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Heart rate during manual restraint
Heart rates during manual restraint (HR, hereafter) were collected between 2011 and 2015. Following the handling aggression scoring, the bird was put in a cloth bag and brought to the novel-environment apparatus (approximately 1 to 200 m away) where we recorded heart rate during manual restraint. Prior to recording, the handler placed the bird’s head between his forefinger and his middle finger and put the bird’s legs between his thumb and forefinger. HR was then recorded for 30 seconds, using a digital recorder with the microphone placed close to the bird’s cloaca and directed towards the heart.
Back in the lab, we used the software Avisoft SASLab Pro version 5.1 to extract the mean time interval (sec) between two heart beats using approximately 100 consecutive heart beats per individual. We used the number of heartbeats in a minute (60 / mean time interval) in the analysis. We recorded HR instead of breath rate (BR hereafter), a measure more commonly used in bird studies (Carere and van Oers 2004; Brommer and Kluen 2012; Kluen et al. 2014; Fucikova et al. 2009), because, while the analysis is more time consuming, HR scoring can be automated and is thus less prone to errors or biases than BR. To compare our results with other studies on birds, we examined the correlation between HR and BR on a subsample of 102 birds in 2015. BR was measured right after recording HR, following the protocol described by Brommer and Kluen (2012). In short, we measured the time required for the bird to take 30 breaths and repeated this procedure twice. We transformed the average of the two measures to obtain the number of breaths in a minute (1800 / average of the two measures).
Exploratory behavior in a novel environment
Data on exploration were collected between 2011 and 2014. After a bird’s heart rate was measured, it was placed in a novel-environment apparatus built on the model proposed by Mutzel et al. (2013). From 2011 to 2013, the apparatus consisted of a large white cage (120 cm x 50 cm x 50 cm) with six perches and one side composed of small mesh, allowing us to video trials (Fig. S2.1a). The apparatus was placed in the trunk of a car (Kangoo, Renault), and the car side and back windows were covered with a tarp to isolate the tested bird from the external environment (Fig. S2.1a). Natural light was used for the video recording. In 2014, to homogenize light conditions over time and space, we used a slightly smaller novel-environment apparatus (110 x 50 x 50 cm) placed inside a closed trailer and artificial lights for every trial (Fig. S2.1b). Prior to all trials, the bird was placed for two minutes in a closed chamber (15 x 15 x 15 cm) located on the right hand side of the novel-environment apparatus, and connected to the main chamber by a sliding door. We then opened the door, gently pushed the bird inside the main chamber and video recorded its behavior for five minutes. The bird was subsequently retrieved of the novel-environment apparatus, ringed when necessary, weighed, and released. Birds that could not be put in the novel-environment apparatus right after the heart rate measurement were placed in a small cloth bag for a maximum of 30 minutes. When the time interval between the HR recording and the novel-environment trials was more than 30 minutes, the birds were placed in a cage with water and mealworms (n =193 trials). Back in the lab, we extracted the average speed of the bird (cm/s) during the trial using the software EthoVision XT version 9 and we used this variable in the analyses as a measure of exploratory behavior. Compared to other ways of measuring movements in the novel environment, the computation of average exploration speed can be automated, reducing both errors and biases. Furthermore, the average speed was well correlated to the number of large flights in our novel-environment apparatus (r = 0.9, p < 0.001, n = 20), a measure that has commonly been used to quantify exploratory behavior in other studies (Dingemanse et al. 2002; Mutzel et al. 2013).
Population difference and variation across sex and time
Populations differed significantly in average handling aggression score (Table 2.3, Table 2.4, Fig. 2.2a, Table S2.8). Birds in D-Muro (mean = 1.69; s.d. = 0.95) had a significantly higher handling aggression score than those from E-Muro (mean = 1.48; s.d. = 0.96) and than those from E-Pirio (mean = 1.49; s.d. = 0.99), while birds in E-Pirio and E-Muro displayed similar scores (Table 2.4, Fig. 2.2a). Females were less aggressive than males [estimate: -0.34 (95% CI: -0.44; -0.24); Table S2.8]. There was no significant interaction between sex and population for this trait (p-value = 0.31; L-ratio: 2.35) but there was a significant interaction between population and year; with individuals from D-Muro being more aggressive compared to individuals in E-Pirio in 2011, while in 2012 and 2013 individuals in D-Muro were less aggressive (Table 2.3, Fig. S2.2a and Table S2.8).
Mean HR during manual restraint was positively related to BR [estimate: 0.82 (95% CI: 0.06; 1.66); L-ratio = 4.33; p-value < 0.05]: individuals with a fast heart rate breathed faster during restraint. When we did not control for body mass, birds from E-Pirio had a faster HR (mean = 976.24 beats/min, s.d.= 86.99) than birds from D-Muro (mean: 963.30 beats/min; s.d.= 87.80) and E-Muro (mean = 955.97 beats/min; s.d. = 89.18) but birds from E-Muro and D-Muro had a similar heart rate [E-Pirio vs D-Muro: estimate: 26.64 (95% CI: 1.15; 52.06); L-ratio = 3.90 p-value < 0.05; E-Pirio vs E-Muro: estimate: 30.66 (95% CI: -0.418; 61.71); L-ratio = 3.74, p-value = 0.053; D-Muro vs E-Muro: estimate: -9.09 (95% CI: -36.14; 17.92); L-ratio = 0.44; p-value = 0.53]. There was also a significant interaction between population and year (L-ratio = 21.92; p-value < 0.01; Fig. S2.2b). Lighter individuals had a faster HR (p-value < 0.001; Table S2.9) and there was a significant difference in body mass between populations: birds from E-Pirio were lighter than birds from D-Muro [estimate: -0.15 (95% CI: -0.27; -0.05); L-ratio = 7.42; p-value < 0.01] and from E-Muro [estimate: – 0.11 (95% CI: -0.23; 0.01); L-ratio = 3.11; p-value = 0.078]. Consequently, mean HR did not differ significantly among populations when we controlled for body mass (E-Pirio vs D-Muro: L-ratio = 2.07; p-value = 0.15; E-Pirio vs E-Muro: L-ratio = 2.01; p-value = 0.16; E-Muro vs D-Muro: L-ratio = 0.308; p-value=0.58; Fig. 2.2b). There was also a significant interaction between population and year when we controlled for body mass (Table 2.3; Fig. S2.2b and Table S2.9).
We found a marginally significant interaction between sex and population (L-ratio = 5.65; p-value = 0.059). When we analyzed both sexes separately and controlled for body mass, males from E-Pirio had a faster HR than males from E-Muro [estimate: 81.03 (95% CI: 35.66; 129.95); L-ratio = 11.62; p-value < 0.001] and males from E-Muro had a marginally significantly slower HR than males from D-Muro [estimate: -32.71 (95% CI: -69.68; 3.90); L-ratio = 3.08; p-value = 0.079; Fig. 2.3]. However, there was no difference in male HR between D-Muro and E-Pirio (L-ratio = 2.36; p-value = 0.12) and no population effect for females (L-ratio = 0.90; p-value = 0.65).
Heart rate during manual restrain
Heart rate and breath rate reflect the activity of the sympathetic and parasympathetic nervous systems (Koolhaas et al. 1999). The sympathetic nervous system is suspected to be the dominant system in individuals that display fast exploration patterns, high handling aggression, and that exhibit a fast life-history strategy and invest more in current reproduction. The parasympathetic system is suspected to be the dominant system in slow exploring and docile individuals that exhibit a slower life-history strategy and invest more in future reproduction (proactive versus reactive coping styles: Koolhaas et al. 1999; Réale et al. 2010; Ferrari et al. 2013). According to the pace-of-life syndrome hypothesis, the birds from the evergreen populations should exhibit a personality typical of a slow pace-of-life and thus a higher activity of the parasympathetic system and a slower heart rate during stressful events (Koolhaas et al. 1999; Ferrari et al. 2013). The tendency for a slower male heart rate in E-Muro than in D-Muro is in accordance with this prediction. However, contrary to our expectations, male heart rate was faster in E-Pirio than in E-Muro. This result contradicts the literature on pace-of-life and coping style (Koolhaas et al. 1999; Réale et al. 2010; Ferrari et al. 2013). However, a fast breath rate has been found to be associated with low activity in the novel-environment apparatus and with low handling aggression in other blue tit studies (Kluen et al. 2014; but see Fucikova et al. 2009). We found a positive relationship between breath rate and heart rate in our populations. Therefore, our results indicate that males in E-Pirio are less active in the novel-environment and have a potentially faster breath rate, which is in line with previous studies on blue tits personality (Kluen et al. 2014) even though it contradicts the general pace-of-life syndrome expectations (Réale et al. 2010). Further studies would be needed to clarify the association between the autonomous nervous system and both personality and life history traits in avian species.
Nest defense behavior
We found a significant repeatability for nest defense behavior (Table 2.2) revealing among-individual differences in nest defense in blue tits. We also found that birds in a pair showed positively correlated nest defense behavior. This correlation between partners could be caused by environmental factors shared by both parents, such as brood size (Montgomerie and Weatherhead 1988), or be the result of individuals matching their behavior to their partner’s (Schuett et al. 2010). Alternatively, this relationship could indicate behavioral assortative mating choice in these populations (Schuett et al. 2010; Class et al. 2014).
Nest defense behavior involves a trade-off between parental survival, energy reserve and offspring protection (Trivers 1972; Montgomerie and Weatherhead 1988). Birds that have a lower future reproductive value and invest more in current reproduction should take more risks and invest more in offspring defense (Hakkarainen and Korpimäki 1994; Wolf et al. 2007; Møller and Nielsen 2014). Since they are faced with lower survival probability and larger clutches (Grosbois et al. 2006; Charmantier et al 2016), D-Muro birds were expected to approach the stuffed predator and the nestbox closer than birds from the evergreen populations. Contrary to this prediction, we did not find any difference among populations for nest defense behavior (Fig. 2.2d). It is possible that, contrary to expectations (Wolf et al. 2007; Sih et al. 2015), risk taking during nest defense is not related to other measures of life-history characteristics in these blue tit populations. Alternatively, the correlation between risk taking during nest defense and other life-history traits could exist in our system but be detectable only at the within-population level if we compare individuals instead of populations (between-individual correlation; Dingemanse and Dochtermann 2013).
Sex-specific personality phenotypes
An increasing number of studies show sex differences in personality traits and behavioral syndromes (Schuett et al. 2010; Dammhahn 2012; Fresneau et al. 2014). For example, Fresneau et al. (2014) found different behavioral syndromes between male and female in a Finnish population of blue tits. We also found sex-specific personality phenotypes in this study, with differences between sexes in mean phenotype for all traits and sex-specific difference between populations for heart rate during manual restraint. We also found that nest defense behavior was repeatable for females but not for males. In general, intersexual differences in personality phenotypes are not well understood, but likely arise because of intersexual differences in life-history strategies and selection pressures (Dingemanse et al. 2004; Class et al. 2014; Dammhahn 2012). A detailed investigation of sex-specific selection acting on these traits would help to explain the sexual dimorphism described in this study.
Local adaptation in personality traits
Phenotypic differences between the three blue tit populations could be interpreted as divergent adaptations to habitat-specific ecological conditions, but from the present study we cannot conclude whether these differences are due to behavioral plasticity or due to underlying genetic differences. However, several lines of evidence from recent studies on personality variation and past investigations in these populations suggest that differences in personality traits likely reflect a genetic difference among populations and adaptations to local ecological conditions. First, personality in Parus is under selection (Dingemanse et al. 2004; Quinn et al. 2009; Nicholaus et al. 2016) and is heritable (Brommer and Kluen 2012; Class et al. 2014). Second, common-garden experiments have revealed genetic differences in life-history, morphological and other behavioral traits among the three populations (Blondel et al 1999; Braillet et al. 2002; Charmantier et al. 2016). Third, genomic analyses using RAD sequencing have recently revealed a fine scale genetic differentiation with a significant Fst of 1.8% between D-Muro and E-Muro (Porlier et al. 2012a; Szulkin et al. 2016). Fourth, genetic drift is not likely to have driven such phenotypic difference, considering the very large population size (roughly estimated around 10,000 in the Regino valley alone; Charmantier, pers. com.). Finally, preliminary results from a common-garden experiment suggest a genetic basis for the phenotypic differences between these populations in personality traits (Dubuc-Messier et al. in prep.).
Table of contents :
CHAPITRE 1 INTRODUCTION
1.1 La divergence des populations peut avoir plusieurs origines
1.2 La variation intraspécifique de comportement
1.3 Le phénotype de personnalité pourrait être associé aux compromis d’histoire de vie
1.4 L’hypothèse du syndrome de train de vie
1.5 L’hypothèse du syndrome de train de vie et l’hétérogénéité environnementale
1.6 Objectifs et structure de la thèse
1.7 Espèce modèle et populations d’études
CHAPITRE 2 ENVIRONMENTAL HETEROGENEITY AND POPULATION DIFFERENCES IN BLUE TITS PERSONALITY TRAITS.
2.7 Supplementary materials
CHAPITRE 3 GENE FLOW DOES NOT PREVENT PERSONALITY AND MORPHOLOGICAL DIFFERENTIATION BETWEEN TWO BLUE TIT POPULATIONS.
3.3 Materials and Methods
3.7 Supplementary materials
CHAPITRE 4 RECIPROCAL-TRANSPLANT EXPERIMENT REVEALS GENETIC DIFFERENTIATION IN PERSONALITY TRAITS BETWEEN TWO NEIGHBOURING AVIAN POPULATIONS.
4.3 Materials and Methods
4.7 Supplementary materials
CHAPITRE 5 ENVIRONMENTAL HETEROGENEITY AND DIFFERENTIAL LOCAL SELECTION PATTERNS ON PERSONALITY TRAITS IN BLUE TIT POPULATIONS
5.3 Materials and Methods
5.7 Supplementary materials
CHAPITRE 6 CONCLUSIONS
6.1 Contributions et conclusions
6.3 Conclusion générale