calls at different syntactic levels and in two physical domains. We measured 14 acoustic parameters in the temporal domain and 20 in spectral domain that may encode motivational information (see [START_REF] Kroodsma | Odour-based discrimination of similarity at the major histocompatibility complex in birds[END_REF] for a review) on syllables and on phrases (classification, description and abbreviations are provided in Table 1).

To increase the accuracy of frequency measurements, we preliminarily downsampled recorded calls from 44.1 to 11.025 kHz using the automatic "Sampling Frequency Conversion" functionality of Avisoft. We also high-passed filtered (cutting frequency: 0.10 kHz, FFT filter) recorded calls to remove low-frequency background noise, which does not affect recordings. We counted the number of syllables and phrases on sonograms. We did not analyze syllables C 2 to C n as they are not present in all individuals. We automatically extracted temporal variables on the amplitude envelopes using the software functionality "Pulse Train Analysis", with a resolution of 11.6 ms. This functionality automatically measures the temporal structure of waveforms using pulse recognition algorithms. We automatically extracted fundamental frequencies and variables describing energy spectral distribution on linear amplitude spectrum with a resolution of 22 Hz. Automatic extractions were based on similar pre-sets for all birds to ensure replicable measurements.

(e) Neural Network Approach

We tested each of the hypotheses, Motivation Hypothesis and Breeding Status Hypothesis, independently, and both problems were stated as a supervised learning problem. Each procedure was repeated identically for Antarctic prions and blue petrels.

To discriminate the three call types, spontaneous calls, male-directed calls, and female-directed calls, we used a Supervised Machine Learning algorithm (SML). We here used algorithms based on a Neural Network (NN). NN relaxes linearity assumptions and thus provides a flexible framework for the analysis of acoustic signals [START_REF] Lek | Application of neural networks to modelling nonlinear relationships in ecology[END_REF][START_REF] Olden | Machine Learning methods without tears: a primer for ecologists[END_REF]). In comparison with other machine learning methods such as random forests, NN exhibit higher predictive power, better flexibility and stability [START_REF] Kotsiantis | Supervised machine learning: a review of classification techniques[END_REF][START_REF] Olden | Machine Learning methods without tears: a primer for ecologists[END_REF].

We tested different NN architectures. Shallow networks (no hidden layers) showed poorer performance (in terms of accuracy) than NN with hidden layers. We finally used a two hidden layers architecture (with 10 and 5 nodes respectively) since more complex architectures did not improve the out of sample accuracy, and were slower to train.

To avoid overfitting, we performed a Cross Validation procedure (CV), in which we randomly split the data in two groups called "training" (70% data) and "test" (30% remaining data). After the training, we evaluated the NN performance by comparing the prediction on the test data and computing the confusion matrix, M, where the element m i,j provides the number of cases predicted with label i that are actually in the class j. We then calculated the accuracy, defined as the sum of the diagonal elements of the confusion matrix divided by the total number of cases, and that corresponds to the proportion of well-identified labels by the algorithm. The procedure split-training-evaluation was repeated (N=1000) to obtain an average and standard deviation for each of the entries of the confusion matrix, and for the accuracy.

To estimate the weight of the variable classes (frequency parameters, temporal variables, and syntactic variables), we trained a NN for each class. As the NN did not converge with only two syntactic variables, we also trained a NN using both temporal and syntax variables. We then graphically compared the accuracy of the three NN with each other, and with the full NN as well.

(f) Generalized Linear Mixed Model (GLMM) approach

In a first phase, we aimed to assess whether the different call types (spontaneous, male-directed, and female-directed), and the calls of males with different breeding status (bachelor or breeder) can be discriminated. In a second phase, we aimed to highlight the acoustic parameters that significantly vary between the three call types or according to the breeding status, and how they vary. We tested each hypothesis, Motivation Hypothesis and Breeding-Status Hypothesis, independently and similarly.

We preliminary performed a standard correlation analysis that shown that frequency parameters are independent from temporal and syntactic parameters (appendices A and B). We thus analyzed the three classes of acoustic parameters independently. Each procedure was repeated identically for blue petrels and Antarctic prions.

We used Principal Components Analysis (PCA) to reduce the dimensionality of the frequency class and the temporal class, consisting of 20 and 12 variables respectively, for both species and both hypotheses independently (Table 1). In both species, PCA performed on the frequency class and temporal class are respectively called PCA F and PCA T hereafter. For each of the four PCA, we first calculated a correlation matrix and we kept the six first Principal Components (PC) that explained between 83 and 91% of the total variance depending on the parameter class and the species. PCA results are available in appendices C and D. We did not need to perform a PCA in syntactic class as it consisted of only two variables.

To test the Motivation Hypothesis, we used Generalized Linear Mixed Models (GLMM) to model the call type as a function of the six principal components of PCA F or PCA T independently. As the response variable has to be binomial, we used three GLMMs to compare spontaneous calls vs maledirected calls, spontaneous calls vs female-directed calls, and male-directed calls vs female-directed calls. To incorporate the dependency among calls of the same male, we used "male ID" as random factor. When we similarly modelled the call type as a function of call syntax, covariates were the number of syllables per phrase and the number of phrases per call. To test the Breeding-Status Hypothesis, we similarly modelled the breeding status as a function of the six principal components of PCA F or PCA T independently using a binomial GLMM. We similarly modelled the breeding status as a function of the number of syllables per phrase and the number of phrases per call. When models failed to converge with the six principal components as covariates, we used fewer principal components (Tables 3,5).

Results

(a) Motivation Hypothesis

(i) Call-type discrimination NN discriminated the three call types of blue petrels and Antarctic prions with an accuracy of 90.6 ± 2.3% and 79.8 ± 3.8%, respectively. In both species, spontaneous calls and female-directed calls were more similar to each other than to male-directed calls (Table 2).

In both species, the accuracy of call-type discrimination based on temporal parameters and syntax only was close to the discrimination accuracy when considering all parameters, and higher than discrimination accuracy when considering temporal parameters or frequency parameters only (Figure 2a,b). In blue petrels, discrimination accuracy when considering only frequency parameters was similar to discrimination accuracy when considering only temporal parameters, whereas it was lower in Antarctic prions (Figure 2a,b).

In spectral domain, PCA F results showed that the two first principal components (PC F 1, PC F 2) were related to fundamental frequency and energy quartiles of syllable and phrase levels, in both blue petrel and Antarctic prion (Table 3). Variables related to PC F 3 to PC F 6 then varied between the two species. In temporal domain, PCA T results showed no clear pattern between the two species (Table 3).

Detailed results of PCA T showing variable contributions to each principal component in both species are given in appendix C. Detailed results of binomial GLMM used to compare the call types in both species are presented in appendix D.

(ii) Female-directed vs spontaneous calls In spectral domain, results in blue petrels showed a decrease of PC F 4 and PC F 5 (estimate = -0.66, p < 0.001; estimate = -1.62, p < 0.001). It suggests a broader frequency bandwidth across the phrase in female-directed calls than spontaneous calls on average (Table 3). In Antarctic prions, results showed a decrease of PC F 1 and PC F 2 (estimate = -0.32, p = 0.001; estimate = -0.39, p = 0.03), and an increase of PC F 5 (estimate = 0.81, p = 0.004). It suggests that female-directed calls were on average higherpitched than spontaneous calls (Table 3).

In temporal domain, results showed a decrease of PC T 2 (estimate = -0.78, p < 0.001) in blue petrels, suggesting that the average duration of syllables was longer and the average phrase tempo was higher in female-directed calls than spontaneous calls (Table 3). In Antarctic prions, female-directed calls were characterized by an increase of PC T 1 and PC T 4 (estimate = 0.67, p < 0.001; estimate = 0.71, p < 0.001), suggesting that the average A-syllable duration was longer and the average phrase tempo was higher in female-directed calls than spontaneous calls (Table 3). In both species, the average number of phrases per call was higher in female-directed calls than spontaneous calls (estimate = 3.60, p < 0.001; estimate = 1.04, p < 0.001). In Antarctic prions, the average number of syllables per phrase was also higher in female-directed calls than in spontaneous calls (estimate = 0.82, p = 0.02; Tables 3,6).

(iii) Female-directed vs male-directed calls In spectral domain, results in blue petrels showed an increase of PC F 1, PC F 3, PC F 4 and PC F 5 (estimate = 4.24, p < 0.001; estimate = 6.00, p = 0.004; estimate = 5.63, p = 0.04; estimate = 20.47, p < 0.001), and a decrease of PC F 2 (estimate = -7.07, p < 0.001). It suggests that male-directed calls were on average higher-pitched with a narrower frequency bandwidth than female-directed calls in blue petrels. In Antarctic prions, female-directed calls and male-directed calls were not significantly different in spectral domain (Tables 3,6).

In temporal domain, female-directed calls and male-directed calls were not significantly different in blue petrels (Table 3). In Antarctic prions, results showed a decrease of PC T 1 (estimate = -36.21, p = 0.04) suggesting that the average duration of syllable A was shorter, and the average phrase tempo was lower in male-directed calls than female-directed calls (Table 3). In both species, the average number of phrases per call was higher in male-directed calls than female-directed calls (estimate = 2.89, p = 0.001; estimate = 2.44, p < 0.001, Tables 3,6).

(iv) Male-directed vs spontaneous calls

In spectral domain, results showed an increase of PC F 1, PC F 3 and PC F 5 (estimate = 0.73, p < 0.001; estimate = 0.51, p = 0.01; estimate = 1.51, p < 0.001), and a decrease of PC F 2 (estimate = -0.59; p = 0.002) in blue petrels; and a decrease of PC F 1 and PC F 2 in male-directed calls (estimate = -1.82, p < 0.001; estimate = -1.77, p = 0.003) in Antarctic prions. It suggests that in both species male-directed calls of bachelors were on average higher-pitched than spontaneous calls. In blue petrels, the average frequency bandwidth was tighter in male-directed calls than in spontaneous calls (Tables 3,6).

In temporal domain, results showed an increase of PC T 5 (estimate = 0.92, p = 0.01), and a decrease of PC T 2 and PC T 6 (estimate = -0.75, p = 0.02; estimate = -2.02, p < 0.001; respectively) in blue petrels; and a decrease of PC T 1 (estimate = -1.28, p < 0.001) and an increase of PC T 2 (estimate = 0.52, p = 0.002) in Antarctic prions. It suggests that in both species, the average duration of phrases was longer, the average phrase tempo was lower, and the average duration of syllable was longer in male-directed calls than spontaneous calls (Table 3). In both species, the average number of phrases per call was higher in male-directed calls than spontaneous calls (estimate = 3.48, p < 0.001; estimate = 9.00, p = 0.004, Tables 3,6).

(b) Breeding-Status Hypothesis (i) Breeding-status discrimination NN discriminated the two breeding status (bachelor vs breeder) in blue petrels and Antarctic prions with an accuracy of 98.9 ± 1.1% and 94.6 ± 3.9%, respectively (Table 4).

In blue petrels, the accuracy of breeding-status discrimination based on frequency parameters only was close to the maximum discrimination accuracy when considering all parameters (Figure 2c).

In Antarctic prions, discrimination accuracy when considering temporal and syntactic parameters was close to the maximum discrimination accuracy when considering all parameters (Figure 2d). Discrimination accuracy when considering only frequency parameters was the lowest, similarly to results of call-types discrimination (Figure 2).

In spectral domain, results of PCA on bachelors' and breeders' male-directed calls were similar to PCA on different calls of bachelors', in both species (Tables 3,4). In temporal domain, PCA T showed no clear pattern between the two species on temporal variables (appendix E). Details of variable contribution to each principal component in both species are given in appendix E. Detailed results of binomial GLMM used to compare bachelors' and breeders' male-directed calls are presented in appendix F in both species.

(ii) Bachelors' vs breeders' male-directed calls In spectral domain, results in blue petrels showed an increase of PC F 2, PC F 4 and PC F 5 (estimate = 0.92, p = 0.001; estimate = 1.13, p = 0.009; estimate = 6.30, p < 0.001) and a decrease of PC F 3 and PC F 6 (estimate = -0.76, p = 0.02; estimate = -1.65, p = 0.02). In Antarctic prions, results showed an increase of PC F 1, PC F 3, PC F 4 (estimate = 0.33, p < 0.001; estimate = 0.62, p = 0.006; estimate = 0.73, p = 0.02, respectively); and a decrease of PC F 6 (estimate = -1.16, p = 0.001). It suggests that on average, breeders produced lower-pitched calls than bachelors in blue petrels, while breeders produced higher-pitched calls than bachelors in Antarctic prion (Tables 5,6).

In temporal domain, results in blue petrels showed a decrease of PC T 2, PC T 3, PC T 4, PC T 5 (estimate = -0.77, p < 0.001; estimate = -0.93, p < 0.001; estimate = -0.85, p < 0.001; estimate = -0.38, p = 0.01), and an increase of PC T 6 (estimate = 0.41, p = 0.01). It suggests that the average rhythm and tempo were higher, and the average duration of syllable (except D) was shorter in breeder calls than bachelor's. In Antarctic prions, results showed a decrease of PC T 3 and an increase of PC T 6 (estimate = -0.44, p = 0.003; estimate = 0.92, p = 0.001), suggesting that the difference between bachelors and breeders was coded at the syllable level: the average durations of syllable A and interval between syllables B and C 1 was longer in breeder calls than bachelor's. In both species, the average number of phrases per call was lower in breeder calls than bachelor's (estimate = -0.13, p < 0.001; estimate = -0.16, p < 0.001, Tables 5,6).

Discussion

The aim of this study was to compare the acoustic structure of males' calls in different social contexts in two burrowing-petrel species. We first compared the three call types of bachelor males (Motivation Hypothesis): spontaneous, male-directed, and female-directed. We then compared whether male-directed calls emitted by breeders and bachelors present the same acoustic variations (Breeding-Status Hypothesis).

(a) Motivation Hypothesis

In both blue petrels and Antarctic prions, calls emitted by bachelors in different social situations (spontaneous, female-directed, and male-directed calls) are discriminable based on their acoustic parameters. Although temporal parameters are the most discriminant due to their great variations between call types, our results showed significant frequency shifts between the different call types as well. For the first time in two non-songbirds, we observed context dependent frequency shifts at the fine scale of syllables within phrases. Thus, in blue petrels and Antarctic prions, the presence of conspecifics, either male or female, influences the vocal performance of callers, resulting in acoustic variations in both temporal and spectral domains.

(i) Female-directed calls Female-directed calls and spontaneous calls were more similar to each other than to male-directed calls. In songbirds, spontaneous songs have two main functions: to attract potential mates and to repel rivals ("Dual-Function Hypothesis": Catchpole and Slater 2008). Our results support the hypothesis that male calls in burrowing petrels have the same functions: attracting flying females into the burrow and repelling other males. The greater similarity between spontaneous and female-directed calls, in both species, suggests that spontaneous calls, resounding at night in the colony, may primarily be sexual signals addressed to flying females susceptible to detect the signal (Gémard et al. submitted;[START_REF] Bretagnolle | Acoustic communication in a group of nonpasserine birds, the petrels[END_REF], even though they are potentially emitted in absence of an audience.

When vocally reacting to a female call, bachelors of both species produce calls characterized by temporal variations. In blue petrels, female-directed calls consist of more, longer, and slower (lower phrase tempo) phrases. In Antarctic prions, female-directed calls are faster (higher phrase tempo), and consist of more phrases and more syllables than spontaneous calls. These results are consistent with previous studies on temporal variations in female-directed songs in songbirds [START_REF] Sossinka | Song types in the zebra finch[END_REF][START_REF] Sakata | Social modulation of sequence and syllable variability in adult birdsong[END_REF]. In both blue petrels and Antarctic prions, an increase in call duration and/or syllable number may thus indicate a higher vocal investment and a greater sexual motivation when a male perceives the presence of a female, in spite of an increased risk of predation (Mougeot and Bretagnolle 2000). This suggests that spontaneous calls may have a trade-off between advertising potential for females flying over the burrow and self-protection against predators.

When vocally reacting to a female call, bachelors of both species produce calls characterized by spectral variations. In blue petrels, our results showed a broader frequency bandwidth due to frequency shifts in syllables. More precisely, the first syllable (A) was higher-pitched and the last syllable (D) was lower-pitched in female-directed calls than in spontaneous calls. In Antarctic prions, femaledirected calls consisted of higher-pitched phrases than spontaneous ones. When reacting to a potential mate, males usually enhance the acoustic parameters related to their qualities [START_REF] Sossinka | Song types in the zebra finch[END_REF][START_REF] Podos | A Performance Constraint on the Evolution of Trilled Vocalizations in a Songbird Family (Passeriformes: Emberizidae)[END_REF]. In previous studies on blue petrels, we showed that large males produce long and high-pitched calls [START_REF] Gémard | Males' calls carry information about individual identity and morphological characteristics of the caller in burrowing petrels[END_REF], and that females are more attracted by high-pitched calls (Gémard et al. submitted). In Antarctic prions, large males produce low-pitched calls [START_REF] Gémard | Males' calls carry information about individual identity and morphological characteristics of the caller in burrowing petrels[END_REF]) and we do not know female preferences for acoustic parameters. One hypothesis may be that male blue petrels exaggerate acoustic parameters related to their morphology when vocally reacting to a female. This may not be the case in Antarctic prions, although we cannot exclude that further relationships between male qualities and acoustic parameters have not been highlighted yet.

(ii) Male-directed calls After being vocally challenged by another male, bachelors of both species produced male-directed calls that are longer (with more phrases) and slower (lower syllable and phrase tempos) than spontaneous calls. This result is consistent with previous studies showing that lengthening vocalizations is an aggressive signal in learning and non-learning birds [START_REF] Martín-Vivaldi | Strophe length in spontaneous songs predicts male response to playback in the hoopoe Upupa epops[END_REF][START_REF] Mager | Male common loons signal greater aggressive motivation by lengthening territorial yodels[END_REF][START_REF] Balsby | Function of vocalization length and warble repertoire size in orange-fronted conures[END_REF]. In both blue petrels and Antarctic prions, male-directed calls also consist of longer syllables than in spontaneous calls. Similar results have been found in a territorial passerine, the skylark (Alauda arvensis): when vocally challenged by another male, skylark males produce longer syllables separated by shorter silences within songs [START_REF] Geberzahn | How a songbird with a continuous singing style modulates its song when territorially challenged[END_REF]. Further studies in songbirds also show that vocal performance and song complexity increase in aggressive contexts [START_REF] Dubois | Swamp sparrows modulate vocal performance in an aggressive context[END_REF][START_REF] Kareklas | Signal complexity communicates aggressive intent during contests, but the process is disrupted by noise[END_REF]). We did not find similar results in blue petrels and Antarctic prions, as challenged males produced calls with lower syllable and phrase tempos, and with a steady number of syllables. Unlike songbirds, burrowing petrels produce stereotyped calls with a limited number of syllable types. In these species, the increase of vocal performance and of song complexity in an aggressive context shown in songbirds may thus be impossible [START_REF] Searcy | Song as an aggressive signal in songbirds[END_REF]. Alternatively, non-learning birds may have evolved a different signaling system compared to learning species, where motivation is not coded by vocal performance.

Although temporal variations in male-directed calls are described in both songbirds and nonsongbirds, spectral variations have never been described in non-songbirds to our knowledge. Our results show that male-directed calls have a higher fundamental frequency than spontaneous calls in both species. Although energy quartiles also increased in Antarctic prions, they decreased in blue petrels suggesting a tighter frequency bandwidth than in spontaneous calls. According to the Motivational-Structural Hypothesis, vocalizations emitted in an aggressive social context are characterized by long durations, low frequencies, wide frequency bandwidth, and little frequency variations [START_REF] Morton | On the occurrence and significance of Motivation-Structural Rules in some bird and mammal sounds[END_REF]. Our results in burrowing petrels show an opposite pattern, which is not so surprising. The Motivational-Structural Hypothesis has been first described in mammals. Although some songbirds such as ravens [START_REF] Szipl | Calls during agonistic interactions vary with arousal and raise audience attention in ravens[END_REF]) and swamp sparrows [START_REF] Dubois | Swamp sparrows modulate vocal performance in an aggressive context[END_REF]) follow the rules, many do not (see Cardoso 2012 for a review). Producing long high-pitched-calls while being vocally challenged by another male at the entrance of the burrow may thus be an aggressive signal in territory tenure.

(b) Breeding-Status Hypothesis

Our results show that calls emitted by bachelors and breeders toward males are discriminable based on their acoustic parameters. When stimulated by another male, breeders produce lower-pitched calls than bachelors in blue petrels and higher-pitched calls in Antarctic prions. In burrowing petrels, breeder and bachelor males do not differ morphologically but breeders coming back from their feeding trips at sea are heavier than bachelors [START_REF] Chaurand | Incubation routine, body mass regulation and egg neglect in the blue petrel Halobaena caerulea[END_REF]Appendix G). Large individuals produce high-pitched calls in blue petrels and low-pitched calls in Antarctic prions [START_REF] Gémard | Males' calls carry information about individual identity and morphological characteristics of the caller in burrowing petrels[END_REF]). Here we observed the opposite pattern, suggesting that weight variation is thus not a sufficient explanation for spectral variations in male-directed calls produced by breeders.

Frequency shifts between bachelors and breeders may thus be related to the motivation of the caller.

In both species, breeders' calls consisted of fewer phrases than bachelors' and are thus shorter.

One hypothesis is that breeders have less endurance than bachelors do, as they fast in the burrow for several days when incubating the egg [START_REF] Chaurand | Incubation routine, body mass regulation and egg neglect in the blue petrel Halobaena caerulea[END_REF]. Another hypothesis is that, in species vulnerable to predation (Mougeot and Bretagnolle 2000), producing short calls may be a trade-off between self-protection from predators and repelling intruders. A short call by the resident male might be enough to immediately scare the intruder that, outside the burrow, would be the first to be caught by a predator possibly attracted by that call.

The acoustic variations related to the breeding status of the caller are not similar to the variations between spontaneous and male-directed calls of bachelors. Therefore, differences between bachelors' and breeders' calls may not be related to the territorial-response intensity of the caller only, contrary to our hypothesis.

(c) Conclusion

In many species, males use long-distance vocal signals to attract mates and/or to regulate the spacing between competitors. In blue petrels and Antarctic prions, we showed that conspecifics vocally stimulating a male at the entrance of its burrow induce temporal variations, but also frequency shifts in the burrow-owner calls. These acoustic variations differ according to the conspecific sex, and are thus likely to convey different motivations, such as aggressive motivation when facing another male and sexual motivation when facing a female. Both bachelors and breeders intensively react to the presence of a conspecific male, but the acoustic variations related to the breeding status of the caller are not explained by a difference in the territoriality intensity. So far, expression of motivation in vocal signals have been highlighted in very few non-songbirds, and this is the first time that a study describes spectral variations related to the signaler motivation in non-songbirds. It opens new leads in the assessment of vocal plasticity in non-oscine species. Tables Table 1. Summary of the 34 syntactic, temporal and spectral parameters and their abbreviations used to describe calls of male blue petrels H. caerulea and Antarctic prions P. desolata.

Figure captions

class

588

in Table 1.

589 29 Variable abbreviations given in Table 1.

32

Figure 1 .

 1 Figure 1. Spectrograms of calls from a bachelor male of blue petrel H. caerulea and Antarctic prion P. desolata (Blackman window, FFT length: 512): (a) spontaneous blue petrel call; (b) spontaneous Antarctic prion call; (c) male-directed blue petrel call; (d) male-directed Antarctic prion call.

Figure 2 .

 2 Figure 2. Accuracy of NN trained to discriminate the three call types of bachelor males based on their acoustic parameters in (a) blue petrel H. caerulea and (b) Antarctic prion P. desolata. Accuracy of NN trained to discriminate male-directed calls of bachelors and breeders in (c) blue petrels and (d) Antarctic prions.

  , B.Q75, C.Q75, Ph.Q75 ↗ ↗ -significant; NA: non-applicable; ↗ indicates an increase and ↘ a decrease. Variable abbreviations given

  -significant; NA: non-applicable; ↗ indicates an increase and ↘ a decrease.

Table 2 .

 2 Mean accuracy and standard deviation of the classification of three call types of bachelor males in blue petrels H. caerulea and Antarctic prions P. desolata.

	species	actual		prediction
			spontaneous	female-directed male-directed
	blue petrels
		spontaneous	25.4% (3.6)	7.8% (2.7)	1.0% (1.1)
		female-directed	8.0% (2.5)	28.7% (3.8)	0.0% (0.2)
		male-directed	1.6% (1.2)	0.1% (0.4)	27.4% (3.9)
	Antarctic prions
		spontaneous	24.3% (2.7)	3.5% (1.5)	1.3% (1.1)
		female-directed	3.1% (1.7)	21.2% (2.6)	0.3% (0.4)
		male-directed	1.4% (1.0)	0.2% (0.5)	44.5% (3.1)

Table 3 .

 3 Variations of acoustic parameters between the three different call types of bachelor males in blue petrels H. caerulea and Antarctic prions P. desolata. Acoustic parameters given here are the most correlated with the principal components (but see appendix C for the contribution of each acoustic parameter in each principal component).

Table 4 .

 4 Mean accuracy and standard deviation of the classification of bachelor and breeder males in blue petrels H. caerulea and Antarctic prions P. desolata.

	species	actual	prediction
			bachelor	breeder
	blue petrels
		bachelor	67.5% (3.8)	0.5% (0.8)
		breeder	0.6% (0.8)	31.4% (3.9)
	Antarctic prions
		bachelor	57.2% (6.4)	3.7% (3.1)
		breeder	3.2% (3.5)	38% (6.2)

Table 5 .

 5 Variations of acoustic parameters between the male-directed calls of bachelor and breeder males in blue petrels H. caerulea and Antarctic prions P. desolata. Acoustic parameters given here are the most correlated with the principal components (but see appendix E for the contribution of each acoustic parameter in each principal component).

Table 6 .

 6 Summary table of the acoustic variations characterizing directed calls emitted by males stimulated by a conspecific, according to the sex of the conspecific and the reproductive status of the signaler.

		bachelor males' calls		breeder males' calls
		female-directed	male-directed	male-directed
		(vs spontaneous)	(vs spontaneous)	(vs bachelors' male-directed calls)
	blue petrels
	frequency variables	-higher pitched	-higher pitched	-narrower bandwidth
		-shifts on syllables	-narrower bandwidth
	temporal variables	-longer phrases	-longer phrases	-shorter syllables
		-lower tempo	-lower tempo	-higher rhythm
	syntax	-more phrases per call	-more phrases per call	-more syllables per phrase
				-less phrases per call
	Antarctic prions
	frequency variables	-higher pitched	-higher pitched	-higher pitched
	temporal variables	-higher tempo	-lower tempo	-longer syllables A
			-longer syllables
			-shorter silences
	syntax	-more phrases per call	-more phrases per call	-less phrases per call

Ethics statement