# Mate choice intensifies motor signalling in Drosophila

Allan Debelle, Alexandre Courtiol, Michael G. Ritchie, Rhonda R. Snook

► To cite this version:

Allan Debelle, Alexandre Courtiol, Michael intensifies motor signalling in Drosophila. 10.1016/j.anbehav.2017.09.014. hal-02617677

G. Ritchie, Rhonda R. Snook. Mate choice Animal Behaviour, 2017, 133, pp.169-187.

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1 Mate choice intensifies motor signalling in *Drosophila*

2 Allan Debelle<sup>a, b, c, *, 1</sup>, Alexandre Courtiol<sup>d, 1</sup>, Michael G. Ritchie<sup>e</sup>, Rhonda R. Snook<sup>a</sup>

3 <sup>a</sup>Animal & Plant Sciences, University of Sheffield, Sheffield, U.K.

4 <sup>b</sup>School of Life Sciences, University of Sussex, Brighton, U.K.

5 <sup>c</sup>INRA, Centre de Biologie et de Gestion des Populations (UMR 1062 INRA/IRD/Cirad/Montpellier SupAgro), Montferrier-Sur-Lez, France

6 <sup>d</sup>Department of Evolutionary Genetics, Leibniz Institute for Zoo and Wildlife Research, Berlin, Germany

7 <sup>e</sup>School of Biology, University of St Andrews, St Andrews, U.K.

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9 <sup>*</sup>*Correspondence*: A. Debelle, Centre de Biologie et de Gestion des Populations, 755 avenue du Campus Agropolis CS 30016, 34988

10 Montferrier sur Lez Cedex, France.

11 <sup>E-mail address:</sup> allandebelle@gmail.com (A. Debelle).

12 <sup>1</sup>These authors contributed equally to this work
Mate choice has the potential to act on the evolution of motor performance via its direct influence on motor sexual signals. However, studies demonstrating this are rare. Here, we perform an in-depth analysis of *Drosophila pseudoobscura* courtship song rate, a motor signal under mate choice in this species, and analyse the response of this signal to sexual selection manipulation using experimental evolution. We show that manipulating the opportunity for sexual selection led to changes in song production rate and singing endurance, with males from the polyandrous populations producing faster song rates over longer time periods than males from monogamous populations. We also show that song rate is correlated with estimates of overall courtship vigour. Our results suggest that the action of mate choice on a motor signal has affected male motor performance displayed during courtship. We consider potential selective benefits associated with changes in motor performance, including condition-dependent signalling, and discuss the implications of these results for the study of motor signals under sexual selection.

Keywords: courtship song, *Drosophila pseudoobscura*, experimental evolution, interpulse interval, mate choice, motor performance, sexual selection
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Motor performance, or *vigour* (Darwin, 1859; Darwin, 1871), is the ability of an individual to repeatedly perform energetically-costly motor acts (Byers, Hebets, & Podos, 2010). As this ability often has drastic fitness consequences (e.g. determining the ability to escape predators, forage or capture preys), its evolution is often driven by natural selection (Byers et al., 2010; Irschick & Garland, 2001). Yet, sexual selection also has the potential to affect the evolution of motor performance, when mate choice or mate competition targets motor signals (i.e. signals involving any kind of sustained muscular activity such as threat displays, courtship displays such as dances, or acoustic and vibratory signals; Bonduriansky, 2011; Husak & Fox, 2008). Because such signals typically require high-speed muscle contractions that are energetically-costly to produce (Lailvaux & Irschick, 2006), they have the potential to be reliable indicators of a signaller's overall motor capacities, and thus of the individual's current condition (Byers et al., 2010; Clark, 2012; Lailvaux & Irschick, 2006; Oufiero & Garland, 2007). Hence, by directly influencing the evolution of a given motor signal, sexual selection may lead to a correlated increase of the overall motor capacities of signallers (Byers et al., 2010; Clark, 2012; Mowles & Ord, 2012; Ryan, 1988).

Although potential links between motor sexual signals and motor performance have received significant attention in the recent literature (Byers et al., 2010; Irschick, Meyers, Husak, & Le Gaillard, 2008; Mowles & Ord, 2012), their investigation has so far been restricted to two issues; the link between motor signals involved in mate competition and overall motor performance (Andersson, 1996; Byers et al., 2010; Lailvaux & Irschick, 2006) and the link between motor signals involved in mate choice and non-motor measures of mate condition (e.g. offspring production, growth rate, etc.; Irschick et al., 2008). For example, a link between male dominance display and running endurance has been shown in *Anolis* lizards (Perry, Levering, Girard, & Garland, 2004), and a correlation between male song structure and
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offspring survival was found in the zebra finch *Taeniopygia guttata* (Woodgate, Mariette, & Bennett, 2012). Yet, mate choice for motor signals may also affect the evolution of overall mate motor performance (Byers et al., 2010; Clark, 2012; Mowles & Ord, 2012; Ryan, 1988; Ryan & Keddy-Hector, 1992). Numerous studies have shown that mate choice could drive the evolution of motor signals, but evidence for a correlated effect on overall motor performance is still lacking (Byers et al., 2010; Fusani, Barske, Day, Fuxjager, & Schlinger, 2014; Mowles & Ord, 2012).

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A suitable approach to investigate this question is to determine how mate choice affects a motor signal over evolutionary time, and then examine whether these changes also results in changes in aspects of overall motor performance. As a widely studied acoustic mating signal, the pulse production rate of *Drosophila* male courtship song is a prime candidate for such a study, for multiple reasons. First, *Drosophila* courtship song consists of a series of repeated pulses created by rapid wing vibrations, obtained via high-speed contractions of thoracic muscles (Ewing, 1979; Ewing, 1977; Shirangi, Stern, & Truman, 2013). The rate at which these pulses are produced (commonly reported as the interpulse interval, or IPI, representing the inverse of pulse rate) is thus likely to be a physically challenging motor trait. Next, the song pulse rate is a key target of female choice in several *Drosophila* species. It is involved in the sexual isolation between *D. melanogaster* and *D. simulans*, and in intraspecific mate choice in *D. melanogaster*, *D. montana* and *D. pseudoobscura* (Bennet-Clark & Ewing, 1969; Debelle, Ritchie, & Snook, 2014; Kyriacou & Hall, 1982; Ritchie, Halsey, & Gleason, 1999; Veltsos, Wicker-Thomas, Butlin, Hoikkala, & Ritchie, 2012; Williams, Blouin, & Noor, 2001). Then, the fact that song pulse rate is a target of female choice has been further demonstrated by showing the coevolution of pulse rate and female preference for pulse rate in experimental populations of *D. pseudoobscura* (Debelle et al., 2014). Finally, a direct action of male-male
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competition on pulse rate evolution is improbable. Courtship song is a near-field acoustic

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signal produced within 2.5-5mm of the female's head (Bennet-Clark, 1971, 1998), rendering

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its accurate reception by surrounding male competitors unlikely (Morley, Steinmann, Casas, &

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Robert, 2012). Hence, and although playing artificial courtship songs to males in playback

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experiments triggers male locomotion (Eberl & Tauber, 2002; von Schilcher, 1976), varying

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pulse rate does not have an effect on male courtship behaviour (Talyn & Dowse, 2004).

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Therefore, *Drosophila* song pulse rate has all the necessary characteristics to be a suitable

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candidate for this study.

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Yet, how song pulse rate relates to the evolution of male motor performance has so far not

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been investigated. This may be because the rate of *Drosophila* courtship song is commonly

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considered to be static, i.e. stable in time and independent of male motor capacities. Like

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many other acoustic signals, pulse rate is thus usually measured at a single time point or

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averaged over the entire courtship sequence (Tauber & Eberl, 2003; but see a notable

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exception in Arthur, Sunayama-Morita, Coen, Murthy, & Stern, 2013). That restricted view of

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this motor signal makes it impossible to know how much this trait depends on a male's motor

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capacities (Irschick & Garland, 2001). Another important aspect in studying the action of mate

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choice on motor performance evolution is to measure how the trait under mate choice is

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associated with other traits. By targeting pulse rate, mate choice could lead to a correlated

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response on other motor traits (Gerhardt & Brooks, 2009; Lande & Arnold, 1983), and

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therefore investigating these associations is essential to understand how mate choice may

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influence the evolution of motor performance beyond pulse rate.

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In this study, we examine closely the production of a motor signal involved in mate choice,

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and quantify how manipulating the opportunity for sexual selection (Jones, 2009) influences

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the evolution of motor performance that is displayed during courtship. For that purpose, we
study the production of *D. pseudoobscura* pulse rate over the duration of courtship, and
explore its response to a long-term experimental manipulation of the opportunity for sexual
selection in *D. pseudoobscura* populations (>100 generations of experimental evolution of
elevated polyandry or enforced monogamy). An analysis of these experimental lines
performed after 30 generations of selection has found that mean pulse rate had responded to
sexual selection manipulation, and had become faster in males from polyandrous lines
compared to monogamous lines (Snook, Robertson, Crudgington, & Ritchie, 2005). This
previous study was however performed on a restricted number of individuals and limited to
the examination of average pulse rate. As a consequence, this study did not allow
investigating potential differences in pulse rate production over time, which is necessary to
study overall motor performance. Here, we perform an in-depth study of pulse rate production
over time in our experimental lines after much longer evolution, and analyse the effect of
sexual selection manipulation on motor signalling.

Our main prediction is that an increased opportunity for sexual selection will lead to the
evolution of more intense male signalling characteristics and thus to an increased motor
performance. For this end, we look at the detailed structure of pulse rate production over
courtship time, to uncover potential sources of motor performance difference between males.
We then compare pulse rate production between the sexual selection treatments, to study
whether pulse rate production responded to sexual selection manipulation. Finally, we
examine associations between pulse rate and other motor courtship traits, to test whether
pulse rate may be correlated with overall courtship vigour.

121 METHODS
123 The courtship behaviour of *D. pseudoobscura* has been described in detail elsewhere (Brown,
124 1964; Ewing & Bennet-Clark, 1968). Courtship song is produced by the vibration of one or
125 both male wing(s), and consists of two main components: a low-repetition rate song (LRR)
126 and a high-repetition rate song (HRR) (Fig. 1). LRR consists of high-amplitude polycyclic
127 pulses and is generally produced first, while the male orients in the direction of the female and
128 approaches her, by flicking one or both wing(s) in a scissoring movement. Once the male has
129 reached the female, he extends the wing that is nearest the female's head to 90° and vibrates
130 it rapidly, producing a burst of HRR, characterised by a high number of low-amplitude
131 polycyclic pulses and an increase in pulse rate (i.e. a shorter duration between two
132 consecutive pulses in a burst of song, and thus a shorter interpulse interval). The male will
133 then generally attempt to mount the female and copulate. If the female refuses to mate, the
134 male will start another courtship sequence, including another round of song bursts. As HRR
135 pulse rate is the main target of female preference in this species (Debelle et al., 2014; Snook
136 et al., 2005; Williams et al., 2001), we focus on HRR song in this study (but provide a similar
137 analysis of LRR song in Appendix A).

139 An ancestral wild-caught population of *D. pseudoobscura*, a naturally polyandrous species
140 (more than 80% of wild-caught females have been shown to be inseminated by up to two
141 males at any given time; Cobbs, 1977), was used to create the selection lines. The
142 establishment and maintenance of the selection lines are described in detail elsewhere
143 (Crudgington, Beckerman, Brüstle, Green, & Snook, 2005). In brief, from an ancestral
144 population derived from Tucson (Arizona, US), 4 replicates (replicate 1, 2, 3 and 4) of two
sexual selection treatments were initiated. To modify the opportunity for sexual selection at each generation, adult sex-ratio in vials is manipulated by either confining one female with a single male ('monogamy' treatment; **M**) or one female with 6 males ('elevated polyandry' treatment; **E**) in vials. Both intra- and inter-sexual selection are relaxed in the monogamy treatment whereas both types of sexual selection are increased in the polyandry treatment.
As previously reported, effective population size was successfully equalized between the treatments (Ne>100 for all the populations; Snook, Brüstle, & Slate, 2009). At each generation and in each population independently, offspring are collected and then pooled together. A random sample of this pool is used to establish the next generation using the appropriate sex-ratios. This protocol thus proportionally reflects the relative offspring production across all families. Standard vials (2.5mm x 80mm) are used to maintain the selection lines, with a 28-day generation time. Bottles (57 mm x 132 mm) are used to maintain the ancestral population, with an equal sex-ratio of adult flies. Therefore, a total of 8 selection lines (M1, M2, M3, M4 and E1, E2, E3, E4) and one ancestral population are maintained and kept at 22°C on a 12L:12D cycle, using standard food media and added live yeast.

## 161 *Experimental Flies*

The flies used in this experiment were from the following generations: 111 and 112 for E1 and M1, 110 and 111 for E2 and M2, 109 and 110 for E3 and M3, 107 and 108 for E4 and M4. To generate the experimental flies, 50 reproductively mature adults of each selection line (25 males and 25 females) were used as parents and kept in mass-cultures, providing a common mating set up for the parents of both sexual selection treatments. The resulting larvae were raised in controlled density vials (100 first instar larvae per food vial), to standardize the larval rearing environment and relax selection. The flies were collected and sexed on the day of
169 emergence, using CO₂ anaesthetisation. Males from each population were kept in yeasted
170 food vials of 10 individuals from the day of emergence to day 4, and then transferred to
171 individual yeasted food vials the day before the recording. We used ancestral females for
172 male courtship song recording to standardise female response. Ancestral females were
173 collected and kept in vials of 10 individuals until used for the song recording experiment.
174 Ancestral females were mated to ancestral males the day before the experiment to reduce
175 their receptivity and prevent them from mating with the focal recorded male within the 5
176 minutes of the trial. Female receptivity is drastically reduced in the 24 hours following a
177 mating, and thus the probability of remating for the ancestral females used in this experiment
178 would be nearly zero (Crudgington et al., 2005; Snook, 1998). This method forces males to
179 continuously court females, therefore facilitating detailed study of song production over time.
180 All males and females used in this experiment were 5 days old and thus reproductively
181 mature (Snook & Markow, 2001). Henceforth, reference to polyandrous or monogamous does
182 not mean current mating situation in any experiments, but refers to the experimental sexual
183 selection treatment from which flies are derived.

184 *Courtship Song Recording*

185 Recordings were performed during the flies' morning photoperiod (Noor, 1998). Courtship
186 song was recorded by confining one virgin selection line male with a mated ancestral female
187 for 5 minutes in a transparent chamber (15 mm x 4 mm) in an Insectavox (Gorczyca & Hall,
188 1987). Recordings took place over the course of 12 days. All 8 lines were randomised across
189 and within days of recording. Each male was only recorded once, and 60 males were
190 recorded per selection line. The Insectavox was connected to a Toshiba Satellite Pro S300-
191 117 laptop, and sound was recorded using Audacity (v. 1.3.11). All songs were digitised after
192 filtering with a Fern EF5-04 filter, band-passed between 100 and 800 Hz. After the
experiments, recordings were manually prepared for software analysis by silencing parts of
the recording without song using Audacity (v. 1.3.11). Recordings were then analysed using a
custom script from the software DataView (Heitler, 2007), allowing the detection of the
position of each 'song event' (pulses and bursts) in a recording. Intrapulse frequency for both
LRR and HRR songs was obtained using a fast Fourier Transform (FFT) in DataView (FFT
duration=16ms, FFT window=hamming, percentage overlap=50%).

199 *Temperature and Body Size*

200 To understand more extensively how pulse rate is related to male motor capacities, it is
201 informative to examine how it covaries with two key bioenergetic factors that can affect
202 acoustic communication in insects: temperature and body size (Bailey, 1991; Bennett, 1990;
203 Gillooly & Ophir, 2010). Temperature - which strongly influences muscle contraction rate - is
204 tightly associated with motor power and endurance in ectotherms via its effect on metabolic
205 rate (Gillooly, Brown, West, Savage, & Charnov, 2001), and has a major impact on the
206 temporal components of acoustic signals in insects (Bailey, 1991), including *Drosophila*
207 courtship song traits (Noor & Aquadro, 1998; Ritchie & Kyriacou, 1994; Ritchie & Gleason,
208 1995; Ritchie, Saarikettu, Livingstone, & Hoikkala, 2001). Likewise, body size - a target of
209 sexual selection - is positively correlated with motor performance, notably due to the
210 increased power provided by larger muscles (Biewener, 2003; Carrier, 1996). Thus, including
211 these variables in our analyses will give a better understanding of how much pulse rate
212 production depends on male motor capacities, and thus of how the physiological properties of
213 *Drosophila* courtship song can have an impact on its evolution as a sexual signal.

214 As the light within the Insectavox generates inevitable random small variations in
215 temperature, we examine in detail how song traits vary with these minor changes in
temperature. Temperature was measured within the chamber every 10 seconds (+-0.01C)
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217 using a Testo 735-1 thermometer (Testo Limited, United Kingdom) and recorded for each
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burst of song in each recording. This temperature variation was then included as a covariate
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in the song analyses (temperature was either calculated for each burst in the case of HRR
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pulse rate, or averaged over all bursts for the other traits).

To estimate how body size could associate with pulse rate production, the size of the singing
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male was included in the analyses. The length of wing vein IV of each individual was
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measured after the experiment (wing vein length has been shown to be a good estimator of
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body size in *Drosophila* species, (e.g. Crudgington et al., 2005; Gilchrist, Huey, & Serra,
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2001; Robertson & Reeve, 1952; Sokoloff, 1966). Wings were mounted in a 30% glycerol-
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70% ethanol medium, images taken using a Motic camera and Motic Images Plus 2.0
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software (Motic Asia, Hong Kong) and then measured with ImageJ (v. 1.44e; Abramoff,
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Magalhães, & Ram, 2004).
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229 *Courtship Traits Analysis*

The different courtship traits analysed in this study are represented in Fig. 1. All the statistical
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analyses were performed in R (v. 3.3.2; R Development Core Team, 2005).
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We first tested for differences between the sexual selection treatments in body size and in
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their probability of producing song. As HRR interpulse interval (i.e. the inverse of pulse rate) is
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not constant over time but lengthens as courtship time increases (see Fig. B1 in Appendix B),
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we then conducted a detailed analysis of pulse rate production over courtship time, and
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compared pulse rate production between treatments. Finally, we performed multivariate
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analyses on all courtship traits to study phenotypic correlations between pulse rate and other
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courtship traits, and to test whether sexual selection manipulation modified these associations.

*Differences In Body Size and Singing Probability Between The Sexual Selection Treatments:* Potential differences in body size between the sexual selection treatments were analysed using a univariate linear mixed model (LMM), in which the sexual selection treatment of the recorded male (E or M) was included as a fixed effect, and the male replicate population (M1, M2, M3, M4, E1, E2, E3 or E4) included as a Gaussian random effect nested within sexual selection treatment. The model was fitted using maximum likelihood estimation, with a Gaussian error distribution. The difference in the probability of singing (i.e. the probability of a male producing at least one burst of HRR during the 5-min recording) between the sexual selection treatments was analysed using the same model structure but fitted a generalized linear mixed model (GLMM) for the binomial family. Both models were fitted using the package *spaMM* (Rousset & Ferdy, 2014) and estimates were compared to zero using parametric bootstraps which were consistent with results from model comparison using asymptotic likelihood ratio tests.

*Detailed Analysis Of Pulse Rate Production Over Time:* To distinguish between HRR interpulse and interburst interval (i.e. the interval of time between the last pulse of a burst and the first pulse of the following burst), an upper threshold was determined visually by plotting the distribution of the duration between two pulses (threshold = 55 ms; the average HRR interpulse interval is approximately 38 ms in *D. pseudoobscura*, Noor & Aquadro, 1998; Snook et al., 2005). To allow sufficient HRR interpulse interval values for each burst, we only included recordings with at least 10 interpulse interval values (i.e. the overall average number of HRR pulses per burst for both E and M males is 17; see Figure B2 for more details).
Variation in individual interpulse interval values along the courtship sequence was analysed by fitting a univariate LMM, using the function glmmPQL() of the MASS package (Venables & Ripley, 2002). This enables correcting for temporal autocorrelation between consecutive interpulse interval values within a burst. We thus included in the model a fourth-order autoregressive moving-average (corARMA) function for autocorrelation, using the pulse position in a burst (i.e. 1, 2, 3, etc.) as a time covariate, and the burst identity (1735 levels) nested within replicate (8 levels) as a grouping factor (nlme package; Pinheiro, Bates, DebRoy, Sarkar, & R Core Team, 2016). We also included two covariates indicating the position of the interpulse interval value within the courtship sequence, the burst position in the recording (i.e. 1, 2, 3, etc.) and the pulse position within a burst (i.e. 1, 2, 3, etc.), to test for a lengthening of interpulse interval over courtship duration (both within bursts and along bursts; see Fig. 1 for more details). The interactions between sexual selection treatment and the two event position covariates (burst position and pulse position) were included in the model, as well as their three-way interaction. This allowed us to assess how interpulse interval variation changes depending on the quantity of song already produced, and also to test whether interpulse interval variation over time is consistent between the two treatments. The interaction between temperature and burst position was also added, to test for an effect of temperature on interpulse interval lengthening over time (the interaction between temperature and pulse position in the burst could not be included in the model, as the mean duration of a burst, <3s, did not allow enough time for the recorded temperature to vary). The significance of the different fixed effects was extracted from the summary table of the glmmPQL fit, which provides the t-test results comparing estimates to zero. The same pulse rate production model was also fitted while including individual body size as an additional covariate (see Table D1 in Appendix D).
Multivariate Response Of Courtship Song To Sexual Selection Treatment: Because multivariate analyses require the different dependent variables to present the same number of observations, we performed the multivariate analysis using only the mean interpulse interval value of the first HRR burst produced (E and M males produced on average 14 bursts of HRR song in a recording; see Figure B2 for more details). Performing such averaging also precludes the need to consider the temporal autocorrelation that exists between successive pulses. To analyse whether interpulse interval and the other courtship traits jointly responded to sexual selection manipulation, we fitted a multivariate LMM on song data. In a multivariate LMM, the different response variables are transformed into a single univariate response variable by creating a vector that considers all observations across the different response variables sequentially (Christensen, 2001). A fixed effect factor is then used to indicate the correspondence between these observations and the original response variables. We assessed the fixed effects of the mean temperature during a recording and sexual selection treatment on five courtship traits: the mean interpulse interval of the first burst of song, the mean amplitude, the mean intrapulse frequency, the total number of bursts produced, and the singing latency (i.e. the time it took a male to produce its first burst of song). All response variables were log-transformed for normalization and then converted to z-scores, to facilitate model convergence. The estimates we provide in the tables of this study correspond to the direct output from the model fit. In the text, we untransformed the estimates back to the original scale of the response variable. To do this, we calculated the exponential of the sum of (1) the product of the standard deviation of the log of the original variable by the corresponding estimate (2) the log of the mean of the original variable.

The model was fitted using the *MCMCglmm* package (Hadfield, 2010). We ran MCMC chains for 100,000 iterations (burn-in phase), followed by five million iterations during which
parameter estimates were sampled every 5000 iterations. This sampling scheme resulted in 309 1000 recorded estimate values for each parameter and for each model. This was sufficient to 310 ensure that the autocorrelation between successive estimates was always lower than ±0.07. 311 All tests on estimates or quantities derived from estimates (e.g. correlations, see below) for 312 this model are based on the analysis of the distribution of the 1000 records associated with a 313 given parameter. Details about the specification of the prior distributions are given in 314 Appendix C. 315

We allowed for the effects of the different covariates to differ between courtship traits. The 316 number of estimated fixed-effect parameters was thus 15 ([1+2]x5). We estimated the 317 variances and covariances between the response courtship traits using random effects. We 318 computed these covariance matrices for each selection treatment (i.e. [5 variances + 10 319 different covariances]x2 = 30 (co)variance). We also estimated the variance between 320 replicates separately for each courtship trait (i.e. 5 variances) considering the identity of the 321 replicate as a random effect. We assumed the covariance between model residuals to be null, 322 as no dependence between observations is expected with the random structure considered. 323 The significance of the different fixed effects was extracted from the summary table of the 324 MCMCglmm fit. Here, the p-value is computed as twice the minimum between the 325 probabilities that estimates sampled along the MCMC chains are either greater or lower than 326 zero. The same model was also run while including individual body size as an additional 327 covariate (see Table D2 in Appendix D), with 20 estimated fixed-effect parameters 328 ([1+1+2]x5). 329

Estimating the variances and covariances of courtship traits allowed us to calculate the 330 correlations between courtship traits for each treatment. Using this approach offers the 331 advantage of estimating correlations that are not confounded by the variables included in the 332
model as fixed (e.g. temperature) or random effects (e.g. the replicate). We then examined
the significance of each individual correlation estimate, and tested for differences between the
treatments, to examine whether the associations between courtship traits have changed as a
result of sexual selection treatment. The significance test of these correlations was based on
the analysis of estimates along the MCMC chains, as explained previously.

In all figures, the mean fixed effect estimates, hereafter referred as "predicted values" of the
mixed models, are represented. Predicted values were adjusted to 22°C, the temperature at
which all populations are maintained. The 95% confidence intervals were computed for the
two univariate LMMs as ±1.96 standard errors around the predicted values, with the standard
error being derived from the covariance matrix of parameter estimates for fixed effects. For
the GLMM, confidence intervals were computed similarly, but at the scale of the linear
predictor (i.e. before the transformation from logit to probabilities). For the multivariate LMM,
confidence intervals are computed as quantiles of the posterior distribution of parameter
estimates along the MCMC chains. Although technically, intervals obtained this way present
statistical properties that can differ from confidence intervals (e.g. Rousset, Gouy, Martinez-
Almoyna, & Courtiol, 2017; they are called credibility intervals), we will refer to both types as
being confidence intervals.

## Predictions

First, given that energetically-costly repeated motor signals are predicted to advertise the
signaller's condition (Mowles & Ord, 2012), we expect pulse rate to depend on courtship
effort, and thus on the quantity of song already produced by a male. For similar reasons, as
motor performance should correlate positively with both temperature and body size,
particularly for traits likely to act as indicators of mate condition (Clark, 2012), we also expect
pulse rate to be associated with temperature and body size. Then, if pulse rate production has been affected by sexual selection manipulation, we expect to observe faster pulse rates and a shallower slope of decline in pulse rate (i.e. a less pronounced lengthening in interpulse interval) in polyandrous males compared to monogamous males. Finally, for pulse rate to be used as an indicator of motor performance, fast pulse rates should be positively correlated with overall courtship vigour estimates (i.e. here estimated by the other motor courtship traits measured).

## Ethical Note

Our design minimised the stress imposed to the individuals used in this experiment. Stress at the larval stage was prevented by controlling for larval density. At adulthood, individuals were transferred in new vials with fresh food and medium adult density. A mouth aspirator was used to gently handle live individuals throughout all the steps of the experiment. The experimental time was only 5 minutes long, after which flies were anaesthetised with CO₂ and rapidly killed in ethanol for wing measurement.

## RESULTS

### Differences In HRR Singing Probability Between The Sexual Selection Treatments

The probability of singing differs significantly between the sexual selection treatments (Table 1), with monogamous males having a lower probability of singing than polyandrous males (Fig. 2).

### Detailed Analysis Of HRR Pulse Rate Production Over Time

This analysis, based on all bursts produced, identifies changes in interpulse interval variation between, and also within, bouts of courtship. The interpulse interval value lengthens between
consecutive bursts, meaning that the rate at which males produce pulses decreases more and more as the male produces song (Table 2 and Fig. 3). Interpulse interval also lengthens within a burst, meaning that pulse rate progressively decreases during a burst too (Table 2 and Fig. 4).

*Temperature:* As expected, temperature strongly associates with courtship traits (Tables 2 and 3). Interpulse interval is negatively associated with temperature, meaning that interpulse interval is longer at lower temperatures, as indicated by both the pulse rate production LMM and the multivariate LMM. In the latter case, interpulse interval shortens by 0.32ms (95% C.I. = -0.07 - -0.57, *P*=0.012) when temperature increases by 1°C (Table 3).

The pulse rate production LMM (Table 2, and Table D1 for its equivalent with body size included) also shows that the progressive shortening observed in interpulse interval is strongly correlated with temperature, with colder recording temperatures being associated with an even more pronounced lengthening in interpulse interval over courtship time (i.e. a steeper decrease in pulse rate; Fig. 5a).

*Body Size:* Males from polyandrous lines are larger on average than males from monogamous lines (Table 1 and Fig. 5b). When body size is included in the pulse rate production LMM (Table D1), we observe a negative effect of body size on interpulse interval. Body size significantly influences interpulse interval both within and between bursts, meaning that larger males produce song with a shorter interpulse interval and maintained this short interpulse interval for a longer time than smaller males (Table D1 and Fig. 5c).

The multivariate LMM also reveals that, when body size is included in the model, interpulse interval shortens with increasing body size, with an increase in wing size of 1 standard deviation being associated with a reduction of 0.31ms in interpulse interval (95% C.I. = -0.03
401 – -0.62, *P*=0.046; Table D2). Amplitude increases with increasing body size as well, with an
402 increase in wing size of 1 standard deviation being associated with an increase in amplitude
403 of 11.8 units (95% C.I. = 2.2 – 21.4, *P*=0.024; Table D2).

404 Evolutionary Response to Sexual Selection Manipulation

405 The pulse rate production LMM shows a significant effect of sexual section treatment on
406 interpulse interval, with polyandrous males producing a shorter interpulse interval (i.e. a faster
407 pulse rate) than monogamous males (Table 2 and Fig. 3 & 4). The model also shows a
408 significant interaction between sexual selection treatment and the quantity of song already
409 produced by a male (i.e. the burst and pulse positions in the courtship sequence), showing
410 that the decrease in pulse rate in polyandrous males is shallower than in monogamous males.
411 Therefore, pulse rate differs between the sexual selection treatments, and this difference
412 gradually widens the more males beat their wings to produce song.

413 Although body size is significantly different between the sexual selection treatments, including
414 body size in the pulse rate production LMM shows a difference between the sexual selection
415 treatments that is independent from the effect mediated by body size, with polyandrous males
416 showing again more endurance than monogamous males (Table D1).

417 Analysis of the Associations Between Courtship Traits

418 The multivariate LMM shows that polyandrous males start to produce song earlier than
419 monogamous males (mean difference in song latency: 5.7s; 95% C.I.= 3.5 – 7.7, *P*=0.001;
420 Table 3). All other courtship traits do not show a significant difference between the sexual
421 selection treatments (Table 3).
Table 4 presents the correlations (r) between courtship traits for each sexual selection treatment extracted from the fit of the multivariate LMM (Table 3), while Table 5 examines whether these associations differ between the sexual selection treatments (r<sub>E</sub> - r<sub>M</sub>). The equivalent of these two tables for the multivariate LMM with body size included as a covariate are shown in the Appendix D (Table D3 and D4). Two out of the 10 correlations between courtship traits changed as a result of selection (Fig. 6 and Table 5), and both of them are associated with interpulse interval. Interpulse interval is correlated with almost all other courtship traits in the polyandry treatment (i.e. with amplitude, latency and the total number of bursts produced; Table 4), but only with amplitude in the monogamy treatment. Faster pulse rates are thus associated with shorter singing latencies, louder songs, and more bursts produced.

The multivariate LMM identified three significant associations between courtship traits that do not differ between sexual selection treatments (compare Table 4 to Table 5). In addition to the correlation between interpulse interval and amplitude, it found similar associations between the sexual selection treatments between intrapulse frequency and amplitude, and between latency and the total number of bursts produced (Table 4). The last associations found were a small positive correlation between amplitude and the total number of bursts produced, and between amplitude and latency, however these were only significant for polyandrous males, and did not significantly differ between the sexual selection treatments (Table 5).

## DISCUSSION

In this study, we tested the hypothesis that mate choice influences the evolution of motor performance and predicted improved motor performance in populations subjected to more intense sexual selection. We performed a detailed analysis of the production of *Drosophila*
pseudoobscura song pulse rate, a motor signal under mate choice in this species. We also analysed the response of this motor signal to sexual selection manipulation via experimental evolution. We showed that song pulse rate decreases with the amount of song a male has already produced, and is associated with body size and recording temperature, indicating a potential for pulse rate to act as an indicator of male condition. Consistent with this, manipulating the opportunity for sexual selection led to the evolution of faster pulse rates and improved song production endurance in males from polyandrous lines compared to males from monogamous lines. Finally, we showed that pulse rate is correlated with estimates of overall courtship vigour, particularly in polyandrous males. In total, these results suggest that selection on song pulse rate by females led to the evolution of increased courtship vigour displayed during courtship, indicating a potential correlated response of overall male motor capacities.

## 457 *Pulse Rate Production*

Our results show that pulse rate is not constant over courtship duration, but progressively declines as a male continues to beat his wings. Although this pattern has previously been reported in the courtship songs of two other *Drosophila* species (*D. melanogaster*: Bernstein, Neumann, & Hall, 1992; Dow, 1978; Ewing, 1983; Wilson, Burnet, Eastwood, & Connolly, 1976; *D. simulans*: Bernstein et al., 1992), its relevance and implications for sexual selection have not yet been considered. In *D. pseudoobscura*, pulse rate appears to decrease progressively both within a burst of song, and also along the burst sequence. The pattern observed in our study suggests that males start producing song with a fast pulse rate but cannot sustain this as courtship progresses (and particularly for males who evolved under monogamy conditions). Repetitive signals are thought to provide a useful measure of mate quality to the receivers, both via the average rate at which they are produced and the
variation of this rate (i.e. increase or decrease) over courtship time (Kotiaho et al., 1998; Mowles & Ord, 2012). As a song with a fast pulse rate can be a physically challenging task, requiring both sustained motor power and motor endurance and thus pushing males to their maximum capacities, variation in the ability of males to maintain a given pulse rate over time has the potential to accurately reflect mate condition.

Pulse rate production is associated with both temperature and body size variation. The effect of temperature on acoustic signalling is common through its effect on metabolic rate and has already been shown in many species (Gillooly et al., 2001; Gillooly & Ophir, 2010), including *Drosophila* species (Noor & Aquadro 1998; Ritchie & Gleason, 1995; Ritchie & Kyriacou, 1994; Ritchie et al., 2001). In addition to this effect, we show that temperature is not only associated with mean pulse rate, but also with pulse rate decrease over time, indicating that both power output and endurance are temperature-dependent. These results suggest that pulse rate probably strongly relies on male physiological state (Lailvaux & Irschick, 2006). Pulse rate also positively correlates with body size, this effect being unsurprising as motor power often positively covaries with body size (Biewener, 2003; Carrier, 1996). The influence of body size on pulse rate has rarely been investigated in *Drosophila* species, sometimes only via correlations between body size and ‘raw’ pulse rate data (i.e. not temperature-corrected), which failed to find an association between size and rate (Hoikkala, Aspi, & Suvanto, 1998; Partridge, Ewing, & Chandler, 1987). The positive influence of body size on pulse rate found here indicates that larger males are able to produce a faster pulse rate than smaller males, suggesting that body size influences motor power. This effect could potentially be due to variation in thoracic muscle size, and lead to a higher power output (i.e. a faster pulse rate) of larger males. Indeed, thorax volume is positively correlated with flight wing-beat frequency in *D. melanogaster* (Curtsinger & Laurie-Ahlberg, 1981). Overall, these results suggest pulse
rate has the ability to reflect both male motor power and endurance to females, potentially
making it an evolutionary driver of overall male motor capacities (Clark, 2012).

### *Effect of Sexual Selection on Courtship Song Evolution*

Males from polyandrous lines are not only more likely to produce song and produce song faster, but they are also able to maintain a fast rate for longer than males from the monogamous lines, demonstrating that manipulating sexual selection had a significant impact on male motor performance during courtship. Our results are consistent with previous work suggesting that polyandrous females prefer faster male pulse rates (Debelle et al., 2014; Williams et al., 2001). Signals with an increased energy content have been shown to be under directional female preference in several species (e.g. in frogs: Gerhardt & Brooks, 2009; Ryan, 1988; in wolf spiders: Shamble, Wilgers, Swoboda, & Hebets, 2009; in crickets: Simmons, Thomas, Simmons, & Zuk, 2013), with females typically preferring louder song, higher calling rate and higher pulse repetition rate (Clark, 2012; Mowles & Ord, 2012). The fact that the ability to sustain a fast pulse rate has been affected by sexual selection manipulation suggests that selection by females towards fast pulse rates led to the evolution of males delivering songs with increased motor power and sustained intensity (i.e. more endurance), and indicates that pulse rate may be used as an indicator of male motor performance by females.

We find, after c.a. 110 generations of selection, a difference in average pulse rate in the same direction than in the preliminary song study (conducted after 30 generations of selection; Snook et al., 2005). The comparable difference in pulse rate between males from polyandrous and monogamous lines after a further 80 generations of selection (1.54 ms between the polyandry and monogamy treatments in Snook et al., 2005; 1.57 ms in the
current study, see Table 2) could indicate that pulse rate evolution has reached stable
equilibrium conditions between sexual and viability selection (Hine, McGuigan, & Blows,
2011; Kirkpatrick, 1996), but could also mean that genetic variation for faster pulse rates has
been depleted in the polyandrous lines. Two studies using artificial selection on pulse rate in
*D. melanogaster* showed a lower evolutionary response towards faster pulse rates (Ritchie &
Kyriacou, 1996; Turner & Miller, 2012), suggesting reduced expressed genetic variation for
fast pulse rates in this environment, an expected result if selection has persistently acted in
this direction.

Male body size responded to the variation in sexual selection opportunity, with males from the
polyandrous lines being overall larger than males from the monogamous lines. Body size
commonly responds to pre-copulatory sexual selection among species (Andersson, 1996;
Blanckenhorn, 2000; Thornhill & Alcock, 1983) and affects male mating success in several
*Drosophila* species (including *D. pseudoobscura*), with larger males winning more aggressive
encounters, delivering more courtship and mating faster (Ewing, 1961; Partridge, Hoffmann, &
Jones, 1987; Partridge et al., 1987; Partridge & Farquhar, 1983). As body size also influences
pulse rate, any pulse rate difference between the experimental evolution treatments could
thus be explained by size differences. However, even after controlling for the effects of body
size (cf. Appendix A and D), sexual selection treatments still differ in their pulse rate
production pattern, indicating that traits other than body size have diverged between the
treatments and contribute to the differences in motor signalling between the treatments.

### *Mate Choice As An Evolutionary Mechanism Driving The Evolution Of Motor Performance*

Males from polyandrous lines are more vigorous than males from monogamous lines. Indeed,
males from polyandrous lines have an enhanced mating capacity and a higher courtship
frequency relative to males from monogamous lines (Crudgington, Fellows, & Snook, 2010; 539 Crudgington, Fellows, Badcock, & Snook, 2009). Our study also shows that males from 540 polyandrous lines start producing song faster, produce a faster pulse rate, and have a higher 541 endurance than males from monogamous lines. In theory, male-male competition could 542 participate to this observed increase in male motor capacities. A direct effect of male-male 543 competition on the evolution of pulse rate seems however unlikely, as courtship song is a 544 near-field sound (Bennet-Clark, 1971, 1998) and pulse rate value does not affect other males 545 behaviour (Talyn & Dowse, 2004). Conversely, pulse rate affects male mating success in no- 546 choice assays in this species (Williams et al., 2001), pulse rate coevolved with female 547 preference for pulse rate in our experimental lines (Debelle et al., 2014), and pulse rate is 548 correlated with other courtship motor traits. This suggests that the action of mate choice on 549 pulse rate is actively involved in the observed evolutionary motor changes in our experimental 550 lines. 551

Drosophila courtship song has so far only been linked to non-motor selective benefits (i.e. 552 high intrapulse frequency in *D. montana* is associated with a higher male mating success and 553 a higher offspring survival; Hoikkala et al., 1998; Ritchie et al., 2001). Our results support the 554 idea that *Drosophila* courtship song could also signal motor performance. Our analysis 555 focused on courtship-related traits, however motor performance expressed during courtship is 556 likely to reflect an individual's overall motor performance (Byers et al., 2010; Clark, 2012; 557 Lailvaux & Irschick, 2006; Oufiero & Garland, 2007). In a context of strong sexual selection, 558 the selection of fast singing males by females could thus also influence the evolution of other 559 motor characteristics (e.g. flying ability, competitive ability, etc.; Byers et al., 2010). 560

Contrary to what we observe in the polyandrous lines, reducing the opportunity for sexual 561 selection in the monogamous lines is associated with lower singing probability, a longer 562
563 singing latency, and the inability to maintain a fast pulse rate. This suggests that these traits
564 are costly and could be selected against in the absence of mating competition. Males from
565 monogamous lines also have a lower courtship frequency compared to males from
566 polyandrous lines (Crudgington et al., 2010). As courting (without mating) has been shown to
567 reduce male longevity in *D. melanogaster* (Cordts & Partridge, 1996), these results overall
568 suggest that intense courtship song could impose an important fitness cost to males in a
569 monogamous context, which may have resulted in the reduced investment in courtship song
570 observed in populations under relaxed sexual selection (Crudgington et al., 2010;
571 Crudgington et al., 2005).

572 In conclusion, our results suggest that the pulse rate has the potential to be an indicator of
573 male condition to females, and that the action of female choice on this motor signal affected
574 male motor performance during courtship in our replicated experimental populations. In
575 natural populations, female selection of male courtship motor performance could thus have an
576 impact on the evolution of motor performance exhibited in contexts other than courtship. This
577 work contributes to the limited number of studies providing evidence that sexual selection via
578 mate choice of motor signals may also drive the evolution of mate motor performance (Byers
579 et al., 2010; Mowles & Ord, 2012). Further work in this and other systems should quantify the
580 selective benefits gained by an increased motor performance in mating and non-mating
581 contexts (e.g. standard locomotion, foraging, escaping predators), and investigate what
582 evolutionary changes lead to enhanced motor signals (e.g. morphological, anatomical,
583 physiological), to gain a better understanding of the influence of sexual selection on the
584 evolution of motor performance.

585
586 REFERENCES

587 Abramoff, M. D., Magalhães, P. J., & Ram, S. J. (2004). Image processing with ImageJ.

588 *Biophotonics International*, **11**(7), 36-42.

589 Albert, A., & Anderson, J. A. (1984). On the existence of maximum likelihood estimates in
logistic regression models. *Biometrika*, **71**(1), 1-10. http://doi.org/10.1093/biomet/71.1.1

591 Andersson, M. B. (1996). Sexual selection. *Trends in Ecology & Evolution*, **11**(2), 53-58.

592 http://doi.org/10.1016/0169-5347(96)81042-1

593 Arthur, B. J., Sunayama-Morita, T., Coen, P., Murthy, M., & Stern, D. L. (2013). Multi-channel
594 acoustic recording and automated analysis of *Drosophila* courtship songs. *BMC Biology*,
595 **11**, 11. http://doi.org/10.1186/1741-7007-11-11

596 Bailey, W. J. (1991). *Acoustic Behaviour of Insects. An Evolutionary Perspective*. London:
597 Chapman and Hall.

598 Bennet-Clark, H. C. (1971). Acoustics of insect song. *Nature*, 255-259.

599 http://doi.org/10.1038/234255a0

600 Bennet-Clark, H. C. C. (1998). Size and scale effects as constraints in insect sound
601 communication. *Philosophical Transactions of the Royal Society B: Biological Sciences*,
602 353(1367), 407-419. http://doi.org/10.1098/rstb.1998.0219

603 Bennet-Clark, H. C., & Ewing, A. W. (1969). Pulse interval as a critical parameter in the
courtship song of *Drosophila melanogaster*. *Animal Behaviour*, **755-759**.

605 http://doi.org/doi:10.1016/S0003-3472(69)80023-0
606 Bennett, A. F. (1990). Thermal dependence of locomotor. *American Journal of Physiology*,
259, 253-258.

608 Bernstein, A. S., Neumann, E. K., & Hall, J. C. (1992). Temporal analysis of tone pulses
609 within the courtship songs of two sibling *Drosophila* species, their interspecific hybrid,
610 and behavioral mutants of *D. melanogaster* (Diptera: Drosophilidae). *Journal of Insect
611 *Behavior*, 5(1), 15-36. http://doi.org/10.1007/BF01049155

612 Biewener, A. A. (2003). *Animal locomotion*. New York: Oxford University Press.

613 Blanckenhorn, W. U. (2000). The evolution of body size: what keeps organisms small? *The
614 Quarterly Review of Biology*, 75(4), 385-407. http://doi.org/10.1086/393620

615 Bonduriansky, R. (2011). Sexual selection and conflict as engines of ecological diversification.
616 *The American Naturalist*, 178(6), 729-745. http://doi.org/10.1086/662665

617 Brown, R. G. B. (1964). Courtship behavior in the *Drosophila obscura* group. I: *D.
618 pseudoobscura*. *Behaviour*, 23(1-2), 61-106. http://doi.org/10.1163/156853964X00094

619 Byers, J., Hebets, E., & Podos, J. (2010). Female mate choice based upon male motor
620 performance. *Animal Behaviour*, 79(4), 771-778.
621 http://doi.org/10.1016/j.anbehav.2010.01.009

622 Carrier, D. R. (1996). Ontogenetic limits on locomotor performance. *Physiological Zoology*,
623 69(3), 467-488. http://doi.org/10.2307/30164211

624 Christensen, R. (2001). *Advanced Linear Modeling: Multivariate, Time Series, and Spatial
625 Data; Nonparametric Regression and Response Surface Maximization*. New York:
626 Springer.
627 Clark, C. J. (2012). The role of power versus energy in courtship: what is the "energetic cost"

628 of a courtship display? *Animal Behaviour*, 84(1), 269–277.

629 http://doi.org/10.1016/j.anbehav.2012.04.012

630 Cobbs, G. (1977). Multiple insemination and male sexual selection in natural population of

631 *Drosophila pseudoobscura*. *The American Naturalist*, 111(2), 641–656.

632 http://dx.doi.org/10.1086/283197

633 Cordts, R., & Partridge, L. (1996). Courtship reduces longevity of male *Drosophila*

634 melanogaster. *Animal Behaviour*, 52(2), 269–278. http://doi.org/10.1006/anbe.1996.0172

635 Crudgington, H. S., Beckerman, A. P., Brüstle, L., Green, K., & Snook, R. R. (2005).

636 Experimental removal and elevation of sexual selection: does sexual selection generate

637 manipulative males and resistant females? *The American Naturalist*, 165, S72--87.

638 http://doi.org/10.1086/429353

639 Crudgington, H. S., Fellows, S., Badcock, N. S., & Snook, R. R. (2009). Experimental

640 manipulation of sexual selection promotes greater male mating capacity but does not

641 alter sperm investment. *Evolution*, 63(4), 926–938. http://doi.org/10.1111/j.1558-

642 5646.2008.00601.x

643 Crudgington, H. S., Fellows, S., & Snook, R. R. (2010). Increased opportunity for sexual

644 conflict promotes harmful males with elevated courtship frequencies. *Journal of*

645 *Evolutionary Biology*, 23(2), 440–446. http://doi.org/10.1111/j.1420-9101.2009.01907.x

646 Curtsinger, J. W., & Laurie-Ahlberg, C. C. (1981). Genetic variability of flight metabolism in

647 *Drosophila melanogaster*. I. Characterization of power output during tethered flight.

648 *Genetics*, (6655), 549–564. http://dx.doi.org/10.1111/j.1570-7458.1995.tb01943.x
649 Darwin, C. (1859). *The Origin of Species by Means of Natural Selection Or the Preservation
650 of Favoured Races in the Struggle for Life*. London: Murray. London: Murray.

651 Darwin, C. (1871). *The Descent of Man, and Selection in Relation to Sex*. London: Murray.

652 Debelle, A., Ritchie, M. G., & Snook, R. R. (2014). Evolution of divergent female mating
653 preference in response to experimental sexual selection. *Evolution*, *68*(9), 2524–2533.
654 http://doi.org/10.1111/evo.12473

655 Dow, M. A. (1978). *Function and Organization of Courtship Behaviour in Drosophila*
656 melanogaster. PhD thesis, University of Edinburgh.

657 Eberl, D. F., & Tauber, E. (2002). The effect of male competition on the courtship song of
658 *Drosophila melanogaster*. *Journal of Insect Behavior*, *15*(1), 109–120.
659 http://doi.org/10.1023/A:1014488330548

660 Ewing, A. (1961). Body size and courtship behaviour in *Drosophila melanogaster*. *Animal
661 Behaviour*, *9*(1–2), 93–96. http://doi.org/10.1016/0003-3472(61)90055-0

662 Ewing, A. W. (1977). The neuromuscular basis of courtship song in *Drosophila*: The role of
663 the indirect flight muscles. *Journal of Comparative Physiology*, *119*(3), 249–265.
664 http://doi.org/10.1007/BF00656637

665 Ewing, A. W. (1979). The neuromuscular basis of courtship song in *Drosophila*: the role of the
666 direct and axillary wing muscles. *Journal of Comparative Physiology*, *130*(1), 87–93.
667 http://doi.org/10.1007/BF02582977

668 Ewing, A. W. (1983). Functional aspects of *Drosophila* courtship. *Biological Reviews*, *58*(2),
669 275–292. http://doi.org/10.1111/j.1469-185X.1983.tb00390.x
Ewing, A. W., & Bennet-Clark, H. C. (1968). The courtship songs of *Drosophila*. *Behaviour*, 31(3/4), 288–301. http://doi.org/10.1163/156853968X00298

Fusani, L., Barske, J., Day, L. D., Fuxjager, M. J., & Schlinger, B. A. (2014). Physiological control of elaborate male courtship: female choice for neuromuscular systems.
*Neuroscience and Biobehavioral Reviews*, 46(P4), 534–546.
http://doi.org/10.1016/j.neubiorev.2014.07.017

Gerhardt, H. C., & Brooks, R. (2009). Experimental analysis of multivariate female choice in gray treefrogs (*Hyla versicolor*): evidence for directional and stabilizing selection.
*Evolution*, 63(10), 2504–2512. http://doi.org/10.1111/j.1558-5646.2009.00746.x

Gilchrist, G. W., Huey, R. B., & Serra, L. (2001). Rapid evolution of wing size clines in Drosophila subobscura. *Genetica*, 112–113:273–286.
http://doi.org/10.1023/A:1013358931816

Gillooly, J. F., Brown, J. H., West, G. B., Savage, V. B., & Charnov, E. L. (2001). Effects of size and temperature on metabolic rate. *Science*, 293(5538), 2248–2251.
http://doi.org/10.1126/science.1061967

Gillooly, J. F., & Ophir, A. G. (2010). The energetic basis of acoustic communication.
*Proceedings of the Royal Society B: Biological Sciences*, 277(1686), 1325–1331.
http://doi.org/10.1098/rspb.2009.2134

Gorczyca, M., & Hall, J. C. (1987). The INSECTAVOX, an integrated device for recording and amplifying courtship songs of *Drosophila*. *Dros Inf Serv*, 66, 157–160.

Hadfield, J. D. (2010). MCMC Methods for Multi-Response Generalized Linear Mixed Models:
691 The MCMCglmm R Package. *Journal of Statistical Software*, 33(2), 1-22.

692 http://doi.org/10.18637/jss.v033.i02 R package version 2.24 cran.r-

693 project.org/package=MCMCglmm.

694 Heitler, W. J. (2007). DataView: a tutorial tool for data analysis. template-based spike sorting and frequency analysis. *Journal of Undergraduate Neuroscience Education*, 6(1), A1--7.

695 Hine, E., McGuigan, K., & Blows, M. W. (2011). Natural selection stops the evolution of male attractiveness. *Proceedings of the National Academy of Sciences of the United States of America*, 108(9), 3659-3664. http://doi.org/10.1073/pnas.1011876108

699 Hoikkala, A., Aspi, J., & Suvanto, L. (1998). Male courtship song frequency as an indicator of male genetic quality in an insect species, *Drosophila montana*. *Proceedings of the Royal Society B: Biological Sciences*, 265(1395), 503-508.
701 http://doi.org/10.1098/rspb.1998.0323

703 Husak, J. F., & Fox, S. F. (2008). Sexual selection on locomotor performance. *Evolutionary Ecology Research*, 213-228.

705 Irschick, D. J., & Garland, T. (2001). Integrating function and ecology in studies of adaptation: investigations of locomotor capacity as a model system. *Annual Review of Ecology and Systematics*, 32, 367-396. http://doi.org/10.1146/annurev.ecolsys.32.081501.114048

708 Irschick, D. J., Meyers, J. J., Husak, J. F., & Le Gaillard, J. F. (2008). How does selection operate on whole-organism functional performance capacities? A review and synthesis. *Evolutionary Ecology Research*, 10, 177-196.

711 Jones, A. G. (2009). On the opportunity for sexual selection, the Bateman gradient and the
712 maximum intensity of sexual selection. *Evolution*, 63(7), 1673–1684.

713 http://doi.org/10.1111/j.1558-5646.2009.00664.x

714 Kirkpatrick, M. (1996). Good genes and direct selection in the evolution of mating

715 preferences. *Evolution*, 50(6), 2125–2140. http://doi.org/10.2307/2410684

716 Kotiaho, J. S., Alatalo, R. V., Mappes, J., Nielsen, M. G., Parri, S., & Rivero, A. (1998).

717 Energetic costs of size and sexual signalling in a wolf spider. *Proceedings of the Royal*

718 Society B: Biological Sciences, 265(1411), 2203–2209.

719 http://doi.org/10.1098/rspb.1998.0560

720 Kyriacou, C. P., & Hall, J. C. (1982). The function of courtship song rhythms in *Drosophila*.

721 *Animal Behaviour*, 30(3), 794–801. http://doi.org/10.1016/S0003-3472(82)80152-8

722 Lailvaux, S. P., & Irschick, D. J. (2006). A functional perspective on sexual selection: insights

723 and future prospects. *Animal Behaviour*, 72(2), 263–273.

724 http://doi.org/10.1016/j.anbehav.2006.02.003

725 Lande, R., & Arnold, S. J. (1983). The measurement of selection on correlated characters.

726 *Evolution*, 37(6), 1210–1226.

727 Morley, E. L., Steinmann, T., Casas, J., & Robert, D. (2012). Directional cues in *Drosophila*

728 melanogaster audition: structure of acoustic flow and inter-antennal velocity differences.

729 *The Journal of Experimental Biology*, 215(14), 2405–2413.

730 http://doi.org/10.1242/jeb.068940

731 Mowles, S. L., & Ord, T. J. (2012). Repetitive signals and mate choice: insights from contest

732 theory. *Animal Behaviour*, 84(2), 295–304. http://doi.org/10.1016/j.anbehav.2012.05.015
733 Noor, M. A. F. (1998). Diurnal activity patterns of *Drosophila subobscura* and *D. pseudoobscura* in sympatric populations. *The American Midland Naturalist*, 140(1), 34–

734 pseudoobscura in sympatric populations. *The American Midland Naturalist*, 140(1), 34–

735 41. http://doi.org/10.1674/0003-0031(1998)140[0034:DAPODS]2.0.CO;2

736 Noor, M. A. F., & Aquadro, C. F. (1998). Courtship songs of *Drosophila pseudoobscura* and

737 *D. persimilis*: analysis of variation. *Animal Behaviour*, 56(1), 115–125.

738 http://doi.org/10.1046/j.1365-2540.2001.00811.x

739 Oufiero, C. E., & Garland, T. (2007). Evaluating performance costs of sexually selected traits.

740 *Functional Ecology*, 21(4), 676–689. http://doi.org/10.1111/j.1365-2435.2007.01259.x

741 Partridge, L., Ewing, A., & Chandler, A. (1987). Male size and mating success in *Drosophila*

742 melanogaster: the roles of male and female behaviour. *Animal Behaviour*, 35(2), 555–

743 562. http://doi.org/10.1016/S0003-3472(87)80281-6

744 Partridge, L., & Farquhar, M. (1983). Lifetime mating success of male fruitflies (*Drosophila*

745 melanogaster) is related to their size. *Animal Behaviour*, 31(3), 871–877.

746 http://doi.org/10.1016/S0003-3472(83)80242-5

747 Partridge, L., Hoffmann, A., & Jones, J. S. (1987). Male size and mating success in

748 *Drosophila melanogaster* and *D. pseudoobscura* under field conditions. *Animal*

749 *Behaviour*, 35(2), 468–476. http://doi.org/10.1016/S0003-3472(87)80272-5

750 Perry, G., Levering, K., Girard, I., & Garland, T. (2004). Locomotor performance and social

751 dominance in male *Anolis cristatellus*. *Animal Behaviour*, 67(1), 37–47.

752 http://doi.org/10.1016/j.anbehav.2003.02.003

753 Pinheiro, J., Bates, D., DebRoy, S., Sarkar, D., & R Core Team. (2016). nlme: Linear and
754 Nonlinear Mixed Effects Models. R package version 3.1-131 cran.r-project.org/package=nlme.

755 project.org/package=nlme.

756 R Development Core Team. (2005). R: A language and environment for statistical computing. R Foundation Statistical Computing.

758 Ritchie, M. G., & Gleason, J. M. (1995). Rapid evolution of courtship song pattern in *Drosophila willistoni* sibling species. *Journal of Evolutionary Biology*, 8(4), 463-479.
759 http://doi.org/10.1046/j.1420-9101.1995.8040463.x

760 http://doi.org/10.1046/j.1420-9101.1995.8040463.x

761 Ritchie, M. G., Halsey, E. J., & Gleason, J. M. (1999). *Drosophila* song as a species-specific mating signal and the behavioural importance of Kyriacou & Hall cycles in *D. melanogaster* song. *Animal Behaviour*, 58(3), 649-657.
762
763
764 http://doi.org/10.1006/anbe.1999.1167

764 http://doi.org/10.1006/anbe.1999.1167

765 Ritchie, M. G., & Kyriacou, C. P. (1996). Artificial selection for a courtship signal in *Drosophila melanogaster*. *Animal Behaviour*, 603-611.

766 melanogaster. Animal Behaviour, 603-611.

767 Ritchie, M. G. M. G., & Kyriacou, C. P. (1994). Genetic variability of courtship song in a population of *Drosophila melanogaster*. *Animal Behaviour*, 48(2), 425-434.
768
769 http://doi.org/10.1006/anbe.1994.1256

769 http://doi.org/10.1006/anbe.1994.1256

770 Ritchie, M. G., Saarikettu, M., Livingstone, S., & Hoikkala, A. (2001). Characterization of female preference functions for *Drosophila montana* courtship song and a test of the temperature coupling hypothesis. *Evolution*, 55(4), 721-727.
771
772
773 http://doi.org/10.1111/j.0014-3820.2001.tb00808.x

773 http://doi.org/10.1111/j.0014-3820.2001.tb00808.x

774 Robertson, F. W., & Reeve, E. C. R. (1952). Heterozygosity, environmental variation and
heterosis. *Nature*, 170(4320), 286. http://doi.org/10.1038/170286a0

Rousset, F., & Ferdy, J.-B. (2014). Testing environmental and genetic effects in the presence

of spatial autocorrelation. *Ecography*, 37(8), 781–790. http://doi.org/10.1111/ecog.00566

R package version 1.11-64 cran.r-project.org/package=spaMM.

Rousset, F., Gouy, A., Martinez-Almoyna, C., & Courtiol, A. (2017). The summary-likelihood

method and its implementation in the Infusion package. *Molecular Ecology Resources*,

17(1), 110–119. http://doi.org/10.1111/1755-0998.12627

Ryan, M. J. (1988). Energy, calling, and selection. *American Zoologist*, 28, 885–898.

http://doi.org/10.1093/icb/28.3.885

Ryan, M. J. M. J., & Keddy-Hector, A. (1992). Directional patterns of female mate choice and

the role of sensory biases. *American Naturalist*, 139, S4--S35.

http://doi.org/10.1086/285303

Shamble, P. S., Wilgers, D. J., Swoboda, K. A., & Hebets, E. A. (2009). Courtship effort is a

better predictor of mating success than ornamentation for male wolf spiders. *Behavioral

Ecology*, 20(6), 1242–1251. http://doi.org/10.1093/beheco/arp116

Shirangi, T. R., Stern, D. L., & Truman, J. W. (2013). Motor control of *Drosophila* courtship

song. *Cell Reports*, 5(3), 678–686. http://doi.org/10.1016/j.celrep.2013.09.039

Simmons, L. W., Thomas, M. L., Simmons, F. W., & Zuk, M. (2013). Female preferences for

acoustic and olfactory signals during courtship: male crickets send multiple messages.

*Behavioral Ecology*, 24(5), 1099–1107. http://doi.org/10.1093/beheco/art036

Snook, R. R. (1998). The risk of sperm competition and the evolution of sperm
796 heteromorphism. *Animal Behaviour*, 56(6), 1497–1507.

797 http://doi.org/10.1006/anbe.1998.0930

798 Snook, R. R., Brüstle, L., & Slate, J. (2009). A test and review of the role of effective

799 population size on experimental sexual selection patterns. *Evolution*, 63(7), 1923–1933.

800 http://doi.org/10.1111/j.1558-5646.2009.00682.x

801 Snook, R. R., & Markow, T. A. (2001). Mating system evolution in sperm-heteromorphic

802 *Drosophila*. *Journal of Insect Physiology*, 47(9), 957–964. http://doi.org/10.1016/S0022-

803 1910(01)00070-1

804 Snook, R. R., Robertson, A., Crudgington, H. S., & Ritchie, M. G. (2005). Experimental

805 manipulation of sexual selection and the evolution of courtship song in *Drosophila*

806 *pseudoobscura*. *Behavior Genetics*, 35(3), 245–255. http://doi.org/10.1007/s10519-005-

807 3217-0

808 Sokoloff, A. (1966). Morphological Variation in Natural and Experimental Populations of

809 *Drosophila pseudoobscura* and *Drosophila persimilis*. *Evolution*, 20(1), 49–71.

810 http://doi.org/10.2307/2406148

811 Talyn, B. C., & Dowse, H. B. (2004). The role of courtship song in sexual selection and

812 species recognition by female *Drosophila melanogaster*. *Animal Behaviour*, 68(5), 1165–

813 1180. http://doi.org/10.1016/j.anbehav.2003.11.023

814 Tauber, E., & Eberl, D. F. (2003). Acoustic communication in *Drosophila*. *Behavioural*

815 *Processes*, 64(2), 197–210. http://doi.org/10.1016/S0376-6357(03)00135-9

816 Thornhill, R., & Alcock, J. (1983). *The evolution of insect mating systems*. Cambridge:
817 Harvard University Press.

818 Turner, T. L., & Miller, P. M. (2012). Investigating natural variation in *Drosophila* courtship

819 song by the evolve and resequence approach. *Genetics*, **191**(2), 633–642.

820 http://doi.org/10.1534/genetics.112.139337

821 Veltsos, P., Wicker-Thomas, C., Butlin, R. K., Hoikkala, A., & Ritchie, M. G. (2012). Sexual

822 selection on song and cuticular hydrocarbons in two distinct populations of *Drosophila*

823 *montana*. *Ecology and Evolution*, **2**(1), 80–94. http://doi.org/10.1002/ece3.75

824 Venables, W. N., & Ripley, B. D. (2002). *Modern applied statistics with S* (Fourth). New York:

825 Springer. R package version 7.3-45 cran.r-project.org/package=MASS.

826 von Schilcher, F. (1976). The role of auditory stimuli in the courtship of *Drosophila*

827 melanogaster. *Animal Behaviour*, 18–26. http://doi.org/10.1016/S0003-3472(76)80095-4

828 Williams, M. A., Blouin, A. G., & Noor, M. A. F. (2001). Courtship songs of *Drosophila*

829 *pseudoobscura* and *D. persimilis*. II. Genetics of species differences. *Heredity*, **86**(1), 68–

830 77. http://doi.org/10.1046/j.1365-2540.2001.00811.x

831 Wilson, R., Burnet, B., Eastwood, L., & Connolly, K. (1976). Behavioural pleiotropy of the

832 yellow gene in *Drosophila melanogaster*. *Genetical Research*, **28**(1), 75–88.

833 http://doi.org/10.1017/S0016672300016748

834 Woodgate, J. L., Mariette, M. M., & Bennett, A. T. D. (2012). Male song structure predicts

835 reproductive success in a wild zebra finch population. *Animal Behaviour*, **83**(3), 773–781.

836 http://doi.org/10.1016/j.anbehav.2011.12.027
840 LRR song was analysed similarly to HRR song. To allow distinguishing between interpulse
841 and interburst intervals, an upper threshold was also determined visually by plotting the
842 distribution of the duration between two pulses (LRR threshold = 482ms, the mean LRR
843 interpulse interval is approximately 220 ms in our populations; Snook, Robertson,
844 Crudgington, & Ritchie, 2005)

845 *Differences In Singing Probability Between The Sexual Selection Treatments*

846 The difference in the probability of singing LRR (i.e. the probability of a male producing at
847 least a single pulse of LRR) between the sexual selection treatments was investigated using a
848 Fisher's exact test on the pooled replicates, due to the distribution of LRR data (as
849 polyandrous males always produced LRR in all replicates, but monogamous males do not,
850 model parameters could not be estimated by a linear model as maximum likelihood estimates
851 do not exist for this particular pattern of data; Albert & Anderson, 1984).

852 *Multivariate Response Of Courtship Song To Sexual Selection Treatment*

853 LRR interpulse interval does not vary over the length of courtship (see Table A1), and
854 therefore values were averaged over the entire length of each recording, and the resulting
855 mean LRR interpulse interval was used for statistical modelling. We fitted a multivariate LMM
856 on LRR song traits with the same structure as the one for HRR song, to test for a response of
857 the mean LRR interpulse interval (of the entire recording in this case), the mean LRR
858 intrapulse frequency, the total number of LRR pulses produced and the LRR singing latency
859 to sexual selection manipulation (Table A2). The number of estimated fixed-effect parameters
were 12 ([1+2]x4), with [4+6]x2 = 20 (co)variance parameters. We also estimated the
variance between replicates separately for each trait (4 variances) as random effects.

We also tested the significance of correlations between song traits (i.e. LRR interpulse
interval, LRR intrapulse frequency, the total number of LRR pulses produced and LRR
latency), as well as the differences in song trait correlations between sexual selection
treatments.

The same model was also run while including individual body size as a covariate (Table A3).
The number of estimated fixed-effect parameters was this time 16 ([1+1+2]x4), with [4+6]x2 =
20 (co)variance parameters.

## 869 Results

### *Differences In LRR Singing Probability Between The Sexual Selection Treatments*

The probability of singing LRR song differs between treatments, with monogamous males
having a lower probability than polyandrous males (Fisher's exact test; polyandrous males: 0
recordings without LRR song out of 231 recordings; monogamous males: 11 recordings
without LRR song out of 230 recordings; *P*<0.001).

### *Evolutionary response to sexual selection manipulation*

The multivariate LMM does not identify any significant response of LRR traits to selection
sexual treatment (Table A2).

*Temperature:* The multivariate LMM shows that LRR interpulse interval shortens with temperature (Table A3). Increasing temperature by one degree reduces the interpulse interval by 3.28ms (95% C.I. = -0.67 – -6.05, *P*=0.02). Both LRR singing latency and LRR intrapulse frequency significantly increase with temperature, with an increase in temperature of one
degree resulting in a latency increase of 14.5s (95% C.I. = 302 – 2558, P=0.01), and an LRR
intrapulse frequency increase of 4.18Hz (95% C.I. = 1.20 – 7.18, P=0.01).

*Body Size*: Including body size in the multivariate LMM does not change the results of the model (Table A3). LRR interpulse interval shortens with body size, with an increase of 1 standard deviation in wing size being associated with an interpulse interval reduction of 4.72ms (95% C.I. = -1.52– -7.53, P=0.004).

*Analysis of the Associations Between Courtship traits*

The multivariate LMM also revealed that LRR interpulse interval was positively correlated with the total number of LRR pulses produced (Table A4), but the correlation reached significance only for monogamous males. As with HRR song, we found a significant negative association between LRR latency and the total number of LRR pulses produced for both treatments (Table A4). There was no significant impact of the sexual selection treatment on the correlations between LRR traits (Table A5, Fig. A1).

Including body size in the multivariate LMM generated very similar results (Tables A6, A7).

896
897 APPENDIX B – HRR IPI Variation Over Time

898 Figure B1 shows a pattern in pulse rate production over courtship time, by illustrating how
899 HRR interpulse interval lengthens as courtship time increases. Figure B2 shows the range of
900 the distribution of the burst and pulse numbers, depending on sexual selection treatment and
901 recording temperature.

902 APPENDIX C – Prior Definition For Fitting The Multivariate LMM.

903 In both MCMCglmm models (the one with body size and the one without), we retained the
904 default settings for the prior distributions for fixed effects. In contrast, we set identity matrices
905 as prior specification for all other prior distributions and we used a degree of belief of 0.001
906 for the priors used in variance estimations only (i.e. weakly informative improper prior) and a
907 degree of belief equal to the number of response variables plus one (i.e. proper prior) for the
908 prior used in covariance matrix estimations. This structure follows the recommendations of
909 the package instructions.

910 APPENDIX D – HRR Song Analyses (With Body Size Included)

911 Running analyses of HRR interpulse interval while including body size as a covariate shows
912 that, although body size has a significant effect on courtship song production, the effect of
913 sexual selection treatment also remains significant (see Tables D1-4).
915 **Table 1.** Summary tables for the fitted GLMM analysing HRR singing probability and the
916 univariate LMM analysing body size.

<table><thead><tr><th rowspan="2">Model parameters</th><th rowspan="2">Factor level</th><th colspan="4">HRR singing probability</th><th colspan="4">Body size</th></tr><tr><th>β*</th><th>Lower CI</th><th>Upper CI</th><th>P</th><th>β</th><th>Lower CI</th><th>Upper CI</th><th>P</th></tr></thead><tbody><tr><td>Treatment</td><td>E</td><td>1.20</td><td>0.56</td><td>1.85</td><td>&lt;0.001</td><td>0.023</td><td>0.010</td><td>0.035</td><td>&lt;0.001</td></tr><tr><td>Intercept</td><td></td><td>1.35</td><td>0.98</td><td>1.71</td><td>&lt;0.001</td><td>1.08</td><td>1.07</td><td>1.09</td><td>&lt;0.001</td></tr><tr><td>Inter-replicate variance</td><td></td><td></td><td></td><td>0.038</td><td></td><td></td><td>0.000066</td><td></td><td></td></tr><tr><td>Residual variance</td><td></td><td></td><td></td><td>-</td><td></td><td></td><td>0.00062</td><td></td><td></td></tr></tbody></table>

In both models, sexual selection treatment was tested as a fixed effect, and replicate was included as a random effect. The following elements are specified: the model estimate of each variable (β), the lower and upper limit of the estimate's 95% confidence interval (CI), and p-value of the test comparing the estimate to zero (P). HRR = high-repetition rate song, Treatment = sexual selection treatment (E = polyandrous; the monogamous treatment M was used as the reference level). N = 471 recordings for HRR probability and N = 355 recordings for body size. *Given that the HRR singing probability GLMM used a binomial error distribution, the given estimates for this model are on a logit scale.
917

918

<table><caption>**Table 2.** Summary table for the fitted univariate LMM analysing the HRR pulse rate production between and within HRR bursts.</caption><thead><tr><th>Model parameters</th><th>Factor level</th><th>β</th><th>Lower CI</th><th>Upper CI</th><th>P</th></tr></thead><tbody><tr><td>Treatment</td><td>E</td><td>-1.57</td><td>-2.64</td><td>-0.501</td><td>0.026</td></tr><tr><td>Temperature</td><td></td><td>-0.71</td><td>-0.81</td><td>-0.62</td><td>&lt;0.001</td></tr><tr><td>BP</td><td></td><td>0.69</td><td>0.51</td><td>0.87</td><td>&lt;0.001</td></tr><tr><td>PP</td><td></td><td>0.92</td><td>0.87</td><td>0.98</td><td>&lt;0.001</td></tr><tr><td>Treatment * BP</td><td></td><td>-0.10</td><td>-0.32</td><td>0.11</td><td>0.339</td></tr><tr><td>Temperature * BP</td><td></td><td>-0.30</td><td>-0.40</td><td>-0.20</td><td>&lt;0.001</td></tr><tr><td>Treatment * PP</td><td></td><td>-0.093</td><td>-0.17</td><td>-0.018</td><td>0.013</td></tr><tr><td>BP * PP</td><td></td><td>0.11</td><td>0.039</td><td>0.17</td><td>0.002</td></tr><tr><td>Treatment * BP * PP</td><td></td><td>-0.16</td><td>-0.24</td><td>-0.076</td><td>&lt;0.001</td></tr><tr><td>Intercept</td><td></td><td>39.27</td><td>38.52</td><td>40.01</td><td>&lt;0.001</td></tr><tr><td>Inter-replicate variance</td><td></td><td></td><td></td><td>0.56</td><td></td></tr><tr><td>Inter-burst variance (nested within replicate)</td><td></td><td></td><td></td><td>3.47</td><td></td></tr><tr><td>Residual variance</td><td></td><td></td><td></td><td>4.92</td><td></td></tr></tbody></table>

919

920

921

922

923

924

925

926

The following elements are specified: the model estimate of each variable (β), the lower and upper limit of the estimate's 95% confidence interval (CI), and the p-value of the test comparing the estimate to zero (P). BP = Burst position, PP = Pulse position, HRR = high-repetition rate song, IPI = interpulse interval, Treatment = sexual selection treatment (E = polyandrous; the monogamous treatment M was used as the reference level), burst position = the position of the burst in the recording, pulse position = the position of the pulse in the HRR burst. The autocorrelation parameters are φ₁ = 0.23, φ₂ = 0.12, φ₃ =
927 0.058 and $\phi_4 = 0.031$. N = 35206 individual interpulse interval values. The same model

928 was fitted while including body size as a covariate (Table D1).

929
<table><caption>**Table 3.** Summary table for the fitted multivariate LMM analysing HRR traits.</caption><thead><tr><th>Trait</th><th>Model parameters</th><th>Factor level</th><th>β</th><th>Lower CI</th><th>Upper CI</th><th>P</th></tr></thead><tbody><tr><td rowspan="3">IPI</td><td>Treatment</td><td>E</td><td>-0.49</td><td>-1.10</td><td>0.12</td><td>0.092</td></tr><tr><td>Temperature</td><td></td><td>-0.14</td><td>-0.24</td><td>-0.028</td><td>0.012</td></tr><tr><td>Intercept</td><td></td><td>3.41</td><td>1.14</td><td>6.10</td><td>0.010</td></tr><tr><td rowspan="3">Amplitude</td><td>Treatment</td><td>E</td><td>-0.21</td><td>-0.57</td><td>0.18</td><td>0.262</td></tr><tr><td>Temperature</td><td></td><td>0.083</td><td>-0.032</td><td>0.188</td><td>0.158</td></tr><tr><td>Intercept</td><td></td><td>-1.79</td><td>-4.24</td><td>0.78</td><td>0.176</td></tr><tr><td rowspan="3">Frequency</td><td>Treatment</td><td>E</td><td>-0.196</td><td>-0.771</td><td>0.43</td><td>0.446</td></tr><tr><td>Temperature</td><td></td><td>0.076</td><td>-0.024</td><td>0.20</td><td>0.172</td></tr><tr><td>Intercept</td><td></td><td>-1.65</td><td>-4.20</td><td>0.89</td><td>0.218</td></tr><tr><td rowspan="3">Total number of bursts</td><td>Treatment</td><td>E</td><td>0.21</td><td>-0.31</td><td>0.74</td><td>0.398</td></tr><tr><td>Temperature</td><td></td><td>0.047</td><td>-0.078</td><td>0.15</td><td>0.414</td></tr><tr><td>Intercept</td><td></td><td>-1.16</td><td>-3.84</td><td>1.45</td><td>0.378</td></tr><tr><td rowspan="3">Latency</td><td>Treatment</td><td>E</td><td>-0.51</td><td>-0.77</td><td>-0.25</td><td>0.001</td></tr><tr><td>Temperature</td><td></td><td>0.080</td><td>-0.061</td><td>0.19</td><td>0.192</td></tr><tr><td>Intercept</td><td></td><td>-1.56</td><td>-4.25</td><td>1.39</td><td>0.254</td></tr></tbody></table>

The following elements are specified: the model estimate of each variable (β; here the posterior mean), the lower and upper limits of the estimate's 95% credibility interval (CI), and the p-value of the test comparing the estimate to zero (P). IPI = interpulse interval,
Treatment = sexual selection treatment (E = polyandrous; the monogamous treatment M was used as the reference level), Latency = the time taken to sing the first burst of HRR song. Covariances between the response variables of the model are provided as correlations in Table 4. Estimated variances between replicates were σ² = 0.17 for IPI, σ² = 0.04 for amplitude, σ² = 0.14 for intrapulse frequency, σ² = 0.12 for the total number of bursts and σ² = 0.01 for latency. Note that all responses are expressed as z-scores of the log transformed value of the original measurements, but temperature was not altered.

Estimates in the table are thus not expressed on the original data scale, but in z-scores of log values (see Methods). The means and standard deviations of the log of the original variables are as following: IPI (mean = 3.63, σ = 0.06), amplitude (mean = 5.85, σ = 0.20), frequency (mean = 5.56, σ = 0.09), total number of bursts (mean = 2.35, σ = 0.84), latency (mean = 9.38, σ = 1.32). N = 280 recordings. The same model was fitted while including body size as a covariate (Table D2).
948

949

<table><caption>**Table 4.** Correlation matrix between courtship traits for the two sexual selection treatments.</caption><thead><tr><th rowspan="2"></th><th colspan="2">IPI</th><th colspan="2">Amplitude</th><th colspan="2">Frequency</th><th colspan="2">Bursts</th><th colspan="2">Latency</th></tr><tr><th>r</th><th>P</th><th>r</th><th>P</th><th>r</th><th>P</th><th>r</th><th>P</th><th>r</th><th>P</th></tr></thead><tbody><tr><td>IPI</td><td>1</td><td>-</td><td>-0.41</td><td>&lt;0.001</td><td>-0.11</td><td>0.192</td><td>-0.38</td><td>&lt;0.001</td><td>0.28</td><td>0.002</td></tr><tr><td>Amplitude</td><td>-0.31</td><td>&lt;0.001</td><td>1</td><td>-</td><td>-0.29</td><td>&lt;0.001</td><td>0.24</td><td>0.008</td><td>-0.17</td><td>0.038</td></tr><tr><td>Frequency</td><td>0.07</td><td>0.470</td><td>-0.42</td><td>&lt;0.001</td><td>1</td><td>-</td><td>0.20</td><td>0.028</td><td>-0.09</td><td>0.298</td></tr><tr><td>Bursts</td><td>0.09</td><td>0.354</td><td>0.07</td><td>0.410</td><td>-0.04</td><td>0.656</td><td>1</td><td>-</td><td>-0.29</td><td>&lt;0.001</td></tr><tr><td>Latency</td><td>-0.05</td><td>0.594</td><td>-0.06</td><td>0.504</td><td>-0.06</td><td>0.544</td><td>-0.39</td><td>&lt;0.001</td><td>1</td><td>-</td></tr></tbody></table>

950

951

952

953

954

955

956

957

The following elements are specified: the correlation coefficient (r) and the p-value (P).
HRR = high-repetition rate song, IPI = interpulse interval, Bursts = the total number of HRR bursts produced, Latency = the time taken to sing the first burst of HRR song. These correlations were derived from the variances and covariances estimated by the multivariate LMM (see Table 3). Since correlation matrices are symmetric, correlation values for polyandrous males and monogamous males are shown above and below the diagonal, respectively.
958

<caption>**Table 5.** Differences in courtship trait correlations between the sexual selection treatments ($r_E$ - $r_M$ from Table 4).</caption>

959

<table><thead><tr><th rowspan="2"></th><th colspan="2">IPI</th><th colspan="2">Amplitude</th><th colspan="2">Frequency</th><th colspan="2">Bursts</th><th colspan="2">Latency</th></tr><tr><th>r<sub>E</sub> - r<sub>M</sub></th><th>P</th><th>r<sub>E</sub> - r<sub>M</sub></th><th>P</th><th>r<sub>E</sub> - r<sub>M</sub></th><th>P</th><th>r<sub>E</sub> - r<sub>M</sub></th><th>P</th><th>r<sub>E</sub> - r<sub>M</sub></th><th>P</th></tr></thead><tbody><tr><td>IPI</td><td>-</td><td>-</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Amplitude</td><td>-0.10</td><td>0.358</td><td>-</td><td>-</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Frequency</td><td>-0.18</td><td>0.144</td><td>0.13</td><td>0.242</td><td>-</td><td>-</td><td></td><td></td><td></td><td></td></tr><tr><td>Bursts</td><td>-0.47</td><td>&lt;0.001</td><td>0.16</td><td>0.188</td><td>0.24</td><td>0.090</td><td>-</td><td>-</td><td></td><td></td></tr><tr><td>Latency</td><td>0.33</td><td>0.008</td><td>-0.11</td><td>0.344</td><td>-0.03</td><td>0.814</td><td>0.10</td><td>0.402</td><td>-</td><td>-</td></tr></tbody></table>

960

961

962

963

964

The following elements are specified: the corresponding correlation coefficients for polyandrous ($r_E$) and monogamous males ($r_M$) and the p-value (P). HRR = high-repetition rate song, IPI = interpulse interval, Bursts = the total number of HRR bursts produced, Latency = the time taken to sing the first burst of HRR song.

965
966

967

<table><caption>**Table A1.** Correlations between LRR IPI and courtship duration in 8 randomly chosen songs, one from each of the 8 replicated populations.</caption><thead><tr><th>Song</th><th>r</th><th>P</th></tr></thead><tbody><tr><td>M1</td><td>0.081</td><td>0.438</td></tr><tr><td>M2</td><td>0.19</td><td>0.365</td></tr><tr><td>M3</td><td>0.36</td><td>0.113</td></tr><tr><td>M4</td><td>-0.17</td><td>0.437</td></tr><tr><td>E1</td><td>-0.30</td><td>0.161</td></tr><tr><td>E2</td><td>0.023</td><td>0.904</td></tr><tr><td>E3</td><td>0.28</td><td>0.235</td></tr><tr><td>E4</td><td>-0.16</td><td>0.395</td></tr></tbody></table>

968

969

970

The Spearman correlation coefficient (r) and its associated p-value (P) are given. E = polyandrous, M = monogamous, 1-4 refers to the replicate population of the song example.

971
<table><thead><tr><th>Song trait</th><th>Model parameters</th><th>Factor level</th><th>β</th><th>Lower CI</th><th>Upper CI</th><th>P</th></tr></thead><tbody><tr><td rowspan="3">IPI</td><td>Treatment</td><td>E</td><td>-0.080</td><td>-0.71</td><td>0.54</td><td>0.798</td></tr><tr><td>Temperature</td><td></td><td>-0.11</td><td>-0.20</td><td>-0.016</td><td>0.022</td></tr><tr><td>Intercept</td><td></td><td>2.59</td><td>0.39</td><td>4.68</td><td>0.020</td></tr><tr><td rowspan="3">Frequency</td><td>Treatment</td><td>E</td><td>-0.27</td><td>-0.85</td><td>0.24</td><td>0.246</td></tr><tr><td>Temperature</td><td></td><td>0.14</td><td>0.044</td><td>0.23</td><td>0.001</td></tr><tr><td>Intercept</td><td></td><td>-2.95</td><td>-5.47</td><td>-0.92</td><td>0.006</td></tr><tr><td rowspan="3">Total number of pulses</td><td>Treatment</td><td>E</td><td>0.14</td><td>-0.083</td><td>0.39</td><td>0.220</td></tr><tr><td>Temperature</td><td></td><td>-0.077</td><td>-0.16</td><td>0.027</td><td>0.094</td></tr><tr><td>Intercept</td><td></td><td>1.69</td><td>-0.68</td><td>3.63</td><td>0.11</td></tr></tbody></table>
<table><tr><td></td><td>Treatment</td><td>E</td><td>-0.25</td><td>-0.60</td><td>0.19</td><td>0.206</td></tr><tr><td rowspan="2">Latency</td><td>Temperature</td><td></td><td>0.13</td><td>0.019</td><td>0.21</td><td>0.010</td></tr><tr><td>Intercept</td><td></td><td>-2.75</td><td>-4.80</td><td>-0.35</td><td>0.014</td></tr></table>

The following elements are specified: the model estimate of each variable (β; here the posterior mean), the lower and upper limits of the estimate's 95% credibility interval (CI), and the p-value of the test comparing the estimate to zero (P). IPI = interpulse interval, Treatment = sexual selection treatment (E = polyandrous; the monogamous treatment M was used as the reference level), Latency = the time taken to sing the first pulse of LRR song. Covariances between the response variables of the model are provided as correlations in Table A4. Estimated variances between replicates were σ² = 0.20 for IPI, σ² = 0.12 for intrapulse frequency, σ² = 0.01 for the total number of bursts and σ² = 0.06 for latency. Note that all responses are expressed as z-scores of the log transformed value of the original measurements, but temperature was not altered. Estimates in the table are thus not expressed on the original data scale, but in z-scores of log values (see Methods). The means and standard deviations of the log of the original variables are as following: IPI (mean = 5.34, σ = 0.14), frequency (mean = 6.19, σ = 0.06), total number of pulses (mean = 3.36, σ = 0.78), latency (mean = 8.90, σ = 1.38). N = 415 recordings. The same model was fitted while including body size as a covariate (Table A3).
<table><caption>**Table A3.** Summary table for the fitted multivariate LMM analysing LRR song (with body size included in the model).</caption><thead><tr><th>Song trait</th><th>Model parameters</th><th>Factor level</th><th>β</th><th>Lower CI</th><th>Upper CI</th><th>P</th></tr></thead><tbody><tr><td rowspan="4">IPI</td><td>Treatment</td><td>E</td><td>0.056</td><td>-0.61</td><td>0.67</td><td>0.838</td></tr><tr><td>Temperature</td><td></td><td>-0.11</td><td>-0.21</td><td>-0.023</td><td>0.020</td></tr><tr><td>Body size</td><td></td><td>-0.16</td><td>-0.26</td><td>-0.052</td><td>0.004</td></tr><tr><td>Intercept</td><td></td><td>2.58</td><td>0.30</td><td>4.72</td><td>0.026</td></tr><tr><td rowspan="4">Frequency</td><td>Treatment</td><td>E</td><td>-0.24</td><td>-0.82</td><td>0.26</td><td>0.298</td></tr><tr><td>Temperature</td><td></td><td>0.14</td><td>0.039</td><td>0.23</td><td>0.010</td></tr><tr><td>Body size</td><td></td><td>0.0040</td><td>-0.096</td><td>0.11</td><td>0.922</td></tr><tr><td>Intercept</td><td></td><td>-3.01</td><td>-5.29</td><td>-0.84</td><td>0.012</td></tr><tr><td>Total number of</td><td>Treatment</td><td>E</td><td>0.068</td><td>-0.17</td><td>0.31</td><td>0.592</td></tr></tbody></table>
<table><tr><td rowspan="3">pulses</td><td>Temperature</td><td>-0.077</td><td>-0.17</td><td>0.019</td><td>0.096</td></tr><tr><td>Body size</td><td>0.10</td><td>-0.0090</td><td>0.20</td><td>0.082</td></tr><tr><td>Intercept</td><td>1.71</td><td>-0.58</td><td>3.72</td><td>0.106</td></tr></table>

<table><tr><td>Treatment</td><td>E</td><td>-0.26</td><td>-0.63</td><td>0.13</td><td>0.192</td></tr><tr><td rowspan="3">Latency</td><td>Temperature</td><td>0.13</td><td>0.029</td><td>0.22</td><td>0.001</td></tr><tr><td>Body size</td><td>0.014</td><td>-0.087</td><td>0.12</td><td>0.814</td></tr><tr><td>Intercept</td><td>-2.82</td><td>-4.83</td><td>-0.58</td><td>0.008</td></tr></table>

The following elements are specified: the model estimate of each variable (β; here the posterior mean), the lower and upper limits of the estimate's 95% credibility interval (CI), and the p-value of the test comparing the estimate to zero (P). IPI = interpulse interval, Treatment = sexual selection treatment (E = polyandrous; the monogamous treatment M was used as the reference level), Latency = the time taken to sing the first pulse of LRR song. Covariances between the response variables of the model are provided as correlations in Table A6. Estimated variances between replicates were σ² = 0.23 for IPI, σ² = 0.13 for interpulse frequency, σ² = 0.01 for the total number of bursts and σ² = 0.06 for latency. Note that all responses are expressed as z-scores of the log transformed value of the original measurements. Wing size was also transformed into z-scores, but temperature was not
altered. Estimates in the table are thus not expressed on the original data scale, but in z-scores of log values (see Methods). The means and standard deviations of the log of the original variables are as following: IPI (mean = 5.34, σ = 0.14), frequency (mean = 6.19, σ = 0.06), total number of pulses (mean = 3.36, σ = 0.78), latency (mean = 8.90, σ = 1.38). N = 415 recordings.

<table><caption>**Table A4.** Correlation matrix between LRR song traits for the two sexual selection treatments.</caption><thead><tr><th rowspan="2"></th><th colspan="2">IPI</th><th colspan="2">Frequency</th><th colspan="2">Pulse number</th><th colspan="2">Latency</th></tr><tr><th>r</th><th>P</th><th>r</th><th>P</th><th>r</th><th>P</th><th>r</th><th>P</th></tr></thead><tbody><tr><td>IPI</td><td>1</td><td>-</td><td>-0.14</td><td>0.088</td><td>0.07</td><td>0.38</td><td>0.06</td><td>0.428</td></tr><tr><td>Frequency</td><td>-0.14</td><td>0.06</td><td>1</td><td>-</td><td>0.06</td><td>0.466</td><td>-0.01</td><td>0.900</td></tr><tr><td>Pulse number</td><td>0.22</td><td>0.002</td><td>0.03</td><td>0.650</td><td>1</td><td>-</td><td>-0.23</td><td>0.001</td></tr><tr><td>Latency</td><td>0.07</td><td>0.358</td><td>-0.06</td><td>0.512</td><td>-0.35</td><td>&lt;0.001</td><td>1</td><td>-</td></tr></tbody></table>

The following elements are specified: the correlation coefficient (r) and the p-value (P). LRR = low-repetition rate song, IPI = interpulse interval, Latency = the time taken to sing the first pulse of LRR song. These correlations were derived from the variances and covariances estimated by the multivariate LMM (see Table A2). Since correlation matrices are symmetric,
correlation values for polyandrous males and monogamous males are shown above and below the diagonal, respectively.

<table><caption>**Table A5.** Differences in LRR song trait correlations between the sexual selection treatments ($r_E - r_M$ from Table A4).</caption><thead><tr><th rowspan="2"></th><th colspan="2">IPI</th><th colspan="2">Frequency</th><th colspan="2">Pulse number</th><th colspan="2">Latency</th></tr><tr><th>r<sub>E</sub> - r<sub>M</sub></th><th>P</th><th>r<sub>E</sub> - r<sub>M</sub></th><th>P</th><th>r<sub>E</sub> - r<sub>M</sub></th><th>P</th><th>r<sub>E</sub> - r<sub>M</sub></th><th>P</th></tr></thead><tbody><tr><td>IPI</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td></tr><tr><td>Frequency</td><td>0.00</td><td>0.988</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td></tr><tr><td>Pulse number</td><td>-0.15</td><td>0.152</td><td>0.03</td><td>0.802</td><td>-</td><td>-</td><td>-</td><td>-</td></tr><tr><td>Latency</td><td>-0.01</td><td>0.978</td><td>0.04</td><td>0.684</td><td>0.12</td><td>0.224</td><td>-</td><td>-</td></tr></tbody></table>

The following elements are specified: the corresponding correlation coefficients for polyandrous ($r_E$) and monogamous males ($r_M$) and the p-value (P). LRR = low-repetition rate song, IPI = interpulse interval, Latency = the time taken to sing the first pulse of LRR song.
<table><caption>**Table A6.** Correlation matrix between LRR song traits for the two sexual selection treatments (with body size included in the model)</caption><thead><tr><th rowspan="2"></th><th colspan="2">IPI</th><th colspan="2">Frequency</th><th colspan="2">Pulse number</th><th colspan="2">Latency</th></tr><tr><th>r</th><th>P</th><th>r</th><th>P</th><th>r</th><th>P</th><th>r</th><th>P</th></tr></thead><tbody><tr><td>IPI</td><td>1</td><td>-</td><td>-0.13</td><td>0.100</td><td>0.09</td><td>0.238</td><td>0.06</td><td>0.450</td></tr><tr><td>Frequency</td><td>-0.15</td><td>0.052</td><td>1</td><td>-</td><td>0.06</td><td>0.482</td><td>-0.01</td><td>0.900</td></tr><tr><td>Pulse number</td><td>0.21</td><td>0.004</td><td>0.03</td><td>0.682</td><td>1</td><td>-</td><td>-0.23</td><td>0.004</td></tr><tr><td>Latency</td><td>0.09</td><td>0.256</td><td>-0.05</td><td>0.556</td><td>-0.35</td><td>&lt;0.001</td><td>1</td><td>-</td></tr></tbody></table>

The following elements are specified: the correlation coefficient (r) and the p-value (P). LRR = low-repetition rate song, IPI = interpulse interval, Latency = the time taken to sing the first pulse of LRR song. These correlations were derived from the variances and covariances estimated by the multivariate LMM (see Table A3). Since correlation matrices are symmetric, correlation values for polyandrous males and monogamous males are shown above and below the diagonal, respectively.
<table><caption>**Table A7.** Differences in LRR song trait correlations between the sexual selection treatments ($r_E - r_M$ from Table A6) (with body size included in the model)</caption><thead><tr><th rowspan="2"></th><th colspan="2">IPI</th><th colspan="2">Frequency</th><th colspan="2">Pulse number</th><th colspan="2">Latency</th></tr><tr><th>r<sub>E</sub> - r<sub>M</sub></th><th>P</th><th>r<sub>E</sub> - r<sub>M</sub></th><th>P</th><th>r<sub>E</sub> - r<sub>M</sub></th><th>P</th><th>r<sub>E</sub> - r<sub>M</sub></th><th>P</th></tr></thead><tbody><tr><td>IPI</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td></tr><tr><td>Frequency</td><td>0.01</td><td>0.868</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td></tr><tr><td>Pulse number</td><td>-0.12</td><td>0.262</td><td>0.02</td><td>0.886</td><td>-</td><td>-</td><td>-</td><td>-</td></tr><tr><td>Latency</td><td>-0.03</td><td>0.808</td><td>0.04</td><td>0.722</td><td>0.12</td><td>0.252</td><td>-</td><td>-</td></tr></tbody></table>

The following elements are specified: the corresponding correlation coefficients for polyandrous ($r_E$) and monogamous males ($r_M$) and the p-value (P). LRR = low-repetition rate song, IPI = interpulse interval, Latency = the time taken to sing the first pulse of LRR song.
<table><caption>**Table D1.** Summary table for the fitted univariate LMM analysing the HRR pulse rate production between and within HRR bursts (with body size included in the model).</caption><thead><tr><th rowspan="2">Model parameters</th><th rowspan="2">Factor level</th><th rowspan="2">β</th><th rowspan="2">Lower CI</th><th rowspan="2">Upper CI</th><th rowspan="2">P</th></tr></thead><tbody><tr><td>Wing size</td><td></td><td>-0.42</td><td>-0.53</td><td>-0.31</td><td>&lt;0.001</td></tr><tr><td>Treatment</td><td>E</td><td>-1.17</td><td>-2.39</td><td>0.046</td><td>0.102</td></tr><tr><td>Temperature</td><td></td><td>-0.75</td><td>-0.85</td><td>-0.65</td><td>&lt;0.001</td></tr><tr><td>BP</td><td></td><td>0.69</td><td>0.51</td><td>0.87</td><td>&lt;0.001</td></tr><tr><td>PP</td><td></td><td>0.92</td><td>0.86</td><td>0.98</td><td>&lt;0.001</td></tr><tr><td>Treatment * BP</td><td></td><td>-0.055</td><td>-0.27</td><td>0.16</td><td>0.609</td></tr><tr><td>Temperature * BP</td><td></td><td>-0.3</td><td>-0.40</td><td>-0.20</td><td>&lt;0.001</td></tr><tr><td>Treatment * PP</td><td></td><td>-0.09</td><td>-0.16</td><td>-0.015</td><td>0.015</td></tr><tr><td>BP * PP</td><td></td><td>0.11</td><td>0.042</td><td>0.18</td><td>0.001</td></tr><tr><td>Treatment * BP * PP</td><td></td><td>-0.16</td><td>-0.24</td><td>-0.079</td><td>&lt;0.001</td></tr><tr><td>Intercept</td><td></td><td>39.04</td><td>38.20</td><td>39.89</td><td>&lt;0.001</td></tr></tbody></table>
<table><tr><td>Inter-replicate variance</td><td>0.73</td></tr><tr><td>Inter-burst variance (nested within replicate)</td><td>3.32</td></tr><tr><td>Residual variance</td><td>4.91</td></tr></table>

The following elements are specified: the model estimate of each variable (β), the lower and upper limit of the estimate's 95% confidence interval (CI), the p-value of the test comparing the estimate to zero (P). BP = Burst position, PP = Pulse position, HRR = high-repetition rate song, IPI = interpulse interval, Treatment = sexual selection treatment (E = polyandrous; the monogamous treatment M was used as the reference level), burst position = the position of the burst in the recording, pulse position = the position of the pulse in the HRR burst. The autocorrelation parameters are φ₁ = 0.23, φ₂ = 0.12, φ₃ = 0.058 and φ₄ = 0.031. N = 35206 individual interpulse interval values.
<table><caption>**Table D2.** Summary table for the fitted multivariate LMM analysing HRR song (with body size included in the model)</caption><thead><tr><th>Song trait</th><th>Model parameters</th><th>Factor level</th><th>β</th><th>Lower CI</th><th>Upper CI</th><th>P</th></tr></thead><tbody><tr><td rowspan="4">IPI</td><td>Treatment</td><td>E</td><td>-0.41</td><td>-1.014</td><td>0.26</td><td>0.178</td></tr><tr><td>Temperature</td><td></td><td>-0.14</td><td>-0.26</td><td>-0.045</td><td>0.016</td></tr><tr><td>Body size</td><td></td><td>-0.13</td><td>-0.27</td><td>-0.014</td><td>0.046</td></tr><tr><td>Intercept</td><td></td><td>3.51</td><td>1.032</td><td>5.89</td><td>0.008</td></tr><tr><td rowspan="4">Amplitude</td><td>Treatment</td><td>E</td><td>-0.32</td><td>-0.74</td><td>0.11</td><td>0.128</td></tr><tr><td>Temperature</td><td></td><td>0.095</td><td>-0.018</td><td>0.21</td><td>0.106</td></tr><tr><td>Body size</td><td></td><td>0.16</td><td>0.042</td><td>0.30</td><td>0.024</td></tr><tr><td>Intercept</td><td></td><td>-2.02</td><td>-4.63</td><td>0.57</td><td>0.138</td></tr><tr><td>Frequency</td><td>Treatment</td><td>E</td><td>-0.11</td><td>-0.63</td><td>0.52</td><td>0.678</td></tr></tbody></table>
<table><tr><td>Temperature</td><td></td><td>0.069</td><td>-0.057</td><td>0.19</td><td>0.266</td></tr><tr><td>Body size</td><td></td><td>-0.092</td><td>-0.22</td><td>0.040</td><td>0.180</td></tr><tr><td>Intercept</td><td></td><td>-1.52</td><td>-4.12</td><td>1.38</td><td>0.296</td></tr></table>

<table><tr><td></td><td>Treatment</td><td>E</td><td>0.21</td><td>-0.37</td><td>0.74</td><td>0.432</td></tr><tr><td rowspan="3">Total number of bursts</td><td>Temperature</td><td></td><td>0.050</td><td>-0.064</td><td>0.16</td><td>0.440</td></tr><tr><td>Body size</td><td></td><td>0.010</td><td>-0.10</td><td>0.14</td><td>0.862</td></tr><tr><td>Intercept</td><td></td><td>-1.22</td><td>-3.52</td><td>1.58</td><td>0.404</td></tr></table>

<table><tr><td></td><td>Treatment</td><td>E</td><td>-0.47</td><td>-0.74</td><td>-0.18</td><td>0.002</td></tr><tr><td rowspan="3">Latency</td><td>Temperature</td><td></td><td>0.076</td><td>-0.041</td><td>0.19</td><td>0.202</td></tr><tr><td>Body size</td><td></td><td>-0.054</td><td>-0.17</td><td>0.073</td><td>0.392</td></tr><tr><td>Intercept</td><td></td><td>-1.48</td><td>-4.18</td><td>1.12</td><td>0.246</td></tr></table>

The following elements are specified: the model estimate of each variable (β; here the posterior mean), the lower and upper limits of the estimate's 95% credibility interval (CI), and
the p-value of the test comparing the estimate to zero (P). IPI = interpulse interval, Treatment = sexual selection treatment (E = polyandrous; the monogamous treatment M was used as the reference level), Latency = the time taken to sing the first burst of HRR song. Covariances between the response variables of the model are provided as correlations in Table D3.
Estimated variances between replicates were σ² = 0.2 for IPI, σ² = 0.05 for amplitude, σ² = 0.13 for intrapulse frequency, σ² = 0.12 for the total number of bursts and σ² = 0.01 for latency. Note that all responses are expressed as z-scores of the log transformed value of the original measurements. Wing size was also transformed into z-scores, but temperature was not altered. Estimates in the table are thus not expressed on the original data scale, but in z-scores of log values (see Methods). The means and standard deviations of the log of the original variables are as following: IPI (mean = 3.63, σ = 0.06), amplitude (mean = 5.85, σ = 0.20), frequency (mean = 5.56, σ = 0.09), total number of bursts (mean = 2.35, σ = 0.84), latency (mean = 9.38, σ = 1.32). N = 280 recordings.

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<table><caption>**Table D3.** Correlation matrix between HRR courtship traits for the two sexual selection treatments (with body size included in the model).</caption><thead><tr><th rowspan="2"></th><th colspan="2">IPI</th><th colspan="2">Amplitude</th><th colspan="2">Frequency</th><th colspan="2">Bursts</th><th colspan="2">Latency</th></tr><tr><th>r</th><th>P</th><th>r</th><th>P</th><th>r</th><th>P</th><th>r</th><th>P</th><th>r</th><th>P</th></tr></thead><tbody><tr><td>IPI</td><td>1</td><td>-</td><td>-0.39</td><td>&lt;0.001</td><td>-0.12</td><td>0.138</td><td>-0.37</td><td>&lt;0.001</td><td>0.26</td><td>0.002</td></tr><tr><td>Amplitude</td><td>-0.3</td><td>&lt;0.001</td><td>1</td><td>-</td><td>-0.27</td><td>&lt;0.001</td><td>0.23</td><td>0.008</td><td>-0.15</td><td>0.076</td></tr><tr><td>Frequency</td><td>0.06</td><td>0.560</td><td>-0.41</td><td>&lt;0.001</td><td>1</td><td>-</td><td>0.21</td><td>0.018</td><td>-0.1</td><td>0.260</td></tr><tr><td>Bursts</td><td>0.07</td><td>0.436</td><td>0.09</td><td>0.314</td><td>-0.04</td><td>0.650</td><td>1</td><td>-</td><td>-0.29</td><td>0.002</td></tr><tr><td>Latency</td><td>-0.04</td><td>0.614</td><td>-0.07</td><td>0.490</td><td>-0.05</td><td>0.584</td><td>-0.39</td><td>&lt;0.001</td><td>1</td><td>-</td></tr></tbody></table>

The following elements are specified: the correlation coefficient (r) and the p-value (P). HRR = high-repetition rate song, IPI = interpulse interval, Bursts = the total number of HRR bursts produced, Latency = the time taken to sing the first burst of HRR song. These correlations were derived from the variances and covariances estimated by the multivariate LMM (see Table D2). Since correlation matrices are symmetric, correlation values for polyandrous males and monogamous males are shown above and below the diagonal, respectively.
<table><caption>**Table D4.** Differences in HRR courtship trait correlations between the sexual selection treatments ($r_E - r_M$ from Table D3) (with body size included in the model).</caption><thead><tr><th></th><th colspan="2">IPI</th><th colspan="2">Amplitude</th><th colspan="2">Frequency</th><th colspan="2">Bursts</th><th colspan="2">Latency</th></tr><tr><th></th><th>r<sub>E</sub> - r<sub>M</sub></th><th>P</th><th>r<sub>E</sub> - r<sub>M</sub></th><th>P</th><th>r<sub>E</sub> - r<sub>M</sub></th><th>P</th><th>r<sub>E</sub> - r<sub>M</sub></th><th>P</th><th>r<sub>E</sub> - r<sub>M</sub></th><th>P</th></tr></thead><tbody><tr><td>IPI</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td></tr><tr><td>Amplitude</td><td>-0.09</td><td>0.426</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td></tr><tr><td>Frequency</td><td>-0.18</td><td>0.142</td><td>0.14</td><td>0.218</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td></tr><tr><td>Bursts</td><td>-0.44</td><td>&lt;0.001</td><td>0.14</td><td>0.290</td><td>0.25</td><td>0.042</td><td>-</td><td>-</td><td>-</td><td>-</td></tr><tr><td>Latency</td><td>0.31</td><td>0.012</td><td>-0.09</td><td>0.484</td><td>-0.05</td><td>0.700</td><td>0.10</td><td>0.360</td><td>-</td><td>-</td></tr></tbody></table>

The following elements are specified: the corresponding correlation coefficients for polyandrous ($r_E$) and monogamous males ($r_M$) and the p-value (P). HRR = high-repetition rate song, IPI = interpulse interval, Bursts = the total number of HRR bursts produced, Latency = the time taken to sing the first burst of HRR song.

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**Figure 1.** *D. pseudoobscura* courtship song representation. Both LRR (low-repetition rate) and HRR (high-repetition rate) song are represented. Each burst of song is composed of multiple pulses, each separated by a certain time interval, the interpulse interval (IPI; i.e. the inverse of pulse rate). As the interpulse interval represents the amount of time between two consecutive pulses, a short interpulse interval means that a male rapidly beats his wings (i.e. fast pulse repetition rate), whereas that a long interpulse interval means that a male slowly beats his wings (i.e. slow pulse repetition rate). HRR frequency represents the intrapulse frequency of a pulse of HRR. In our analysis, we will refer to ‘burst position’ as the position of an HRR burst in the courtship sequence (i.e. the 1st burst produced, the 2nd burst produced, the 3rd burst produced), and to ‘pulse position’ as the position of a pulse within a burst of HRR (i.e. the 1st pulse of a burst, the 2nd pulse of a burst, the 3rd pulse of a burst). || in colour on the Web and in black-and-white in print - 2-column fitting image ||

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**Figure 2.** Differences between the sexual selection treatments in singing probability (the probability of singing HRR). Model estimates are given in Table 1. The letters represent the fitted values predicted by the mixed model depending on male sexual selection treatment (E = polyandrous males, M = monogamous males). HRR = high-repetition rate song. 95% confidence intervals are represented in dashed lines. || in black-and-white colour on the Web and in print - 1-column fitting image ||

**Figure 3.** Changes in HRR interpulse interval production along bursts in the courtship sequence, depending on sexual selection treatment, as predicted by the fitted univariate pulse rate production LMM. The figure shows the changes of the mean interpulse interval
value along bursts in a 40-burst courtship sequence of song for monogamous (grey) and polyandrous (black). Model estimates are given in Table 2. The letters represent the fitted values predicted by the mixed model depending on male sexual selection treatment (E = polyandrous males, M = monogamous males). HRR = high-repetition rate song, IPI = interpulse interval. 95% confidence intervals are represented in dashed lines. || in black-and-white colour on the Web and in print - 1-column fitting image ||

**Figure 4.** Changes in HRR interpulse interval production along pulses within a burst, depending on sexual selection treatment, as predicted by the fitted univariate pulse rate production LMM. The figure shows the changes of individual interpulse interval values along pulses at the beginning of courtship (burst 1; grey) and after 40 bursts of song (burst 40; black), for males of polyandrous (a) and monogamous (b) males. Model estimates are given in Table 2. The letters represent the fitted values predicted by the mixed model depending on male sexual selection treatment (E = polyandrous males, M = monogamous males). HRR = high-repetition rate song, IPI = interpulse interval. 95% confidence intervals are represented in dashed lines. || in black-and-white colour on the Web and in print - 2-column fitting image ||

**Figure 5.** Body size and temperature effects on HRR interpulse interval, as predicted by the fitted univariate pulse rate production and body size LMMs: (a) the effect of recording temperature variation on interpulse interval variation along bursts (estimated for 4 different recording temperatures: 21, 22, 23, and 24°C); (b) the average body size difference between the treatments; and (c) the effect of body size on interpulse interval. Model estimates for figure (a) and (c) were extracted from the univariate pulse rate production LMM that included body size as a covariate (Table D1), while figure (b) is based on the univariate body size LMM
presented in Table 1. The symbols represent the fitted values predicted by the mixed models depending on male sexual selection treatment (E = polyandrous males, M = monogamous males), body size (circles) or temperature (21, 22, 23 and 24). IPI = interpulse interval. 95% confidence intervals are represented in dashed lines. || in black-and-white colour on the Web and in print - 1-column fitting image ||

**Figure 6.** Correlations ellipses between courtship traits for polyandrous (black) and monogamous (dark grey) males. This figure is a graphical representation of the correlation values provided in Table 4. The dotted light grey circle represents a null correlation (r = 0). The stronger the correlation, the narrower the ellipse becomes. || in black-and-white colour on the Web and in print - 2-column fitting image ||

**Figure A1.** Correlations ellipses between LRR song traits for polyandrous (black) and monogamous (dark grey) males. This figure is a graphical representation of the correlation values provided in Table A4. The dotted light grey circle represents a null correlation (r = 0). The stronger the correlation, the narrower the ellipse becomes.

**Figure B1.** Example of HRR interpulse interval lengthening along HRR bursts, over courtship duration. Three random songs are represented (the three types of symbols in black, dark grey and grey), with each data point showing the mean HRR interpulse interval value of a single burst of song. A trend line showing the relationship between HRR interpulse interval and courtship duration was added for each song, for illustration purposes only. The Spearman correlation coefficient (r) and its associated p-value (P) are given for each song as follows:
black squares (r = 0.69, P = 0.002), grey circles (r = 0.59, P = 0.057), crosses (r = 0.57, P = 0.001). HRR = high-repetition rate song, IPI = interpulse interval.

**Figure B2.** Violin plots showing the distribution of: a) burst number and b) pulse number depending on sexual selection treatment, and c) burst number and d) pulse number depending on recording temperature distribution. The means (grey circles) +/- 1 standard deviation (vertical grey bars) are represented. E = polyandrous males, M = monogamous males.
<figure><img src="image_2.png" /><figcaption>Figure 1</figcaption></figure>
<figure><img src="image_3.png" /><figcaption>Figure 2</figcaption></figure>

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<figure><img src="image_4.png" /><figcaption>Figure 3</figcaption></figure>

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<figure><img src="image_6.png" /><figcaption>Figure 4</figcaption></figure>

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<figure><img src="image_9.png" /><figcaption>Figure 5</figcaption></figure>
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<figure><img src="image_12.png" /><figcaption>Figure B1</figcaption></figure>

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<caption>1110 **Figure B2**</caption>