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85 Behav Ecol Sociobiol DOI /s y ORIGINAL PAPER Informative content of multiple plumage-coloured traits in female and male European Rollers Nadia Silva & Jesús M. Avilés & Etiénne Danchin & Deseada Parejo Received: 20 February 2008 /Revised: 4 July 2008 /Accepted: 8 July 2008 # Springer-Verlag 2008 Abstract Animals may assess the quality of other individuals by using information that different ornaments may provide. The European Roller (Coracias garrulus) is a socially monogamous species in which males and females display highly conspicuous plumage colouration. According to the mutual selection hypothesis, we predicted that, in this species, plumage coloration could signal individual quality in both sexes because both female and male rollers invest a considerable amount of time caring for their offspring. We used spectrophotometric measurements to investigate the information content of multiple plumage colour traits. We found that the roller is actually a sexually dimorphic and dichromatic species. Different plumage colours from different origins were correlated within individual. Head and back brightness correlated with body condition in both sexes, and in males, head brightness correlated with the number of fledglings in successful nests, while head green-yellow saturation correlated with parental Communicated by I. Cuthill D. Parejo (*) Department of Functional and Evolutionary Ecology, Estación Experimental de Zonas Áridas, C.S.I.C., C/ General Segura 1, Almería, Spain parejo@eeza.csic.es N. Silva : E. Danchin Laboratoire Évolution et Diversité Biologique, UMR CNRS-UPS 5174, Université Paul Sabatier Toulouse III, 118 Route de Narbonne Bat IV R3 entrée b2, Toulouse Cedex 9, France J. M. Avilés Departamento de Biología Animal y Ecología, Facultad de Ciencias, Universidad de Granada, Granada, Spain provisioning. Meanwhile, in females, back brightness was related to the number of fledglings in successful nests and to parental provisioning rate. In addition, there was a positive assortative mating in relation to weight, body condition, head green-yellow saturation and back brightness. Finally, we found a positive correlation between parent and offspring coloration. Altogether, these results suggest that multiple colour traits may act as quality indicators in the roller and that they may be used by the two sexes to assess potential mate quality. Keywords Assortative mating. Coracias garrulus. Multiple mutual ornaments. Plumage coloration Introduction Sexual selection theory proposes that ornamental traits, such as plumage colour or elaborate visual and vocal displays, reliably signal individual quality (Darwin 1871; Andersson 1994). Because elaborate ornamental traits may be costly to produce and maintain, their expression may be quality dependent and only high quality individuals could achieve maximum expression of such traits (Andersson 1994; Hamilton and Zuk 1982; Kodric-Brown and Brown 1984; Zahavi 1975; Zahavi and Zahavi 1997). These sexual selected ornaments might thus provide honest signals of individual phenotypic or genetic quality. Until the last decade, most sexual selection studies focussed on male secondary sexual traits of sexually dimorphic species in which the male is the most ornamented sex. Several studies demonstrated that females prefer to mate with well-ornamented males, as well as fitness benefits of making this choice (review in Andersson 1994). Comparatively fewer studies have investigated the

86 Behav Ecol Sociobiol functional role of female ornaments (review in Amundsen 2000; Amundsen and Pärn 2006; Kraaijeveld et al. 2007). In some monomorphic species, however, both males and females are similarly ornamented, often to a high degree. Female ornaments have been proposed as resulting from genetic correlations with male ornaments and thereby to be non-functional (Lande 1980). Developmental constraints may also lead to non-adaptive female ornamentation (Emlen et al. 2005). On the other hand, a growing body of evidence suggests that female ornaments can also signal either the same or a different aspect of quality as male ornaments (review in Amundsen 2000; Amundsen and Pärn 2006; Kraaijeveld et al. 2007). The mutual selection hypothesis proposes that mutual ornamentation is the result of mutual mate choice (Huxley 1914; West-Eberhard 1979; Johnstone et al. 1996; Johnstone 1997; Trivers 1972; Servedio and Lande 2006), which can lead to assortative mating if males and females have similar preferences. Theoretical models predict that mutual selection is likely to occur when both sexes benefit from mating with highquality individuals of the other sex because both sexes provide a substantial amount of parental care to the offspring (Johnstone et al. 1996; Kokko and Johnstone 2002; Trivers 1972) or because their reproductive success is limited by the other sex s reproductive or parental abilities (Grafen 1990; Heywood 1989; Hoelzer 1989). In birds, plumage coloration is one of the most widespread and conspicuous ornament, and it has been the focus of several tests of the honest signalling theory (Andersson 1994; Hill 2006). Plumage coloration can result from three different mechanisms, which can act alone or in conjunction (carotenoid and melanin pigments or feather microstructure; Hill and McGraw 2006a). Colour production may have different associated costs depending on its origin. Therefore, plumage coloration might convey different information to potential partners and/or competitors (Hill 2006). The informative content of pigment-based plumage colorations has been profusely studied in many avian taxa. Evidence suggests that carotenoid-based plumage colorations are strongly condition-dependent (Hill 1990; von Schantz et al. 1999; McGraw and Hill 2000; reviewed in Hill and McGraw 2006b). For instance, McGraw and Hill (2000) demonstrated that males parasitised by intestinal coccidians showed less saturated carotenoid-based plumage than unparasitised males. Melaninbased plumage colorations, on the other hand, have long been considered to be under genetic control and independent from environmental conditions (e.g. Badyaev and Hill 2000; Bize et al. 2006; Roulin and Dijkstra 2003), although some studies have shown that melanic colours can also be determined by nutritional (Veiga and Puerta 1996) or rearing conditions (Fargallo et al. 2007). In addition, a recent metaanalysis has shown that carotenoid- and melanin-based plumages do not differ actually in their ability to act as honest signals of the quality of their bearers (Griffith et al. 2006). Behavioural ecologists became interested in the function of structural plumage colours only recently. There is a growing evidence that the full expression of such colorations requires good condition during moult (McGraw et al. 2002; Siefferman and Hill 2005a), suggesting that structural plumage ornaments may signal different aspects of individual quality (e.g. Doucet 2002; Keyser and Hill 1999; Keyser and Hill 2000; Doucet and Montgomerie 2003; Hill et al. 2005; Siefferman and Hill 2005b; Solís et al. 2008; Avilés et al. 2008). Hitherto, studies of bird male and female ornamentations have mainly focussed on single conspicuous ornaments. Many species, however, possess multiple ornaments that may or may not be simultaneously displayed by both sexes and that may convey exclusive, overlapping or unreliable information on diverse aspects of condition (Møller and Pomiankowski 1993). Studies of multiple ornaments have focussed on males of promiscuous and polygynous avian species because these groups include some of the most extravagantly ornamented species (Zuk et al. 1990, 1993; Ligon and Zwartjes 1995; Omland 1996; Andersson et al. 2002). Comparatively less attention has been given to multiple colour ornamentation in females (see review in Kraaijeveld et al. 2007). The general aim of our study is to assess the information content of multiple plumage-coloured traits in the European Roller (Coracias garrulus L.). The Roller is a socially monogamous Coraciiform species with biparental care (Cramp and Simmons 1988). Both sexes incubate the eggs, brood and feed the young, even though the female takes a larger share. Females and males appear monochromatic to humans and are similar in size (Avilés 2006). Typical individuals exhibit highly conspicuous structural violet and turquoise colorations in scapulars and rump and head and belly, respectively. Furthermore, they show a melanin-based chestnut back plumage (see Materials and methods ). Both structural and melanin-based plumage patches are conspicuously displayed during the characteristic rolling flight of the species. We used spectrophotometric measurements to account for ultraviolet (UV) information hidden to humans with the aim to investigate in breeding rollers: (1) whether the species is sexually dichromatic, (2) the relationship among the various colour traits in both males and females (Jawor and Breitwisch 2004), (3) whether breeding pairs show assortative mating in relation to components of coloration as would be expected for species in which the two sexes provided substantial care to the offspring, (4) whether coloured traits correlate with individual quality (i.e. body condition, reproductive success and/or reproductive investment) in the two sexes and (5) whether the expression of coloured traits is correlated

87 Behav Ecol Sociobiol between parents and offspring, which would suggest that coloured traits are transmitted either genetically or by maternal or parental effects or are the result of a common environmental effect affecting parents and their offspring colorations. Materials and methods Study system The study was conducted during the breeding seasons in an unwooded area of Cáceres province in western Spain (39 27 N, 6 20 E) where rollers breed in nest boxes placed on the poles of electric lines (Avilés et al. 1999; 2000). The area is characterised by the predominance of dry pastures, which are used by livestock. The European Roller is a migratory secondary holenesting bird (Cramp and Simmons 1988). They mostly arrive to breeding grounds in April and begin to lay in early May (Avilés et al. 1999). The mean clutch size in the study area is 4.23 eggs (range, 1 7; Avilés et al. 1999). Incubation usually begins after the laying of the third egg and takes around 20 days. Due to the incubation pattern, chicks hatch asynchronously. Chick rearing takes 24 days, and both sexes participate in incubation and feeding tasks (authors, unpublished data). Field data collection During the three study years, nest boxes were monitored weekly from mid-april to fledging to determine laying dates, clutch sizes and fledging success. Adult rollers were captured at the nest with an automatic trap at the beginning of the nestling period. We captured eight females and one male in 2005, eight females and seven males in 2006 and 29 females and 28 males in Adults were ringed and measured at capture. We calculated body condition for each individual as the residuals from the linear regression between body weight and tarsus length. Upon capture, a drop of blood was extracted by brachial venipuncture and stored in ethanol for later sexing (see Parejo et al for the detailed protocol) by molecular methods as described by Fridolfsson and Ellegren (1999). Additionally, we plucked three to five feathers from the same location of the following body regions: head (turquoise), scapulars (violet) and back (chestnut). In 2007, to investigate plumage colour transmission, we also collected feathers from fledglings with the same protocol as in adults. Chick feathers were collected from all chicks of a brood when the older chick was 19 days old. At this moment, fly feathers are not fully developed, thus minimising the risk of early nest abandonment. Parental investment In 2006 and 2007, we made behavioural observations at nests in order to estimate parental investment. Observations were made in the morning ( hours) and extended 1 h after the moment we saw at least one adult roller approaching the nest. Two observations were made on each nest, one during incubation (around the 13th day after the onset of incubation; range, 8 18), which allowed us to calculate the time spent by parents incubating at nests per hour and the other in the middle of the chick-rearing period (around the 15th day after hatching; range, 10 20) from which we calculated the rate of visits that parents made to feed their offspring in a per hour basis. As identification of parents was not always possible due to their fast entrance in nests, we calculated all variables for both parents together. Determination of the presence of carotenoid pigments in the different plumage patches We investigated the presence of carotenoid pigments in feathers by following the method described in McGraw et al. (2005). Briefly, 3 5 mg of coloured parts were cut from feathers of the three body regions (see above) from different individuals and introduced in a glass vial. To extract pigments, 1 ml of acidified pyridine was added to each vial, and then the tubes containing tissues and pyridine were capped tightly and heated in a 95 C water bath for 4 h. After this time, tubes were allowed to cool at room temperature. Pigments were present in the feathers whenever the heated pyridine solution was colourful after the treatment, as occurred for back feathers. As pigments may be carotenoids or other different ones, we proceeded with a follow-up analysis to confirm the presence of carotenoids. In this last test, 2 ml of distilled water were added to the coloured acidified pyridine solution, and then the mixture was capped and homogenised by inversion of the tube. Next, 1 ml of hexane/tert-butyl methyl ether (1:1) was added, the tube capped and the mixture shaken vigorously for 2 min. Finally, the solution was centrifuged at 3,000 rpm for 5 min to see whether the colour was retained in the upper (carotenoids) or bottom (non-carotenoids pigments) phases of the solution. Colour measurements For colour measurements, feathers were carefully placed on black paper in a fashion that mimicked the way the feathers naturally lay on the bird. Spectral data was always recorded by the same person (N.S.) in total darkness with an Ocean Optics DH 2000 spectroradiometer. Plumage reflectance was quantified in the range nm with a deuterium and a halogen light source using a bifurcated micron fibre

88 Behav Ecol Sociobiol optic probe at a 45 angle from the feather surface and illuminating an area of 1 mm 2. Using the spectra acquisition software package, OOIBase, we sequentially recorded ten spectra relative to a standard white reference (WS-2) and then averaged the spectra to reduce electrical noise from the collection array within the spectrometer. This process was repeated three times, the probe lifted and replaced on the feather sample between each scan. We then averaged the three spectra for each body region and individual. Colour variables We summarised reflectance data using the three standard descriptors of reflectance spectra: brightness, chroma and hue. Brightness or the total amount of light reflected by the feather was calculated as the summed reflectance from 300 to 700 nm (e.g. Siefferman and Hill 2005b). Chroma, a measure of spectral purity, was the ratio of the total reflectance in the range of interest and the total reflectance of the entire spectrum ( nm; Siefferman and Hill 2003). If the spectra showed a bimodal pattern (i.e. head; Fig. 1), two measures of chroma were calculated, each one corresponding to each peak of reflectance (Chroma UVblue: nm; Chroma green-yellow, nm). Hue referred to the wavelength at which the maximum peak of reflectance is reached. As for the chroma, when the spectra showed a bimodal pattern, one hue value for each of the two peaks was calculated. The spectra of the chestnut back was invariably truncated at 700 nm (Fig. 1); therefore, we used yellow-red chroma and total brightness to summarise chestnut back spectra. Colour variables were then entered into a principal components analysis (PCA) for each body region separately (e.g. Doucet and Montgomerie 2003, Siefferman and Hill 2005b). In Table 1, component loadings for each PCA are summarised. PC scores originated from the three PCAs were then used to define inter-individual differences in coloration: Regarding the head, individuals with a high-positive PC1 colour score displayed an overall less saturated UV-blue plumage coloration and high saturated green-yellow plumage coloration in the head and showed a main peak of maximum reflectance at a higher wavelength than individuals with negative PC1 colour scores (Table 1). In addition, individuals with high-positive PC2 scores for the head showed a brighter head and a secondary peak of maximum reflectance at higher wavelengths in the heads than individuals with negative PC2 colour scores (Table 1). Concerning the scapulars, individuals with a high-positive PC1 colour score showed brighter and more saturated UVblue scapulars and a hue displaced towards shorter wavelengths than individuals with negative PC1 colour scores (Table 1). Regarding the back, individuals with high PC1 a Reflectance (%) b Reflectance (%) c Reflectance (%) colour scores exhibited more brilliant and less saturated yellow-red plumage coloration in the back than individuals with negative PC1 colour scores (Table 1). Statistical analysis Head Scapulars Back Wavelenght (λ) Fig. 1 Reflectance patterns across the whole spectrum of colour patches on the different parts of the plumage: a head, b scapulars and c back in male (continuous line) and female (dotted line) rollers Analyses were performed using SAS statistical software (SAS 2001 Institute, Cary, NC, USA). Sexual differences in size and coloration were tested by running linear mixed models (MIXED SAS procedure) with identity link function and normal distribution, in which sex and study year were entered as a fixed and a random factor, respectively. When investigating sexual differences in coloration, we also introduced in analyses the body condition as a covariable and the interaction term between this variable and the sex to study the relationship between

89 Behav Ecol Sociobiol Table 1 Principal components loadings for colour variables of the different three body regions of the roller Principal components Head Scapulars Back PC1 PC2 PC1 PC1 Total brightness UV-blue chroma Green-yellow chroma Hue of the main peak Hue of the secondary peak Yellow-red chroma 0.71 Variance explained by Each component 56.5% 18.2% 54.3% 78.6% Cumulative 56.5% 74.7% 54.3% 78.6% plumage coloration and body condition in the two sexes. Relationships between different plumage measures of an individual were investigated separately for males and females by Pearson correlations (CORR SAS procedure). Assortative mating was tested by performing a Pearson correlation matrix between mate colour attributes. Since an exploratory analysis showed that the year was nonsignificant, we did not perform linear mixed models with year as a random factor. Relationships between plumage coloration and reproductive variables or measures of parental investment were analysed separately for males and females by means of linear mixed models, except when reproductive success (nesting success versus nesting failure) was the dependent variable for which we used a generalised linear mixed model (GLIMMIX procedure in SAS) with logistic link function and binomial distribution. In these analyses, reproductive variables (laying dates, clutch size, reproductive success and number of fledglings in successful nests) and measures of parental investment (time spent incubating per hour and number of feeding visits per hour) were entered as dependent variables, and all colour variables were entered as covariables. Multicollinearity due to correlation of color of different traits was considered unimportant in these analyses because correlations were largely below 0.7 (Table 3), which is the threshold value over which collinearity should be corrected for (Green 1979). In all models, the year was entered as a random factor, and no interaction terms were considered due to low sample sizes. Finally, to study the relationship between parent and offspring phenotypes, linear mixed models were run in which the colour attribute of the chick was entered as the dependent variable and colour attributes of the same trait of its parents as covariables. The nest was introduced as a random effect to account for the fact that chicks from the same nest are not independent. We performed backward model selection using P=0.05 as the threshold value for elimination. Final models only contained significant effects. Results Origin of roller coloration In the roller, only feathers of the back presented pigments, and head and scapulars feathers were structural plumage. In the back, as the bottom phase (pyridine water phase) of the solution retained the colour of feathers, we concluded that these feathers did not contain carotenoids either, although they seem to contain some other pigment such as phaeomelanin (McGraw et al. 2005). Therefore, we can reasonably assume that the colour traits of rollers that we study here have two different origins: the head and scapulars with a structurally based coloration and the back with a melanin-based coloration. Reflectance patterns of the three plumage parts The reflectance patterns of roller head, scapulars and back are shown in Fig. 1. The head showed a bimodal pattern with a main peak in the green-yellow region ( nm, peak around 555 nm) and a secondary peak in the UV-blue region ( nm, peak around nm). The scapular region reflected the most strongly in the UV-blue region, with a peak in the blue one ( nm, peak around 440 nm). Finally, the back s reflectance spectrum increased continuously from the yellow region (from 550 nm) onwards. Sexual dimorphism and dichromatism Some of the morphological and plumage attributes varied between the two sexes (Fig. 1, Table 2). Rollers were sexually dimorphic in wing length (Table 2), with males (mean±se, n=20.08±1.32 cm, 36) showing longer wings than females (mean±se, n=19.62±0.94 cm, 43). Furthermore, rollers were sexually dichromatic in structural colorations since head and scapular coloration varied between sexes (Table 2). More specifically, males displayed purer UV-bluish heads than females (i.e. lower PC1 scores for the head than females) and purer UV-bluish and brighter scapulars than females (i.e. higher PC1 scores for the scapulars than female; Fig. 1). Melanin-based backs, however, were sexually monochromatic (Table 2), and no year effect was found. Because of these sexual differences in coloration, all the following analyses were done in males and females separately.

90 Behav Ecol Sociobiol Table 2 Linear Mixed Models (Mixed procedure in SAS) with (1) morphological traits as the dependent variables, the sex as a fixed factor and the year as a random factor to look for sexual differences in these traits; and (2) plumage attributes as the dependent variables, the sex as a fixed factor, body condition as a covariable and the year as a random effect to simultaneously look for sexual differences in these attributes and relationships between colour plumage and body condition Trait Independent variables Statistic P value Morphological traits Tarsus length (mm) Sex F 1,77 = Year Z= Wing length (cm) Sex F 1,77 = Year Z= Weight (g) Sex F 1,75 = Year Z= Plumage attributes Head PC1 Sex F 1,75 = Body condition F 1,72 = Sex*Body condition F 1,71 = Year Z= Head PC2 Sex F 1,72 = Body condition F 1,75 = Sex*Body condition F 1,71 = Year Z= Scapulars PC1 Sex F 1,76 = Body condition F 1,73 = Sex*Body condition F 1,72 = Year Z= Back PC1 Sex F 1,73 = Body condition F 1,76 = Sex*Body condition F 1,72 = Year Z= Retained effects in models are highlighted in bold. Relationships between plumage measurements Some of the measurements of plumage coloration were correlated despite the fact that some of these traits have different origins (i.e. pigment versus structural; Table 3). Females that exhibited more green-yellowish heads (i.e. high PC1 scores for the head) displayed less brilliant and purer yellow-red backs (i.e. low PC1 scores for the back; Table 3). On the other hand, males that exhibited more green-yellowish heads (i.e. high PC1 scores for the head) exhibited less brilliant and pure UV-blue scapulars (i.e. low PC1 scores for the scapulars; Table 3). Additionally, males with brighter heads (i.e. high PC2 scores for the head) showed brighter and less pure yellow-red backs (i.e. high PC1 scores for the back; Table 3). Plumage attributes and body condition Body condition was positively correlated to plumage brightness in the head (head PC2) (regression coefficient= 0.03) and also positively related to plumage brightness and negatively to yellow-red saturation in the back (back PC1; regression coefficient=0.03) in the two sexes (Table 2). All other relationships between colour attributes and body condition were non-significant. Furthermore, we did not find any significant year effect in these analyses (Table 2). Assortative mating We did not find assortative mating according to tarsus (Pearson correlation coefficient, r= 0.02, P=0.90, N=27) and wing length (Pearson correlation coefficient, r=0.30, P=0.12, N=27) but found significant positive assortative mating in weight (Pearson correlation coefficient, r=0.42, P=0.03, N=26, Fig. 2a) and body condition (Pearson correlation coefficient, r=0.50, P=0.008, N=27, Fig. 2b). These two positive relationships were maintained after the removal of outliers (Fig. 2a,b; weight, r=0.60, P= 0.002, N=25; body condition, r=0.42, P=0.04, N=25). We further found assortative mating in the degree of greenyellowish colour in the head (Pearson correlation coefficient, r=0.42, P=0.03, N=27, Fig. 2c), as well as in the total brightness of the back (Pearson correlation coefficient, r=0.41, P=0.035, N=27, Fig. 2d). After leaving out outliers (Fig. 2c), we found random mating according to the degree of green-yellowish colour in the head (r=0.20, P=0.33, N=25). Assortative mating was not significant for the remaining colour traits (P>0.05, N=27 in all cases). Plumage attributes and reproductive success and investment Breeding success correlated positively with female back brightness, dullness and yellow-red colour purity (back Table 3 Results from the Pearson correlation matrix among colour plumage measurements of male and female rollers Sex Colour plumage measure Scapulars PC1 Back PC1 Female Head PC (40) 0.04 (40) Head PC (40) 0.06 (40) Scapulars PC (42) Male Head PC (36) 0.27 (36) Head PC (36) 0.03 (36) Scapulars PC (36) Values are correlation coefficient and P values with sample sizes in parenthesis. Significant correlation coefficients at the P<0.05 level are in bold.

91 Behav Ecol Sociobiol Female weight (g) 160 a Male weight (g) Female body condition (g) 30 b Male body condition Female Head PC1 8 6 c Male Head PC1 Female Back PC1 3 2 d Male Back PC1 Fig. 2 Assortative mating on a body weight, b body condition, c head PC1, and d back PC1, in the European Roller. Arrows indicate outliers that we removed to repeat each analysis PC1) once controlled for laying date (Table 4, regression coefficient= 0.41). Additionally, parental provisioning was correlated in the same way with this maternal trait (Table 4, regression coefficient= 0.83). On the other hand, breeding success was correlated to male head brightness (head PC2; Table 4, regression coefficient=0.98). Moreover, parental provisioning was higher in nests of males with pure greenyellow heads (head PC1; Table 4, regression coefficient= 0.44). Except for the relationships between clutch size, reproductive success and success of successful nests with laying date, none of the other relationships were significant (Table 4). Parent offspring relationships in coloration Scapular brightness and UV-blue saturation appeared positively correlated between parents (males and females) and offspring (female scapulars PC1, F 1,51 =4.29, P=0.04, regression coefficient=0.38; male s scapulars PC1, F 1,51 = 10.65, P=0.002, regression coefficient=0.99; nest effect, Z=2.37, P=0.009; Fig. 3a). However, only the relationship between male-offspring scapular brightness and UV-blue saturation remained significant after removing the two outliers (Fig. 3a; male s scapulars PC1, F 1,51 =9.81, P=0.003, regression coefficient=1.03; nest effect, Z=2.53, P=0.006). In addition, male back brightness was correlated with that of their chicks (male s back PC1, F 1,79 =4.55, P=0.04, regression coefficient=0.30; nest effect non-significant; Fig. 3b). Discussion The European Roller appears as a sexually dimorphic and dichromatic species. Males have longer wings and exhibit brighter and more saturated UV-blue heads and scapulars than females. Thus, this dichromatism mainly exists in the UV part of the spectrum so that it remains undetected to humans. Birds usually have a tetrachromatic vision (Goldsmith 1980) and can perceive ultra-violets. Such hidden sexual dichromatism is common in passerines (Eaton 2005), and our results suggest that this also occurs in non-passerines. Furthermore, recent findings suggest that birds vary in their maximum sensitivity to the lower wavelengths and can be classified as violet or ultraviolet sensitive species (Cuthill et al. 2000). Evidence suggests that rollers are violet sensitive (Ödeen and Håstad 2003), and accordingly, we found that the hue of the head and scapulars is biased toward relatively long wavelengths (violet ~ 390 nm) within the ultraviolet region of the spectrum (see Fig. 1). We studied the coloration of three different plumage traits that are either structural- (head and scapulars) or melanin-based (back). Despite these differences, we found that variation in coloration from different body regions is correlated within individuals (Table 3). Male and female melanic chestnut back coloration correlated with the structural head coloration. In addition, colorations with the same origin were correlated in males. However, different

92 Behav Ecol Sociobiol Table 4 Relationship between fitness components and phenotypic traits in rollers Linear Mixed Models or Generalised Linear Mixed Models explaining variation in fitness components. Separate models were run for each sex. The year was entered in all models as a random factor. Starting models are specified. Final models were obtained by backward elimination, with the stepwise removal of all effects with P>0.05. Selected effects in each model are in bold type. Dependent variables Independent variables Females Males Statistic P value Statistic P value Laying date Head PC1 F 1,37 = F 1,31 = Head PC2 F 1,33 = F 1,32 = Scapulars PC1 F 1,35 = F 1,30 = Back PC1 F 1,34 = F 1,29 = Clutch size Head PC1 F 1,33 = F 1,30 = Head PC2 F 1,34 = F 1,28 = Scapulars PC1 F 1,32 = F 1,19 = Back PC1 F 1,37 = F 1,31 = Laying date F 1,39 =45.10 <0.001 F 1,32 =32.18 <0.001 Reproductive success (success vs. failure) Head PC1 F 1,32 = F 1,30 = Head PC2 F 1,33 = F 1,31 = Scapulars PC1 F 1,38 = F 1,29 = Back PC1 F 1,36 = F 1,28 = Laying date F 1,37 = F 1,32 = Success of successful nests Head PC1 F 1,29 = F 1,24 = Head PC2 F 1,28 = F 1,29 = Scapulars PC1 F 1,31 = F 1,25 = Back PC1 F 1,32 = F 1,23 = Laying date F 1,32 = F 1,26 = Time of incubation/hour Head PC1 F 1,28 = F 1,29 = Head PC2 F 1,29 = F 1,27 = Scapulars PC1 F 1,27 = F 1,28 = Back PC1 F 1,26 = F 1,30 = Laying date F 1,25 = F 1,26 = Number of parental provisioning visits/hour Head PC1 F 1,20 = F 1,23 = Head PC2 F 1,19 = F 1,20 = Scapulars PC1 F 1,23 = F 1,19 = Back PC1 F 1,24 = F 1,22 = Laying date F 1,21 = F 1,21 = plumage patches did not provide redundant information. Different aspects of male head coloration predicted body condition, breeding success and food provisioning, while female head coloration only predicted its condition. On the other hand, female but not male back coloration predicted food provisioning and nest breeding success. This suggests that the various colour signals in that species are not redundant and inform on various aspects of the phenotype (Møller and Pomiankowski 1993). Interestingly, results differed in males and females. In the latter, multiple ornaments may function as exclusive indicators of quality (see also Jawor and Breitwisch 2004). But in the former, results suggest that only the head may potentially convey information on individual quality. Interestingly, our results suggest that structural and melanin-based colorations might be condition-dependent in both sexes. Body condition was correlated with head and back brightness in females and males, and the number of fledglings in successful nests was positively related to male head brightness and to female back brightness. Moreover, female back brightness related to the number of parental provisioning rate. Thus, head and back brightness appear to be indicators of quality in males and females, respectively. This supports the condition-dependent expression of structural coloration found in other species in relation to food restriction (McGraw et al. 2002; Siefferman and Hill 2005a) and parasite load (Hill et al. 2005) for instance. Moreover, our results suggest that female traits in rollers signal phenotypic quality as in other species where males provide a significant amount of parental care and in which mate choice is probably reciprocal (Amundsen et al. 1997; Siefferman and Hill 2005a; Johnsen et al. 1996). As an alternative, however, plumage colour could well express social dominance, and for instance, it may be important in competition for territories, affecting the probability of obtaining a place to breed. This could be one factor leading to mutual ornamentation in the roller whenever both sexes experienced the same selection pressure (Kraaijeveld et al. 2007). Unfortunately, this hypothesis cannot be tested with our data set because our sample is restricted to breeders. Therefore, if plumage colour covaries with social dominance, our data are likely to be biased to more ornamented individuals (those that acquired a breeding territory), and then variability in plumage traits should be

93 Behav Ecol Sociobiol A Mean PC1 scores of offspring's scapulars PC1 scores of females' scapulars Mean PC1 scores of offspring's scapulars PC1 scores of males' scapulars 3 B PC1 scores of offspring's back PC1 scores of males' back Fig. 3 Parent offspring regressions in plumage coloration in the a scapulars and in the b back. In a, values for offspring are mean values per nest because the random effect of the nest was significant in the analysis (see text). In b, values are given for each chick of each nest because the random effect of the nest was not significant (see text). Arrows indicate outliers that we removed to repeat the analysis limited. Considering this, we can affirm that our data are conservative, which enhances the importance of the found patterns. Finally, it has been shown that mutual ornamentation may result from selection for sexual mimicry in females that frequently interact with courting males (Kraaijeveld et al. 2007). However, rollers usually arrive mated to their breeding territories and, once settled, only very rarely interact with arriving floaters (Parejo, own unpublished data). Nonetheless, it may still be possible that selection for concealing the sex in females was very strong in winter territories or during migration when group-living habits in rollers are common (Cramp and Simmons 1988). Rollers appear to mate assortatively in relation to weight, body condition, and head green-yellow saturation as well as back brightness. These results are not surprising because these two plumage characteristics seem to indicate individual phenotypic quality. Indeed, parental provisioning rate related to head green-yellow saturation in males and to back brightness in females. In addition, female back brightness correlated with the number of fledglings in successful nests. These relationships between coloration and phenotypic quality may reveal the information conveyed by each colour. Assortative mating based on plumage coloration revealing quality may result from the existence of a mutual choice based on the same ornament. Since the roller males invest in reproduction as much as females, mutual selection would be beneficial. Alternatively, assortative mating may also result from an effect of breeding date if the best individuals arrived earlier to their breeding areas. However, laying date was not significant in all the analyses of assortative mating. Finally, it may be possible that individuals mated assortatively by age and that ornamentation was age-dependent. This might lead to a positive correlation between ornaments of the members of a pair. Therefore, only experiments may allow us to conclude the indicator function of these traits. Interestingly, rollers mated assortatively by two plumage colours of different origin. Positive assortative mating based on structural and melaninbased coloration has been also shown in other birds (e.g. Amundsen et al. 1997; Andersson et al. 1998; Potti and Merino 1996; Roulin 1999). We finally document a positive correlation between parent and offspring coloration, suggesting some kind of transmission of these traits or similar strong environmental effects on parents and their offspring coloration. This transmission may be of various kinds, from genes to maternal or paternal effects. Indeed, there is some evidence that structural colours may be condition-dependent in nestlings while other colours would be relatively more genetically determined (Johnsen et al. 2003). For instance, the transmission of the melanin-based throat patch of house sparrows, Passer domesticus, was shown to be due to environmental factors (Griffith et al. 1999). In addition, although correlative results in the field remain highly controversial, melanin-based colours can also show high broad sense heritability (see revision in Mundy 2006). In the case of the roller, as we did not perform a crossfostering, the mechanism of transmission cannot be known.

94 Behav Ecol Sociobiol Nevertheless, adult back brightness may be under mutual sexual selection, and its transmission from parents to offspring suggests that it may be an important signal in that species. Rollers only make a partial post-juvenile moult that involves head, body, lesser and median upper wingcovers and part of tail (Cramp and Simmons 1988). Furthermore, the first prebreeding moult is rather limited and occasionally absent (Cramp and Simmons 1988). Therefore, first breeders may still have feathers grown as nestlings. In conclusion, we provide tentative evidence that structural and melanin-based colorations of male and female rollers might function as reliable signals of their phenotypic and parental qualities. Furthermore, the existence of assortative mating on some of these traits may suggest that they may be used in mate choice. We finally document the potential for a transmission of structural and melanin-based plumage coloration from parents to offspring. Altogether, these results give correlative support to the hypothesis that multiple coloured traits may act as quality indicators in the roller and that they may be used by the two sexes to assess potential mate quality mutually. Nonetheless, experimental studies are clearly needed to confirm these interpretations. Acknowledgments We thank all the people who collaborated in data collection either in the field (L. Derousse, M. Guillemin, M. Kauffman, M. Kriloff, C. Landsmann, V. Lartigot, X. Mandine and G. Martinerie) or in the laboratory (J. M. Gasent). We also thank I. Cuthill and one anonymous referee for constructive comments that improved our manuscript. Fieldwork was done under the permission of the Junta de Extremadura and in compliance with the Spanish laws. 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Oxford University Press, Oxford Zuk M, Thornhill R, Ligon JD, Johnson K, Austad S, Ligon S, Thornhill N, Costin C (1990) The role of male ornaments and courtship behavior in female choice of red jungle fowl. Am Nat 136: Zuk M, Ligon JD, Thornhill R (1993) Effects of experimental manipulation of male secondary sex characters on female mate preference in red jungle fowl. Anim Behav 44:

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177 Behav Ecol Sociobiol (2008) 62: DOI /s ORIGINAL PAPER Do great tits rely on inadvertent social information from blue tits? A habitat selection experiment Deseada Parejo & Étienne Danchin & Nadia Silva & Joel F. White & Amélie N. Dreiss & Jesús M. Avilés Received: 6 December 2007 /Revised: 4 March 2008 / Accepted: 4 April 2008 /Published online: 28 May 2008 # Springer-Verlag 2008 Abstract Sympatric species sharing requirements are competitors, but recent evidence suggests that heterospecifics may also be used as a source of information. The heterospecific habitat copying hypothesis proposes that individuals of one species might use information inadvertently produced by the breeding performance of individuals of other species to assess habitat quality whenever the two species share needs. In this study, we provide the first experimental test of this hypothesis by examining whether the manipulated reproductive success of blue tits (Cyanistes caeruleus) is used as heterospecific inadvertent social information (ISI) in breeding-habitat selection by sympatric great tits (Parus major). The reproductive success of blue tits was manipulated 1year at the scale of patches by transferring nestlings from decreased to increased patches. No evidence was found of great tits using the reproductive Communicated by J. Lindström D. Parejo (*) Department of Functional and Evolutionary Ecology, Estación Experimental de Zonas Áridas, C.S.I.C., Almería, Spain parejo@eeza.csic.es É. Danchin : N. Silva : J. F. White Évolution et Diversité Biologique (EDB), UMR CNRS-UPS 5174, Université Paul Sabatier Toulouse III, Toulouse, France É. Danchin : J. F. White : A. N. Dreiss Laboratoire de Fonctionnement et Évolution des Systèmes Écologiques, Université Pierre et Marie Curie, CNRS-UMR 7625, Paris, France J. M. Avilés Departamento de Biología Animal y Ecología, Facultad de Ciencias, Universidad de Granada, Granada, Spain success of blue tits as a source of heterospecific ISI. However, dispersal decisions by adult great tits correlated with information on con- and heterospecific densities, which constitute other sources of ISI. As density and breeding performance are tightly intertwined forms of information, the difficulty in distinguishing between them might lead great tits to use heterospecific ISI more in the form of density than breeding performance when making dispersal decisions. Keywords Breeding-habitat selection. Habitat copying. Heterospecifics. Species coexistence. Social information Introduction In community ecology, sympatric species sharing ecological requirements have been usually considered as competitors. The coexistence of species with overlapping resource use has been shown to negatively affect fitness in many animal species (Brown and Davidson 1977; Minot 1981; Gustafsson 1987; Wedin and Tilman 1993; Schmidt and Whelan 1998; Cooper et al. 2007). Consequently, theory predicts heterospecific avoidance during habitat selection to avoid competition (Stamps 1991). In this context, recent experimental evidence suggests the potential use of heterospecific location or abundance as valuable information in breeding-habitat selection (Mönkkönen et al. 1990; Elmberg et al. 1997; Forsman et al. 1998), as well as in foraging-patch selection (see for instance Whiting and Greef 1999, Nieh et al. 2004, and Silverman et al. 2004). Indeed, in breeding-habitat selection, organisms that rely on the location of heterospecifics to settle in a breeding area have been shown to achieve direct fitness benefits (Forsman et al. 2002; see however Forsman et al. 2007). Also, the use of

178 1570 Behav Ecol Sociobiol (2008) 62: information inadvertently produced by the foraging success of heterospecific fishes (Gasterosteus sp.) as a source of heterospecific inadvertent social information (ISI sensu Danchin et al. 2004) has been demonstrated in a foraging context (Coolen et al. 2003). Furthermore, Seppänen and Forsman (2007) have recently demonstrated in a welldesigned experiment that individuals from one species may acquire arbitrary preference of competing informant species for such a trait as a symbol attached to nest sites. Their results show the importance of interspecific social learning in species coexistence. Finally, the heterospecific habitat copying hypothesis (Parejo et al. 2005) states that individuals of one species, to assess local habitat quality, may use information inadvertently produced by the breeding performance of individuals of other species. This hypothesis, which broadens the habitat copying hypothesis (Wagner and Danchin2003) to heterospecifics, states that whenever individuals share ecological needs, they may inadvertently produce valuable information to members of the other species. It is the fact that heterospecifics as well as conspecifics are competitors that makes their performance a valuable source of information about habitat suitability. Therefore, competitors may also be envisaged as potentially beneficial neighbours. Heterospecific habitat copying may thus provide another mechanism, among many others, explaining species coexistence. Heterospecific information may be secondary because it is rather indirect relative to conspecific or other more direct information (Parejo et al. 2005). Indeed, conspecific information likely reveals habitat quality more accurately than heterospecific information because an individual s ecological needs are likely to overlap much more with conspecifics than heterospecifics. However, conspecifics could be, under certain circumstances, suboptimal sources of information compared to heterospecifics (Seppänen et al. 2007). In particular, using heterospecifics as a source of information could reduce intraspecific competition whenever a resource is limiting, and heterospecifics would not compete as severely for that resource (Seppänen et al. 2007). Moreover, in most natural communities, heterospecifics are more abundant than conspecifics and thus more likely to be used as a source of information. Consequently, population density of both con- and heterospecifics may be a factor revealing the suitability of con- and heterospecific cues for habitat selection. Recent theoretical models suggest that conspecific and heterospecific attraction may be most beneficial at moderate population densities (Mönkkönen et al. 1999; Fletcher 2006). Furthermore, Fletcher (2007) has recently demonstrated that, in a bird species, the least flycatcher Empidonax minimus, social attraction to con- and heterospecifics (American redstart Setophaga ruticilla) is more effective at intermediate population densities. Heterospecifics are likely to produce ISI through their location and performance. The use of these two types of information among conspecifics is claimed to be widespread in breeding-site choice of many animal taxa (e.g., Deutsch and Nefdt 1992, Stamps 1987, Danchin et al. 1998, Reed et al. 1999, Doligez et al. 2002, le Galliard et al. 2003, and Parejo et al. 2007a). ISI is highly valuable to indicate local habitat quality for two reasons. First, such information is easier to gather than independently evaluating all habitat characteristics influencing habitat quality such as the amount and quality of food sources, predation pressure, and micro-climate conditions (Boulinier and Danchin 1997). Second, it is reliable because it is not produced intentionally. For instance, individuals are selected to perform as well as possible rather than to inform others, and thus they are unlikely to falsify their performance (Danchin et al. 2004). In this study, we experimentally test whether the manipulated reproductive success of blue tits (Cyanistes caeruleus; see Parejo et al. 2007a) is used as heterospecific ISI in breeding habitat decisions by sympatric great tits (Parus major). This study constitutes the first experimental test of the heterospecific habitat copying hypothesis because, until now, only some correlative evidence in other bird species has supported this hypothesis (Parejo et al. 2005). In the blue tit, correlative evidence suggests that settlement decisions are related to cues produced by conspecifics (Parejo et al. 2007b). Moreover, an experimental manipulation of the reproductive success demonstrated that blue tits use conspecific ISI in their dispersal decisions (Parejo et al. 2007a). In these two cases, results were independent from the local reproductive success of the great tit, indicating that blue tits do not use great tits to gain information. However, both blue and great tits might serve as heterospecific sources of information for the other species because they share ecological requirements and are thus competitors (Dhondt 1989). In our study system, 53.3% of the occupied nest boxes were used by blue tits versus 42.7% by great tits. With such relative densities, great tits have about the same probabilities of acquiring information on breeding-habitat quality through conspecifics as heterospecifics. Furthermore, the two species share requirements (nest boxes and diet) and show a high overlap in their breeding phenology. Thus, heterospecific ISI is likely to be used by these species. The local reproductive success of blue tits in 1year at the scale of patches (patch reproductive success, i.e., mean number of fledged chicks per patch) was manipulated via brood-size manipulations. Patches were either (1) manipulated to decrease the mean reproductive success of blue tits (treatment D), (2) unmanipulated (unmanipulated control), (3) manipulated by cross-fostering chicks between nests within patches of the same treatment, thus leaving blue tit patch reproductive success unchanged (manipulated control), or (4) manipulated to increase the local mean

179 Behav Ecol Sociobiol (2008) 62: reproductive success of blue tits (treatment I). This manipulation of the quantity of juvenile blue tits produced in our study patches altered the quality of juveniles (mean body condition), generating a negative relation between the quantity and quality of fledglings (Parejo et al. 2007a) and thus allowing us to disentangle the role of these two cues (quality and quantity) in breeding-habitat selection. We expect manipulation to influence dispersal decisions in great tits. As number and condition of chicks in each nest are usually positively related, it is logical to assume that the most reliable estimate of quality must result from the use of the two cues simultaneously. If this is the case, we expect a preference of great tits for control (unmanipulated and manipulated control) over manipulated patches (D and I treatments). Alternatively, we might deduce that the correlation offers individuals with the possibility of estimating quality by the use of either of the two cues. In this case, we would expect a preference for both I and D patches relative to control patches (both unmanipulated and manipulated control). Finally, individuals might use only one of the two cues. If they rely on fledging number, for instance, we would expect a preference for I over the control (both unmanipulated and manipulated control) over D patches. Materials and methods Study system and methodology The experiment was conducted during the spring of 2003 and its effects observed during the spring of 2004 in a 500-ha portion of a mixed deciduous forest of the Parc Régional de la Forêt d Orient in central France (Aube, N, 4 17 E). The study area was divided in patches of 8.14 ± 0.90ha each (mean ± SD, Fig. 1). Patches were separated by paths at least 3m wide. In the study area, there were 759 nest boxes evenly distributed over 31 patches, resulting in patches containing an average of ± 0.52 nest boxes each (mean ± SD, Fig. 1). Further details may be found in Parejo et al. (2007a). Blue and great tits commonly used such nest boxes. There were empty boxes in all patches during the study period because nest boxes were provided in excess. The blue and great tits are small, short-lived territorial hole-nesting passerines common in European woodlands (Cramp and Perrins 1993). In the study area, they are mostly sedentary (winter recaptures regularly occur). The mean size of the first clutch was eggs (range = 5 17, N = 228) and 10.4 eggs (range = 5 14, N = 161) for blue and great tits, respectively. In both species, only the female incubates the eggs and broods the young, whereas both sexes feed and clean them. The nestling periods last 16 20days and 16 22days in blue and great tits, respectively (Cramp and Perrins 1993). Fig. 1 Map of the study area with the 31 nestbox patches. Numbers within patches indicate the treatment and the number of nest boxes present in each patch. Patches with no data for the number of nest boxes are wooded patches with no nest boxes. The gray area indicates water, and the non-delimitated white area indicates cultivated fields. Experimental treatments are D decreased patches, C unmanipulated control patches, CM manipulated control patches, and I increased patches As both species are cavity nesters, sharing nest boxes in the same forests, and feed mainly on arboreal arthropods, they can be considered to have overlapping ecology. The nest boxes were checked regularly from nest building (early April) to fledging during each breeding season to determine reproductive parameters and compute emigration and immigration rates. Adults were captured, measured, and ringed in the nest boxes when chicks were from 8 to 13days old or identified during incubation and chicks ringed around 13days old. Measurements taken were body mass (measured with a Pesola spring balance with a precision of 0.1g) and tarsus length (measured with a sliding calliper to the nearest 0.1mm). In the 2003 breeding season, we captured 101 adult great tits, which represented 54.9% of the breeders that raised chicks until the age of

180 1572 Behav Ecol Sociobiol (2008) 62: days, and we marked 837 chicks, which constituted 100% of the chicks that survived until the ringing age. From these marked individuals, only 49 (28 adults and 21 juveniles) were recaptured breeding in In that year, we captured 41.9% of the breeding adults (with 8-day-old chicks). The mortality rate for this species is high, for instance in Britain, mortality ranged from 0.56 to 0.60 (Clobert et al. 1988). Therefore, the low apparent local return rate may be a consequence of the high-mortality rate together with our relatively low capture rate of adults. However, as the adult capture effort in 2003, measured as the probability of each breeder to be captured, did not differ among treatments (logistic regression model: treatment effect, χ 2 3 ¼ 4:80, P = 0.19, N = 210), we can consider observed patterns as representative of the whole population. Dispersal distance between nest boxes used in the two consecutive years was estimated from the Universal Transverse Mercator coordinate of each nest box determined by the Global Positioning System. Position was recorded only when the estimated error was <5m. Emigration was quantified by two variables: dispersal probability between patches in the two consecutive years as a binary variable (resident versus emigrant) and actual dispersal distance between subsequent nest boxes. Despite that data on individual dispersal distance could be skewed if many individuals dispersed very far and hence outside of our study system, we considered this measure in our emigration analyses because (1) the study area was a large (500ha), quite-isolated forest patch. Thus, dispersal seems far more likely to occur inside than outside the study area, and (2) even if some birds dispersed far away, it is important to understand dispersal within our large study system to understand its local population dynamics. The immigration rate was computed as the ratio of the number of immigrants into a patch (number of breeders in the patch minus the faithful breeders) to the number of nest boxes that were available to great tits (nest boxes not previously occupied by insects or small mammals). Another estimate was the observed number of immigrants. These two estimates of immigration are likely to quantify different aspects of the immigration process. Indeed, while the number of immigrants is likely to estimate the attractiveness of a patch, the immigration rate quantifies the relative attractiveness of a patch by accounting for patch occupancy. Population density for each tit species was computed for each patch as the proportion of nest boxes occupied by great or blue tits. This was realistic because patches had approximately the same dimensions and nest box density. Whenever patch dimension varied, nest box density varied proportionately (Fig. 1). The proportion of occupied nest boxes by blue tits ranged from 0.11 to 0.54 (mean = 0.31) and by great tits from 0.04 to 0.36 (mean = 0.17). A nestbox was considered to be occupied when egg-laying began; only first clutches were included in these analyses. Manipulation of blue tit reproductive success Blue tits breeding success was manipulated at the patch scale by removing three 2-day-old nestlings from nests of the D treatment plots to nests (matched by hatching dates) of patches of the I treatment in In addition, nestlings were cross-fostered between pairs of nests of patches assigned to the manipulated control treatment. At the beginning of 2003, each patch was randomly assigned to one of the following treatments: (1) patches with decreased patch reproductive success of blue tits (D, N = 10 patches), in which the success of 51% (X ) of the 49 existing blue tit nests was reduced by removing three chicks; (2) unmanipulated control patches (N = 6 patches), in which no manipulation was performed and the natural blue tits patch reproductive success remained unchanged; (3) manipulated control patches (N = 5 patches), in which 38% (X ) of the 21 blue tit nests had three chicks cross-fostered (both nests belonged to patches of the manipulated control treatment). This manipulation thus did not lead to any change in the blue tits patch reproductive success. (4) Patches with increased patch reproductive success (I, N = 10 patches), in which the success of 49% (X ) of the 51 existing blue tits nests was enlarged. All patches thus included non-manipulated nests. Statistical analyses Analyses were performed using SAS statistical software (SAS 2001 Institute, Cary, NC, USA). As in Parejo et al. (2007a), the effect of the treatment at the level of the patch on fledging quality and quantity was investigated by means of a linear mixed model (Mixed SAS procedure). In this analysis, we tested the effect of the treatment on chick body condition, introducing chick weight as the dependent variable, chick tarsus length and brood age as predictors, and the treatment as a factor. The nest was introduced as a random effect in this analysis because chicks from the same nest are not independent. The effect of the treatment on fledging quantity was analysed by a one-way analysis of variance (ANOVA; GLM SAS procedure) in which the number of fledglings per nest was the dependent variable and the treatment the factor. The effect of the experimental manipulation of the blue tits performance information on the great tits emigration process was studied by performing (1) generalized linear mixed models with logit link function and binomial distribution (Glimmix SAS procedure), in which the probability of each great tit to emigrate from a patch between years 2003 and 2004 was the dependent variable; and (2) linear mixed models (Mixed SAS procedure), in

181 Behav Ecol Sociobiol (2008) 62: which the log-transformed dispersal distance for each individual was the dependent variable. In these analyses, the sex of the individual was introduced as a factor to account for the fact that sex is known to affect dispersal decisions (Greenwood 1980), and blue and great tit densities (arcsin transformed) as predictors to take into account population density (of both con- and heterospecifics) as one of the factors affecting animal dispersal decisions (see review in Clobert et al. 2001). In addition, we introduced the mean patch reproductive success (mean number of fledged chick per patch) of great tits in the models to address the possible influence of conspecific performance information. Finally, the patch was introduced as a random effect nested within the treatment to take into account the possible nonindependence of individuals from the same patch. The effects of the treatment on both the great tits individual emigration probability and dispersal distance were studied separately for juveniles and adults because factors affecting natal and breeding dispersal are likely to differ (Clobert et al. 2001). For juveniles, determinants of dispersal probability could not be analysed because, among recaptured juveniles, only one recruited in its natal patch. When analysing the dispersal of juveniles, the low sample size did not allow us to perform the statistical analysis with the patch nested within the treatment as a random effect. Therefore, to account for this possible non-independence of data, we performed two different analyses of covariance (GLM SAS procedure): one with all the dispersal events and the other one with one random dispersal event per patch. Although the dispersal of adults and chicks from the same nests may not be statistically independent events, we considered them independent in the emigration analysis because all the 49 individuals recaptured in 2004 came from 44 different nests and, except for two individuals that were faithful to both mate and nest in the two subsequent years, no bird coming from a specific nest, either adults or juveniles, went to the same nest as its partner, offspring, siblings, or parents. General linear models and generalized linear mixed models (GLM and Glimmix SAS procedures) were used to test for the effect of the experimental treatment on the immigration rate and on the number of immigrants to a patch. The experimental treatment was introduced in the model as a factor, and blue and great tit densities (arcsine transformed), as well as mean patch reproductive success of great tits as co-variables. Analysis of the number of immigrants was performed with log-link function and Poisson error, using the SAS macro-glimmix. Significance level was set at α = The best-fit model for analyses was determined using Akaike s information criterion as an estimate of the improvement in fit for the addition of variables (Burnham and Anderson 2002). Because the number of data points in the models divided by K (the number of parameters in the model) is always less than 40, AIC was corrected for small sample sizes (known as AICc) following Burnham and Anderson (2002). The model with the lowest value of AICc is the most parsimonious one and therefore the model selected. The Akaike weights give the relative support that a given model has from the data compared with the other models in the set (all information in Burnham and Anderson 2002). Only the five top-ranked candidate models are reported. Our results were qualified by calculating power with the G-Power program version 3.0.5, assuming α = 0.05 and the thresholds suggested by Cohen (1992) for differences or changes in means of 0.2, 0.5, and 0.8 for respectively small, medium, and large effect sizes. Results Manipulation of blue tit reproductive success The experimental manipulation affected mean chick body condition of blue tits (Fig. 2a, modified from Parejo et al. 2007a; Fig. 2a) once the effect of chick age and the random effect of the nest were controlled. Mean body condition of blue tit chicks was higher in D patches than in I patches and in nests in control patches that had, in general, chicks of intermediate condition (Fig. 2a), although in unmanipulated control patches (NMC in Fig. 2), chick quality was almost as high as in D patches. Mean chick body condition, however, did not differ between the two types of control patches. The experimental manipulation also affected the mean fledgling number per breeding blue tit pair per patch (i.e., patch reproductive success; Fig. 2b, modified from Parejo et al. 2007a; Fig. 2b): The mean number of fledglings was higher in I patches and lower in D patches compared to the control patches (Fig. 2b). The mean number of fledglings did not differ between the two types of control patches. Data from the two control treatments (C) were combined for subsequent analyses because neither the mean body condition nor the mean number of fledglings per patch differed between these two treatments. Furthermore, our experiment produced a negative relationship between the mean body condition and mean number of fledglings of blue tits that does not exist under natural conditions in the population, given that we found no relationship between these two variables in blue tit unmanipulated nests after controlling for chick age, chick tarsus length, and the random effect of the nest (see Parejo et al. 2007a). Effect of the manipulation of blue tit reproductive success on great tit emigration We found an effect of the age (juvenile versus adult) of the individual in 2003 on emigration probability (logistic

182 1574 Behav Ecol Sociobiol (2008) 62: Fig. 2 Effect of the experimental manipulation of PI in 2003 on a mean chick body condition and b mean number of chicks per nest. Error bars are standard error. Chick body condition is computed as the residuals of the general linear mixed model performed analysing the effect of tarsus length, chick age at capture, and the random effect of the nest on chick mass. Numbers inside bars are sample sizes of individuals (top panel) and nests (bottom panel). Only significant pairwise differences are shown, with arrows designating pairs and asterisks indicating significant differences. Neither mean chick body condition (P=0.54) nor mean number of chicks (P=0.21) differed between the two types of control patches. Experimental treatments are D decreased patches, NMC control patches, CM manipulated control patches, and I increased patches. *P<0.05. Modified from Parejo et al. (2007a) regression model: χ 2 1 = 21.77, p < , n = 49 individuals) and on dispersal distance (ANOVA: F 1,41 = 62.89, P < , n = 43 individuals). We thus performed separate analyses for each age class. The most parsimonious model to explain adult great tit emigration probability between 2003 and 2004 retained blue and great tit densities and the patch treatment (Table 1). However, neither blue tit density (F 1,23 = 1.54, P = 0.23, n = 28 individuals) nor great tit density (F 1,23 = 2.25, P = 0.15, n = 28 individuals) proved to be related to adult emigration probability. The patch treatment did not affect the adult emigration probability either (F 2,23 = 0.30, P = 0.74, n = 28 individuals, Fig. 3a). A model including great tit density and the treatment showed the same Akaike weights, although in this case, none of the explanatory variables (great tit density: F 1,24 =0.78, P=0.39; treatment effect: F 2,24 =0.35, P=0.71, n=28 individuals) were significant in the model either. The most parsimonious model explaining adult dispersal distance of great tits included heterospecific population density (Table 1). The two variables, adult great tit dispersal distance and heterospecific population density, were negatively related (F 1,20 =8.16, P=0.01, regression coefficient= 1.39, n=22 individuals). Adult dispersal distance did not differ among experimental patch treatments (Fig. 3b) because models in which treatment, great tit density, patch effect (nested within the treatment effect), or sex effects were added had considerably lower Akaike weights than did the selected one (Table 1). The dispersal distance of juvenile great tits did not differ according to the manipulation performed at the patch scale (Table 1). The selected model to explain the dispersal distance of juveniles included blue tit density when we analysed all data and sex when using only one datum per patch (Table 1). However, neither blue tit density (F 1,19 = 1.31, P=0.27, n=21 individuals) in the first analysis nor sex of the individual (F 1,10 =4.93, P=0.05, n=12 individuals) in the second were related to juvenile dispersal distance. Models in which the treatment effect was added had lower Akaike weights (Table 1). Effect of the manipulation of blue tit reproductive success on great tit immigration Great tit local immigration rate from 2003 to 2004 did not differ among treatments (Fig. 3c). The most parsimonious model to explain great tit local immigration rate included conspecific local density, which was positively related (F 1,28 =54.29, P<0.0001, regression coefficient= 0.57, n=31 patches), and heterospecific density, which was negatively related (F 1,28 =6.74, P=0.01, regression coefficient= 0.24, n=31 individuals; Table 1). Nevertheless, it should be taken into account that the great tit immigration rate was not independent of the conspecific local density because the former was estimated as the number of immigrants into a patch (number of breeders in the patch minus the faithful breeders)/number of nest boxes not previously occupied by insects or small mammals, while the latter was the number of faithful breeders. The number of great tit immigrants did not differ among treatments (Fig. 3c). The most relevant model positively related the number of immigrants to local heterospecific density in 2003 (F 1,29 =14.23, P=0.001, regression coefficient=1.80, n=31 patches, Table 1). The model in which

183 Behav Ecol Sociobiol (2008) 62: Table 1 Models for the factors determining emigration and immigration of great tits Model Factors K Deviance AICc ΔAICc Akaike weight Adult dispersal probability 1 BT density, GT density, treatment GT density, Treatment Sex, GT density, Treatment Sex, BT density, Treatment BT density, Treatment Adult dispersal distance 1 BT density BT density, GT density BT density, patch (treatment) BT density, treatment Sex, BT density Juvenile dispersal distance (all individuals considered) 1 BT density BT density, treatment GT density BT density, GT density Sex Juvenile dispersal distance (only one individual per patch considered) 1 Sex Sex, Treatment Sex, BT density Sex, BT density, treatment BT density Local immigration rate 1 BT density, GT density GT density BT density, GT density, GT patch RS BT density, GT density, treatment GT density, treatment Number of immigrants 1 BT density BT density, GT density BT density, treatment BT density, GT density, treatment BT density, GT patch RS The independent variables considered were the sex, the manipulated (patch reproductive success of blue tits = treatment) and unmanipulated inadvertent social information (density of blue and great tits, patch reproductive success of great tit), and the patch nested inside the treatment as a random factor. For each case, only the five top-ranked models are shown. The selected model is in bold type. K is the number of estimated parameters. BT blue tit, GT great tit, RS reproductive success. treatment effect was added had much lower Akaike weights (Table 1). Discussion The experimental manipulation that we performed to modify blue tit patch reproductive success, as one of the forms of ISI, was successful and affected blue tit dispersal decisions (Parejo et al. 2007a). However, our results suggest that great tits do not use the heterospecific breeding performance in their dispersal decisions. There are several potential explanations for the lack of evidence of the use of heterospecific breeding performance by great tits: 1. An experimental design including all possible combinations of quality and quantity of fledglings (high quality high quantity, high quality low quantity, low quality high quantity, and low quality low quantity) could be thought

184 1576 Behav Ecol Sociobiol (2008) 62: Fig. 3 Effect of experimental manipulation of blue tits performance in 2003 on the dispersal probability of adult great tits in 2004 (top panel), the dispersal distance of adult great tits in 2004 (middle panel), and the immigration rate and the number of immigrants to the patches in year 2004 (bottom panel). Numbers inside bars are sample sizes (individuals in the top and middle panels and patches in the bottom panel). P values are provided for the treatment effect. Experimental treatments: D decreased patches, C control patches, I increased patches a Adult dispersal probability (mean+/-se) b P = D C I P = 0.71 Adult dispersal distance (m) (mean+/-se) D C I c 0.3 Immigration rate P = 0.37 Number of immigrants P = Immigration rate Number of immigrants D C I Experimental treatments to be more suitable than the approach used here. That design would generate overlapping predictions for each of the combinations, while our design generates two predictions that separate each combination between quality and quantity of fledglings. Therefore, our experimental design seems to be simpler than and, at least, as valid as the other design to test the working hypothesis. 2. Another explanation relates to time constraints because the gathering of performance based information may occur only during the short time during which heterospecific breeding performance is available (i.e., at the end of the nestling period), and synchrony is likely to be lower among heterospecifics than among conspecifics. 3. Alternatively, in that system, it may well be that costs of interspecific competition exceed the benefits of acquiring information from heterospecifics. In our study area, tit breeding density is not very high (mean number of breeding pairs of tits/ha = 1.5), although other nest box studies have reported density-dependent effects at similar or lower breeding density (e.g., Wilkin

185 Behav Ecol Sociobiol (2008) 62: et al. 2006). In any case, if competition diminishes the value of the information, it would lead to heterospecific avoidance, but for resident great tits, we found exactly the opposite pattern because they appeared to prefer patches with high blue tit densities. 4. Another possibility is that the overlap in resource use between these two species is not great enough to make the information from heterospecifics valuable. However, the two species have been shown to compete during the breeding season (Dhondt 1989) as well as during the winter (Hogstad 1989). Moreover, great tits seem to use information on heterospecific density. 5. Alternatively to the last possibility is the fact that the two study species are residents and non-hoarding tits, and thus, they tend to be equally informed on habitat quality, this diminishing the probabilities of heterospecific information use. The use of information produced by heterospecifics has been suggested to be more likely in situations in which individuals of one species have less accurate information on local habitat quality than the other species (Seppänen et al. 2007). 6. Nevertheless, it is possible that heterospecific habitat copying was not detected simply because that strategy is beneficial only under some environmental circumstances. Our study covered only 2 years, and thus it may be that the use of heterospecific performance information was not advantageous at that moment. Therefore, more multipleyear studies would be needed to elucidate the environmental parameters that influence the role of information on con- and heterospecific breeding performance in breeding habitat choice. 7. Finally, our sample size might not have been large enough to allow us to detect statistically significant differences among treatments in great tit individual dispersal decisions. Indeed, power calculations for our analyses revealed a low power (ranging from 0.11 to 0.14) to detect low effect sizes (0.20), a moderate power (ranging from 0.48 to 0.65) to detect medium (0.50) effect sizes, and a high power (ranging from 0.88 to 0.97) for large effect sizes (0.80). This allows us to conclude that the experimental manipulation of heterospecific performance information does not exert a large effect and probably not a medium effect either on great tit dispersal decisions. Subtle effects of our experiment, however, may be unnoticeable with our sample sizes. Adult great tit emigration and immigration decisions correlated with information on con- as well as heterospecific abundance, which may constitute other potential sources of ISI. Conspecific and heterospecific attraction have been shown in many animals, either as the main mechanism explaining habitat selection (e.g., Forsman et al. 2002, Nocera et al. 2006, and Fletcher 2007) or as one more among all the mechanisms used in a population (e.g., Doligez et al and Parejo et al. 2007a). However, in the literature, apart from the widely accepted use of neighbours as indirect measures of habitat quality (Forsman et al. 2002; Fletcher 2007), other possible mechanisms have been proposed to explain con- and/or heterospecific attraction, such as increased mating success and positive density dependence effects (i.e., the Allee effect; Stamps 1988). Adult great tits dispersal distance negatively related to blue tit density. Meanwhile, the immigration rate in 2004 was positively related to patch-specific conspecific density in 2003 and the number of immigrants to patch-specific heterospecific density. Although the result concerning immigration rate might be affected by the relationship between immigration rate and conspecific local density, the fact that the three analyses indicate the same strengthens the results. Furthermore, great tit immigration rate was negatively related to local heterospecific density in 2003, which may simply be a result of competition. All together, these results suggest that (1) great tits may be influenced by heterospecifics in dispersal decisions but (2) appear to consider conspecifics also in settlement decisions. These results are not surprising if we bear in mind that information availability for emigrants and immigrants may differ greatly (Doligez et al. 2002). Indeed, only local breeders, i.e., emigrants and birds immigrating from immediate vicinity, have access to information about a given breeding patch throughout the breeding season. For many immigrants, the time available to gather information on future breeding patches is limited to the period after breeding, which may constrain immigrants in gathering information on the easiest cues, which are extracted from conspecifics. The use of information produced by con- or heterospecific density rather than performance may result from the longer time availability of the former. Local population density may be evaluated all year long, including at the beginning of the following season, while information on breeding performance may be assessed only during a short time at the end of each reproductive season (Boulinier et al. 1996). Consequently, habitat selection based on density is likely to be a more ubiquitous strategy in resident birds such as the great tits as they spend much of the year in the reproductive habitat. Similar studies on the collared flycatcher (Ficedula albicollis) suggest that conspecific density likely constitutes a valuable source of information even in migratory species (Doligez et al. 2004). None of the variables analysed seems to affect juvenile dispersal decisions. Although the use of information produced by the breeding performance of neighbours is particularly expected in juveniles because they cannot rely on their own reproductive success (Danchin et al. 1998), juveniles may be unable to gather this kind of information due to time constraints (Doligez et al. 2004; Nocera et al.

186 1578 Behav Ecol Sociobiol (2008) 62: ; Parejo et al. 2007a). Similarly, our results suggest that ISI taken from local population density is probably less influential in great tit juveniles, as their dispersal decisions were not associated to con- and/or heterospecific density. Great tits in our population seemed not to rely on conspecific breeding performance. However, as this variable was not manipulated in our study, we cannot conclude definitively that great tits do not use it, only that their dispersal decisions seem to be more influenced by con- and heterospecific density as sources of ISI. In conclusion, our study reveals that great tits might use interspecific ISI more in the form of density than actual breeding performance. When making habitat selection decisions, great tits did not appear to respond to the manipulated blue tit reproductive success, either to the number or to the condition of fledglings, but seemed to be influenced by heterospecific density. The basis of this may reside in the difficulty in distinguishing between these two tightly intertwined forms of information, density, and breeding performance. As we manipulated only heterospecific breeding performance and not heterospecific density, our only firm conclusion is that heterospecific breeding performance is not the main cue used by great tits when selecting a breeding habitat and that it is apparently less influential than heterospecific density. As habitat copying may be defined as breeding habitat selection based on ISI (Wagner and Danchin 2003, Danchin et al. 2004), and great tits seem to rely on heterospecific density as a form of ISI, we may conclude that great tits might be using a heterospecific habitat copying strategy. Acknowledgment We wish to thank all people who collaborated in data collection: I. Dworzynska, C. Loiseau, J. B. Mihoub, F. Moyenne, L. Pichegru, M. Xavier, and many others. M. 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188 J. Avian Biol. 38: , 2007 doi: /j x # 2007 The Authors. J. Compilation. # 2007 J. Avian Biol. Received 28 September 2006, accepted 12 February 2007 Within-brood size differences affect innate and acquired immunity in roller Coracias garrulus nestlings Deseada Parejo, Nadia Silva and Jesús M. Avilés D. Parejo (correspondence) and J. M. Avilés, Department of Functional and Evolutionary Ecology, Estación Experimental de Zonas Áridas, Almería, C.S.I.C. Spain. parejo@eeza.csic.es. N. Silva, Evolution et Diversité Biologique (EDB), UMR CNRS-UPS 5174, Université Paul Sabatier-Toulouse III, France. Present address of JMA: Department of Animal Biology, University of Granada, E-18071, Granada, Spain. The immune system has a crucial importance determining animal health and survival. Its maintenance and activation are costly and usually trade with other physiologically costly functions. In birds, number and size of siblings in a nest are likely to determine the development of immunity. Indeed lower immunocompetence is expected in large than in small broods. Moreover, in asynchronous breeders, siblings are expected to differ in immunocompetence because asynchrony produces marked size hierarchy within-broods. Here we studied the effect of environmental conditions at the nest, chick sex and size, and natural mass differences among siblings due to hatching asynchrony on the development of the innate and acquired immune systems in the threatened non-size dimorphic asynchronous breeder European roller Coracias garrulus. Constitutive innate immune function was estimated by using a new technique proposed by Matson et al. (2005). Natural Antibody (NAb) and Complement levels, innate immunity, varied with the mass difference between each chick and its heaviest sibling. NAb levels were higher in late-hatched siblings compared to early-hatched ones, indicating that the smallest offspring in each brood has the most developed innate immune system. This relationship was independent of the nest environment. The heterophil/lymphocyte (H/L) ratio, which may indicate the level of stress, was higher in the heaviest siblings of each brood. In addition, the H/L ratio and white blood cell count (WBC) of nestlings, measures belonging to both the innate and acquired arms of the immune system, were related to conditions suffered in the nest. Our results may be explained by differential allocation of resources by female rollers as a way to improve the survival of the whole brood. Disease is one of the most important evolutionary agents (Haldane 1949). Animals face pathogenic or parasitic infections by the activation of their immune system (Zuk and Stoehr 2002). Immune response is, thus, a physiological mechanism enhancing animal health and survival (Johnsen et al. 2000, Råberg and Stjernman 2003, Møller and Saino 2004). However, the maintenance of the immune system in absence of infection (e.g. Lochmiller and Deerenberg 2000, but see Klasing 1998), and mounting an immune response (Bonneaud et al. 2003), are nutritional and energetically demanding processes that may monopolize many of the nutrients and energy that could be used for other costly functions (Sheldon and Verhulst 1996, Lochmiller and Deerenberg 2000). For instance, immunity may trade with nestling growth (Saino et al. 1997, Fair et al. 1999, Soler et al. 2003, Mauck et al. 2005), investment in reproduction (Festa-Bianchet 1989, Moreno et al. 1999, Bonneaud et al. 2003, Ardia 2005), and body condition (Sanz et al. 2004). Therefore, immunity can be disadvantaged during stressful periods as the result of reallocation of resources towards other energetically costly functions. Chick immunocompetence in birds is mediated by parents and by environmental conditions. Parents influence genetically their offspring s immune system and may influence the environment in which the offspring develops by parental effects. Furthermore, number and size of siblings in a nest can determine the degree of competition within broods (Mock and Parker 717

189 1997) and hence the energetic stress suffered by each chick during its growth. This stress is likely to affect the development of immunity because chicks in poor condition usually have low immunocompetence (Saino et al. 1997, Alonso-Álvarez and Tella 2001). It seems obvious that chicks in larger broods should suffer more energetic stress than those in smaller broods (e.g. Naguib et al. 2004). In addition, we can predict that older chicks suffer less energetic stress since they are more competitive than the smaller ones. However, the way in which parents may allocate resources within their broods to reduce sibling competition, might change this to a different pattern from that predicted (Martínez-Padilla et al. 2004). The immune system of vertebrates consists of two branches, a non-specific, innate branch and a more specific, acquired branch (Male and Roitt 2000). The innate immune system provides non-specific initial protection to parasites and infections. Meanwhile, the acquired immune system provides later and more specific protection against foreign agents. The two branches are constituted by defensive cellules (cellular component), and soluble molecules or cell associated receptors which respond to specific antigens (humoral component). Although the innate and acquired immune systems seem to be combinatorial systems (Fearon 1997), each compartment of them indicates variations in different aspects of individual condition (Ots et al. 1998, Matson et al. 2005). Thus, it seems appropriate to simultaneously investigate different parts of the immune system when studying its ecological and/ or evolutionary sources of variation (Matson et al. 2005, 2006, Mendes et al. 2006). In this study we measured innate and acquired immune systems in chicks of a wild population of a non-dimorphic bird, the European roller Coracias garrulus. We measured natural antibodies and the complement cascade as innate humoral immunity. Natural antibodies (NAb) recognise and attach to invading organisms and also initiate the complement cascade (Ochsenbein and Zinkernagel 2000). Their levels have been shown to parallel general disease resistance (Parmentier et al. 2004). Regarding the complement cascade, it recognises and kills invading organisms by lysing cells. Its deficiency is related to a range of diseases (Matson et al. 2005). We measured the relative amount of leucocytes (Total White Blood Cell Count, WBC hereafter) and the heterophil/ lymphocyte ratio (H/L hereafter) as components of both the innate and acquired immune systems. Leucocytes include cells belonging to both the innate (heterophils) and acquired (lymphocytes) arms and protect against various pathogenic antigens. High levels of leucocytes circulating are symptomatic of stress syndrome and inflammatory processes (Ots et al. 1998). Heterophils, as part of the white blood cells, protect in a non-specific way against antigens. Meanwhile, lymphocytes are highly specific defensive cells. The ratio H/L is used as an estimator of stress in response to infectious diseases, starvation and psychological disturbance (Ots et al. 1998). Therefore, these two measures could provide information on individuals health. Rollers are particularly suitable for investigating the link between hatching asynchrony and immune function development within broods. Incubation begins before clutch completion, thus nestling rollers usually hatch at one day intervals (Cramp and Simmons 1988), which results in patent size hierarchies within broods (Sosnowski and Chmielewski, 1996, this study Figs. 1 and 2). The main aim of this study was to assess the effect of environmental conditions at the nest, chick sex, size and mass, and natural mass differences among siblings due to hatching asynchrony on the development of the immune system in the roller. We predicted that: (i) different pairs should have chicks with different immunity as a function of the interaction between parental quality and environmental conditions during the rearing period (e. g. Saino et al. 1997, Chin et al. 2005). In addition, we expected that (ii) chicks withinbroods should differ in their immunity because they Fig. 1. Relationship between the size position of roller chicks in their broods with: (a) natural antibody levels, and (b) level of complement activity of these chicks. NAb level was calculated at the step where agglutination stopped and level of complement activity at the step where lysis stopped. Mass position of each chick was calculated as the difference between its weight and the weight of its largest sibling. 718

190 Fig. 2. Effect of body mass difference between each chick and its heaviest sibling on the Heterophil/Lymphocyte ratio of roller nestlings. The y-axis represents the residuals from the general linear mixed model performed controlling for the effect of brood size as a covariable and of nest as a random factor. presumably are under different nutritional stress as a consequence of hatching asynchrony (e.g. Martínez- Padilla et al. 2004). Also, because the sex of nestlings may influence the development of the immune function (Grossman 1985, Moreno et al. 2001, Dubiec et al. 2006), we considered the sex of nestlings in our analyses. We have not, however, a clear prediction concerning the sex of the nestlings due to the absence of sexual-size dimorphism in this species. Materials and methods Study system The study was conducted during the 2005 breeding season in an unwooded area of the Cáceres province, in western Spain (39827?N, 6820?E) where rollers breed in nestboxes placed on electric poles crossing the area. The area is characterized by the predominance of dry pastures. The roller is a threatened secondary hole-nesting bird (Cramp and Simmons 1988) that uses nest-boxes where natural cavities are scarce (Avilés and Sánchez 1997). It is a sexually monomorphic and monochromatic species (Avilés 2006). The roller is a socially monogamous species, both sexes incubate the eggs, brood and feed the young but the female takes a larger share. Incubation takes 20 d and rearing takes 24 d (Cramp and Simmons 1988). Nest boxes were monitored every 10 days from early May to fledging to determine laying dates, clutch sizes, and fledging success. Hatching order in broods was not directly established because a higher frequency of visits to nests would have produced disturbance to such a threatened species. Thus, we considered that mass hierarchy reflected hatching order. This assumption is supported by one-day visits during the entire hatching period to five nests in the same area (J. M. Avilés unpubl. data). In these nests, chicks hatched during the first three days of the hatching period grew at a similar rate while chicks hatched after that time grew slower. Moreover, in these nests mass hierarchy always reflected hatching order. When the older chick in each brood was 19 days old, chicks were weighted to the nearest gram with a Pesola spring balance and their wing lengths measured with a rule to the nearest 1 mm. Additionally 225 ml of blood were extracted by brachial venipuncture. Blood collected was stored refrigerated until centrifugation and plasma removal. Then, plasma was frozen for storage until assessing innate immune response. Blood cells were stored in ethanol for later sexing. Also, a drop of blood was smeared on a slide, air-dried and fixed in ethanol until measuring acquired immune response. Nestling size was measured by wing length and body mass. We used these two measurements because nestling body mass may be more related to condition than wing length. We also calculated the wing length and mass difference between each chick and its larger or heavier sibling at 19 days of age to measure the rank of a chick in the within-brood size/mass hierarchy. These two ranks were highly correlated in each chick (F 1, , PB0.001, regression coefficient 0.53), after accounting for the random effect of the nest (Z0.20, P 0.42) and consequently we only used the mass difference in our analyses to avoid collinearity. Sex identification Individuals were sexed by using a polymerase chain reaction (PCR) amplification based on the technique used by Fridolfsson and Ellegren (1999). DNA was isolated from the red blood cells by boiling them in 100 ml of 50 mm NaOH for 20 min in a thermocycler. PCR amplification was performed in 20 ml volumes on an Applied Biosystems GeneAmp PCR System Final concentrations were: 5 mm MgCl2, 0.2 mm dntps (each; Bioron GmbH), 0.25 mm (each) 2550F/ 2718R primers (Fridolfsson and Ellegren 1999), mg/ml BSA (Amersham Biosciences), 0.5 U Taq DNA polymerase (Bioron GmbH) and 1 ml raw extract. Thermal profile used was: 948C for 2 min, 558C for 30 s, 728C for 1 min, followed by 36 cycles (928C for 30 s, 528C for 30 s, 728C for 30 s), and a final 728C for 5 min step. PCR products were separated in 3% agarose gels run in standard TE buffer and visualized by SyBRSafe (Invitrogen) staining. Measuring immunity Assessment of innate humoral immunity was made by using the new assay described in detail by Matson 719

191 et al. (2005). Briefly, this assay is based on NAbmediated complement activation and red blood cell agglutination. The agglutination reaction measures the interaction between NAb and antigens and the lytic reaction measures the amount of hemoglobulin released from the lysis of exogenous erythrocytes, which is a function of the amount of lytic complement proteins present in the sampled blood. The assay is specially designed for small or threatened wild birds because it requires only a small (100 ml) blood sample and because information can be collected in a single visit to the nest. Quantification is done by serial dilution of plasma samples and assessment of the dilution step at which either the agglutination or lysis reaction against the same amount of rabbit blood cell suspension stopped. Plates are vortexed for 10 s at a low speed, and set to incubate at 378C for 90 min. After incubation plates are tilted at a 458 angle along their long axis for 20 min at room temperature, and then scanned (Microtek Scanmaker 5900, Carson, USA) using the positive transparency (top-lit) option and a full-size image (300 dpi). Subsequently, plates are kept at room temperature for an additional 70 min and scanned for a second time to record maximum lytic activity. We then quantified agglutination (measures NAb) and complement-mediated lysis by assessing the dilution stage (on a scale from 1 to 12) at which these two reactions stopped (further details in Matson et al. 2005). The measure of acquired immunity was made by examination of blood smears that were stained with azure-eosin. Total number and proportion of different types of leucocytes were estimated in slides. This was made on the basis of an examination of a total of 100 leucocytes under oil immersion. Estimates of the WBC were obtained by counting the number of leucocytes per approximately 10,000 erythrocytes. Differential leucocyte counts were obtained by multiplying their proportions with WBC. In the analyses, only data for lymphocytes and heterophils as the most numerous immune cells are used. Statistical analyses Chick was used as the statistical unit in analyses. However, because nestlings in a given nest share parents and environmental conditions, the nest was introduced as a random factor in all statistical models. Immunological variables were NAb level, complement-mediated lysis, WBC and H/L ratio. NAb data were log 2 - transformed to achieve normality. We performed linear mixed models (LMM) with the MIXED procedure of SAS (SAS 1999) to analyse the relationship among immunological variables accounting for the random effect of the nest. LMM were also used to analyse if the immunological variables, as dependent variables, were affected by the nestling sex, as a fixed factor, by nestling wing length, nestling mass, position of the chick in the within-brood mass hierarchy and brood size of the nest, as covariables, and by the nest as a random effect. Laying date might affect nestlings immunology in this species because its reproductive parameters has been shown to decline seasonally (Avilés et al. 1999). However, we did not introduce this variable in analyses because laying date and brood size correlated in the study system (F 1, , PB0.002) and thus we considered that introducing brood size in models we accounted for laying date. Model selection was carried out by backward stepwise procedures, testing the significance of each variable one by one, and removing only the variable that resulted in the largest increase in model fit. The nest as a random effect was an exception to that rule because it was always retained in statistical models. The result is the most adequate model for explaining the variability in the response variable. In this study, 37 nests with 114 nestlings were considered. Variations in sample size among statistical analyses were due to the fact that some morphological or physiological data were unavailable for some broods or nestlings. Results Relationships between components of the immune system The two innate components measured here, i.e. NAb level and complement-mediated lysis, were negatively related (F 1, , PB0.001, regression coefficient 0.399) after controlling for the random effect of the nest (Z1.30, P0.10). On the other hand, WBC and H/L ratio were positively correlated (F 1, , PB0.003, regression coefficient 45.90), after controlling for the significant random effect of the nest (Z2.28, P0.01). Regarding the relationship among innate and mixed components of immunity, WBC was correlated neither with the NAb levels (F 1, , P0.96; nest effect: Z2.09, P 0.02), nor with the complement-mediated activity (F 1, , P0.76; nest effect: Z2.11, P 0.02). The H/L ratio was correlated neither with the NAb levels (F 1, , P0.20; nest effect: Z 2.03, P 0.02), nor with the complement-mediated activity (F 1, , P0.46; nest effect: Z1.96, P0.02). 720

192 Innate immunity: natural antibodies and complement activity NAb levels were positively related to mass difference between the target chick and its largest sibling (Table 1), i.e. lighter chicks of each brood had higher level of NAb compared to heavier ones (regression coefficient 0.015, Fig. 1a). NAb levels, however, were not affected either by the nest of origin, the number of siblings sharing the nest (brood size), the sex of the chick, and the wing length and mass of the chick during blood sampling (Table 1). The level of complement activity was negatively related to mass differences (regression coefficient 0.03, Fig. 1b) between the target chick and its heaviest sibling in a brood (Table 1). This result involves that the lighter chicks of each brood had less complement activity. This result was independent of the nest in which the chicks were being raised, brood size, sex, wing length and mass of the chick (Table 1). Mixed immunity: leucocyte counts When we controlled for the brood size of the nest, the H/L ratio was negatively related to mass difference between the target chick and its heaviest sibling (Table 1), i.e. heavier nestlings inside broods had higher H/L levels (Fig. 2). Moreover, H/L was dependent of the nest in which the chick was being raised (Table 1). Neither sex, nor nestling wing length or mass influenced H/L (Table 1). No relationships were found between WBC and chick wing length, chick mass, chick sex, brood size and mass difference (Table 1). WBC was only dependent of the nest in which the chick was being raised (Table 1). Discussion Our results show the importance of the position of chicks in the mass hierarchy of a brood to determine their innate and acquired immunity. The relationship found between the NAb level and difference between body mass of the chick and its heaviest sibling, which is likely to be the oldest, indicates that these antibodies in roller nestlings increase with differences to the heaviest sibling, i.e. their levels are higher in late-hatched siblings compared to early-hatched ones. This means that NAb levels depend on within-brood mass hierarchy and that the lightest offspring in each brood has a more developed innate immune system than their heavier Table 1. Determinants of innate and acquired immune arms in nestling rollers. Linear mixed models for each immune variable were used with: 1) nestling size measured by wing length and nestling mass, mass difference between the chick and its heaviest sibling and brood size as covariables, 2) nestling sex as a fixed factor, and 3) the nest as a random factor. Non-significant terms were backward eliminated when their removal improved the model fit, otherwise they remained in the model. Retained terms are in bold type. Response term Sources of variation Statistic P-value NAb level Sex F 1, P0.45 Wing length F 1, P0.32 Body mass F 1, P0.11 Mass difference F 1, P0.034 Brood size F 1, P0.15 Nest Z1.40 P0.09 Level of complement activity Sex F 1, P0.78 Wing length F 1, P0.19 Body mass F 1, P0.24 Mass difference F 1, P0.049 Brood size F 1, P0.96 Nest Z0.34 P0.37 H/L index Sex F 1, P0.20 Wing length F 1, P0.98 Body mass F 1, P0.55 Mass difference F 1, P0.03 Brood size F 1, P0.25 Nest Z1.90 P0.03 WBC Sex F 1, P0.64 Wing length F 1, P0.13 Body mass F 1, P0.47 Mass difference F 1, P0.70 Brood size F 1, P0.32 Nest Z2.24 P

193 siblings because high levels of NAb seem to parallel general disease resistance (Parmentier et al. 2004). Different interpretations could explain the relationship between Nab levels and within-brood mass hierarchy. First, higher levels of NAb in late compared to early-hatched chicks could reflect a higher level of infection in the former individuals. However, contrary to all the other immunoglobulin molecules (Pereira et al. 1986, Boes 2000), the level of NAb does not depend on previous exposure to specific antigens. Moreover, if junior chicks were more infected than senior chicks, their level of WBC and/or the H/L index should be more elevated in junior than in senior chicks because these indexes express stress in response to inflammatory processes and infectious diseases. However, we found exactly the opposite pattern and late-hatched chicks showed lower H/L ratio than their older siblings. A second explanation for our results is that females might allocate more immunoglobulins (Ig) in the last eggs in order to benefit late-hatched young more than earlyhatched ones. Nestling mortality not attributable to nest or adult predation and thereby due to brood reduction is very low (9.09% of the n 143 eggs hatched did not produce a fledging in our study population). Thus, differential allocation of inmunoglobulins within broods could be the mechanism by which asynchronous rollers may avoid detrimental effects of brood reduction. Saino et al. (2001) found the same immunocompetence pattern within broods of barn swallows Hirundo rustica. Barn swallows have also hatching asynchrony and brood reduction seems not to be a common reproductive strategy in their population (Saino et al. 2001). In all the other species in which within-brood variations in immunocompetence were measured, immunity was either similar among siblings or higher in senior than in junior siblings (house martin Delichon urbica: Christe et al. 1998, barn owl Tyto alba and blue tit Parus caeruleus: Roulin et al. 2003, blackheaded gull Larus ridibundus: Müller et al. 2003), irrespectively of the species specific level of hatching asynchrony or brood reductionism. Nevertheless, maternal Ig seem to contribute little to the NAb level as indicated by the low level of agglutination by plasma from young chicks (Matson et al. 2005). However, perhaps a little contribution is enough to mediate within-brood variation in NAb or this variation is mediated by other maternally controlled substances. Indeed, and as a third possibility to our results, mothers could deposit decreased yolk androgen (immunosuppresors) levels over the laying sequence to improve the advantages of bigger chicks, as a way of hormonal favouritism (Schwabl et al. 1997), thus prejudicing their immune system. This androgens deposition pattern has been found in two non-reductionist species but with hatching asynchrony: the american coot Fulica americana (Reed and Vleck 2001) and the zebra finch Taeniopygia guttata (Gil et al. 1999), but also in a siblicidal species such as the cattle egret Bubulcus ibis (Schwabl et al. 1997). This mechanism of hormonal favouritism would favour increased growth and worse immunity of senior compared to junior chicks as the consequence of the existing trade-off between growth and immunity (Soler et al. 2003). This explanation is supported by the high H/L values found in early compared to late-hatched nestlings. This could indicate a high growth rate in old nestlings that would produce nutritional stress and the high levels of the ratio H/L. Also, unpublished data in which nests were visited daily suggests that older siblings grow faster than younger ones (J. M. Avilés unpubl. data). Nevertheless, only an experiment would allow distinguish among the different possible mechanisms at work. However, we found that the level of complement activity in nestlings of roller broods had the opposite pattern than the NAb level, i.e. the complement level decreased with the increase in body mass difference between each chick and its senior sibling irrespective of the nest. This result is probably due to the fact that the lysis titres reflect the interaction of NAb and complement, not only the complement (Matson et al. 2005). The advantage shown by late-hatched nestlings within each brood seems to be extended to the H/L index because in roller nestlings this index increased when mass differences decreased. This pattern shown for H/L ratio is not the consequence of older chicks showing a more developed acquired immune system because our analyses revealed that the values of H/L ratio were independent of wing length, which is a variable that is likely to reflect nestling age. Since the H/L index indicates stress due to inflammatory processes, infectious diseases or nutritional restrictions, it is reasonable to conclude that junior nestlings are the less stressed nestlings within broods of rollers. This is in agreement with the results obtained in the kite Milvus migrans in which senior males had the maximum stress in broods, probably as a consequence of their greater activity and aggressiveness to impose their control in the brood hierarchy (Blanco et al. 2006). In the roller, senior chicks seem also to be dominant because they grow faster than junior siblings (J. M. Avilés unpubl. data). Furthermore, there is some evidence of sibling aggression from senior to junior siblings within a brood (D. Parejo pers. obs.). Interestingly, we found a nest effect when analysing factors influencing WBC and H/L ratio but not innate immunity (Table 1). The explanation to this could be found in the fact that the acquired immunity measures the response of the individual to foreign agents while the innate immunity measures the level of existing defence even in the absence of infection. That is, the acquired immune system may be highly dependent of the environment and hence of parental condition. 722

194 Therefore, the dependence of the H/L index and the WBC of the nests may indicate that different broods are under different parasite load and/or level of infections. In contrast, the pattern found for the NAb levels within-broods seems to be consistent through the different nests and then NAb levels seem to be more the consequence of genetic or maternal effects than of environmental conditions. No effect of the nestling sex was found in any of our analyses. Contrarily to size dimorphic birds, in the roller both sexes are similar in size, thus it is not surprising the lack of a sex effect on the development of the within-brood immune system because the main effect was mediated by the size hierarchy and this is independent of the sex in size non-dimorphic birds. Conclusions Our study shows the existence of within-brood variations in roller chick s immunity suggesting that junior siblings within each brood show the best immunocompetence. Since the link between immunocompetence and future survival and then fitness is well established (e.g. Christe et al. 1998, 2001, Moreno et al. 2005), our results could indicate that roller junior chicks are provided with better arms to survive compared to their older siblings. However, we cannot discard that better immunity in junior chicks compared to seniors was a by-product of the immunosuppressive effect of a higher allocation of testosterone by the female to the chicks. Therefore, the link between chick immunity and maternal allocation of Ig and testosterone in eggs within-broods remains to be elucidated. Furthermore, this is the first time, to our knowledge, that a suite of immune system measures has been applied to study within-brood variations of immunocompetence in a bird species. Despite the importance of these variations in animal life history strategies and fitness, only a few studies have been focused on withinbrood variations in one measure of immunity (see however Christe et al. 1998, Saino et al. 2001, Müller et al. 2003, Roulin et al. 2003). Moreover, the study of several immune components, although of pivotal importance, has not been faced many times (but see Ots et al. 1998, Matson et al. 2006, Mendes et al. 2006). Finally, we have successfully used a very new and low invasive technique to assess constitutive innate immune function in a wild population of a threatened bird. Our success in doing that in the roller leads us to recommend this technique with other threatened species for conservational purposes. Acknowledgements We thank all people who collaborated in data collection either in the field (L. Derousse, M. Kauffman and G. Martinerie) or in the laboratory (J. M. Gasent, A. Moreno). J. Carranza kindly allowed us to use his laboratory equipment. We are indebted to J. J. Soler for interesting discussions on immune function trade-offs. C. Navarro helped us in the laboratory. Fieldwork was done under permission of the Junta de Extremadura and complying with the Spanish laws. This research work was partially supported by a doctoral grant to NS by the European Social Fund, I3P contracts to DP and JMA funded by the European Social Fund and by the Spanish Ministerio de Educación y Ciencia (project ref. CGL /BOS). References Alonso-Álvarez, C. and Tella, J. L Effects of experimental food restriction and bodymass changes on the avian T-cell-mediated immune response. Can. J. Zool. 79: Ardia, D. R Individual quality mediates trade-offs between reproductive effort and immune function in tree swallows. J. Anim. Ecol. 74: Avilés, J. M Carraca europea Coracias garrulus. In: Carrascal L.M. and Salvador A. (eds). Enciclopedia Virtual de los Vertebrados Españoles. Museo Nacional de Ciencias Naturales. Avilés, J. 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218 doi: /j x Condition-dependent genetic benefits of extrapair fertilization in female blue tits Cyanistes caeruleus A. N. DREISS,* N. SILVA, M. RICHARD,* F. MOYEN,à M. THÉRY,à A. P. MØLLER & É. DANCHIN *Laboratoire Fonctionnement et Évolution des Systèmes Écologiques, Université Pierre et Marie Curie-Paris 6, Paris, France Laboratoire Évolution et Diversité Biologique, Université Paul Sabatier, Toulouse, France àmuséum National d Histoire Naturelle, Département d Écologie et de Gestion de la Biodiversité, CNRS UMR 5176, Brunoy, France Laboratoire de Parasitologie Évolutive, Université Pierre et Marie Curie-Paris 6, Paris, France Keywords: Cyanistes caeruleus; extrapair fertilization; genetic benefit hypothesis; genetic similarity; plumage colour; song. Abstract In many socially monogamous birds, both partners perform extrapair copulations (EPC). As this behaviour potentially inflicts direct costs on females, they are currently hypothesized to search for genetic benefits for descendants, either as good or complementary genes. Although these hypotheses have found some support, several studies failed to find any beneficial consequence of EPC, and whether this behaviour is adaptive to females is subject to discussion. Here, we test these two hypotheses in a natural population of blue tits by accounting for the effect of most parameters known to potentially affect extrapair fertilization. Results suggest that female body mass affected the type of extrapair genetic benefits obtained. Heavy females obtained extrapair fertilizations when their social male was of low quality (as reflected by sexual display) and produced larger extrapair than within-pair chicks. Lean females obtained extrapair fertilizations when their social mate was genetically similar, thereby producing more heterozygous extrapair chicks. Our results suggest that mating patterns may be conditiondependent. Introduction In many socially monogamous bird species, males and females are known to copulate with multiple partners (Petrie & Kempenaers, 1998; Griffith et al., 2002). Males obviously gain fitness through such behaviour by increasing the number of their descendants, and are therefore expected to initiate extrapair copulations (EPC) (Westneat & Stewart, 2003). However, females also have control over fertilization (Andersson, 1994; Birkhead & Pizzari, 2002) and sometimes apparently seek EPC (Kempenaers et al., 1992; Lifjeld & Robertson, 1992; Wagner et al., 1996; Strohbach et al., 1998). This suggests that females may benefit from mating with multiple males. Because the existence of direct fitness benefits for females is equivocal despite extensive tests for such effects (Birkhead & Møller, 1992; but see: Gray, 1997), Correspondence: A. N. Dreiss, Department of Ecology and Evolution, University of Lausanne, Biology Building, CH-1015 Lausanne, Switzerland. Tel.: +41 (0) ; amelie.dreiss@unil.ch females are currently believed to gain indirect genetic benefits and to improve the quality of their offspring through EPC, thereby compensating for a poor-quality social mate (Griffith et al., 2002). First, females may gain additive genetic benefits (referred to as good genes ) if extrapair mates are of higher genetic quality than their social mates (Kempenaers et al., 1992; Hasselquist et al., 1996). Secondly, females may obtain non-additive genetic benefits (referred to as complementary genes) through extrapair fertilizations and avoid inbreeding depression (Blomqvist et al., 2002) or increase offspring heterozygosity at specific loci (Tregenza & Wedell, 2000). In this way, some studies have shown that offspring quality is improved through extrapair paternity (EPP) (Hasselquist et al., 1996; Suter et al., 2007), but others have failed to find any genetic benefits of extrapair fertilization (Charmantier et al., 2004; Augustin et al., 2007). Empirical data thus provide only partial support for genetic benefits (Griffith et al., 2002; Akçay & Roughgarden, 2007) and the function of EPC for females is still not well understood, leading Arnqvist & Kirkpatrick (2005) to conclude that females are unlikely to ª T H E A U T H O R S. J. E V O L. B I O L. 21 ( ) J O U R N A L C O M P I L A T I O N ª E U R O P E A N S O C I E T Y F O R E V O L U T I O N A R Y B I O L O G Y

219 Extrapair young and genetic benefits 1815 benefit from EPCs (but see Griffith, 2007). Here, we examined simultaneously both hypotheses of genetic benefits search for extrapair fertilizations by investigating whether extrapair fertilizations occur when females are paired to supposedly low-quality mates or to genetically similar mates, in a natural population of blue tits Cyanistes caeruleus. We also examined whether extrapair fertilizations depend on female phenotype and whether they lead to qualitative effects on chicks, measured as heterozygosity and body size. In the blue tit, EPC is common [30 50% of nests contain extrapair young (EPY); Kempenaers et al., 1997; Krokene et al., 1998) and at least partly under female control (Kempenaers et al., 1992, 1995). Female extrapair behaviour has been suggested to be based on male phenotypic criteria like song output (Kempenaers et al., 1997), plumage colour (Delhey et al., 2003) and genetic similarity between mates (Foerster et al., 2003), although some studies failed to find genetic benefits from EPC (Charmantier et al., 2004). To our knowledge, no study has tried to account for these parameters simultaneously yet. Here, we followed 90 nests (47 in 2002 and 43 in 2003) and analysed the presence of EPY within nests in relation to: (i) the two main male secondary sexual characters; (ii) within-pair genetic similarity and (iii) female phenotype, in a natural population reproducing in nest boxes. Because female phenotype may be related to male s (Andersson, 1994) and female s mate preference (Burley & Foster, 2006) and to territory quality (Matthysen, 1990), it could have an important role in extrapair behaviour. Phenotype was assessed through tarsus length and body mass, which may be important proxies of female quality, particularly in blue tits (Alatalo & Lundberg, 1986; Merilä & Fry, 1998). Male secondary sexual characters were estimated, because they should partly signal the good genes carried by particular males (Møller & Alatalo, 1999; Tomkins et al., 2004). During the females period of fertilization, long after territory establishment and social mate choice, males express two major secondary sexual characters: the dawn chorus (an elaborate and intense song display just before daybreak) and intense crown plumage colour. We predicted that, under the good genes hypothesis, cuckolded social males would display poor-quality dawn chorus and less conspicuous colours than males that were not cuckolded, and that EPY would be in better condition than within-pair young (WPY), but not more heterozygous. Under the genetic complementarity hypothesis, cuckolded social males were expected to be genetically more similar to their mates than males that were not cuckolded, and thus EPY to be more heterozygous and in better condition than WPY. Methods Fieldwork was carried out in in Parc Régional de la Forêt d Orient (Aube, France, N, 4 17 E) as part of a long-term study on tit reproduction. The study area includes 1000 nest boxes accurately located by Global Positioning System (GPS). The forest studied covered a total area of 500 ha, and was separated from other woods by a lake and cereal fields several kilometres wide. General methods, dawn song and plumage sample are described in Dreiss et al. (2006) and below. Nest boxes were visited every 2 4 days to record laying date of the first egg. Final clutch size was determined during the incubation period. After 12 days of incubation, the nests were visited every day to determine hatching date and brood size. Parents were nest-trapped 7 to 10 days after hatching. For all birds, we recorded body mass (to the nearest 0.25 g, using a Pesola balance; Pesola AG, Baar, Switzerland) and tarsus length (to the nearest 0.1 mm with a calliper), and we collected a small sample of blood for molecular analysis. We collected three to four feathers in the middle of the crown of adult males for later colour measurements in the laboratory. Neighbour density was estimated for each pair as the number of blue tit singers during recording of male dawn chorus. Male sexual display Male song was recorded at dawn during the female s fertile period (from 6 days before the first egg was laid until the day when the sixth egg was laid; Mace, 1987) for 86 males, and crown colour was measured on feathers collected from males during chick rearing for 76 males. Four dawn song variables and four crown colour variables were included in the analysis. The four dawn chorus variables estimated were: (i) strophe duration [i.e. duration of song units separated by a pause; mean (±SD) 1.48 ± 0.29 s], (ii) song rate (number of strophes per minute, in strophe bouts where pauses did not exceed 10 s; 0.24 ± 0.05), (iii) strophe diversity estimated as the number of different strophes divided by the number of strophe bouts (0.79 ± 0.21) and (iv) strophe bout length (mean number of strophes per strophe bout; 52.1 ± 23.9). Repeatability (r) of song traits (Lessells & Boag, 1987), estimated for 12 males recorded on two different morning sessions were respectively (ANOVAs): (i) F 11,12 = 10.00, R 2 = 0.90, P=0.0002, r = 0.86 ± 0.03; (ii) F 11,12 = 5.48, R 2 = 0.83, P=0.0033, r = 0.76 ± 0.05; (iii) F 11,12 = 6.92, R 2 = 0.87, P=0.0017, r = 0.81 ± 0.04; (iv) F 11,12 = 7.97, R 2 = 0.89, P=0.0009, r = 0.83 ± Four objective parameters of crown colour were calculated according to the method described by Endler (1990): (i) brightness (spectral intensity, R ; 5764 ± 2115) estimated as the sum of reflectance from 300 to 700 nm; (ii) hue (spectral location, k max : 389 ± 21) defined as the wavelength of maximum reflectance; (iii) UV-brightness (R ; 1781 ± 641) estimated as the sum of reflectance in the UV; and (iv) UV-chroma (spectral purity, R R ; ± 0.051). For each individual, we computed the mean of five reflectance spectra, each measured with two ª T H E A U T H O R S. J. E V O L. B I O L. 21 ( ) J O U R N A L C O M P I L A T I O N ª E U R O P E A N S O C I E T Y F O R E V O L U T I O N A R Y B I O L O G Y

220 1816 A. N. DREISS ET AL. superimposed feathers. Repeatability of colour traits given by the five spectra were respectively (ANOVAs): (i) F 82,362 = 36.58, R 2 = 0.89, P<0.0001, r = 0.88 ± 0.02; (ii) F 82,362 = 17.86, R 2 = 0.80, P<0.0001, r = 0.77 ± 0.03; (iii) F 82,362 = 26.69, R 2 = 0.86, P < , r = 0.83 ± 0.02; (iv) F 82,362 = 18.77, R 2 = 0.81, P < , r = 0.79 ± Feathers were collected during young feeding and not during mate choice, and colour may have slightly faded during the reproductive period (Örnborg et al., 2002). However, Griffith et al. (2003) obtained similar results when they measured the colour of blue tits before or during chick-feeding, suggesting that our measurements are likely to be meaningful and to reflect the within-male difference in plumage traits. One global principal component analysis (PCA) on correlation matrix was performed on all variables to describe male sexual display. The components retained were F1-global (explaining 30% of the variance) and F2-global (explaining 21% of the variance; Table 1). F1-global was mainly explained by crown colour variables and was positively related to crown brightness (total brightness and UV-brightness) and negatively related to UV-chroma. F2-global represented dawn chorus performance (strophe bout length and song rate) and crown brightness and UV-chroma (Table 1). UV-chroma and strophe bout length have both been found to predict brood sex ratio (Sheldon et al., 1999; Dreiss et al., 2006). Two other PCA (song and colour) were also performed to summarize information on each of the two categories of male secondary sexual character with few independent variables. The same four song and four colour variables were used for the analyses. The components retained were Song performance (F1-song) and Song diversity (F2-song) (explaining 38% and 27% of the variance, respectively) and Crown brightness (F1-colour; explaining 59% of the variance). Song performance (F1-song) was mainly explained by the variables strophe bout length, strophe duration and song rate, while Song diversity (F2-song) mainly represented strophe diversity. Table 1 Loadings of the variables of male sexual display on the two first principal components extracted from the global PCA, and cumulative variance associated with each. Variables F1-global F2-global Dawn song Strophe duration 0.01 )0.42 Song rate ) Strophe diversity ) Strophe bout length ) Crown colour Brightness Hue 0.52 )0.16 UV-brightness UV-chroma ) Eigenvalue Cumulative variance 30% 51% Table 2 Loadings of the variables of (a) the PCA on male dawn song, and (b) the PCA on crown colour, on the first principal components extracted, and cumulative variance associated with each. (a) Variables F1-song F2-song Strophe duration ) Song rate Strophe diversity ) Strophe bout length Eigenvalue Cumulative variance 38% 65% (b) Variables F1-colour Brightness 0.61 Hue 0.50 UV-brightness 0.52 UV-chroma )0.32 Eigenvalue 2.29 Cumulative variance 59% Crown brightness (F1-colour) was mainly explained by the variables brightness and UV-brightness (Table 2). In the analyses, we used the principal components with a cumulative variance exceeding 50%. Genetic analyses Molecular methods and paternity analyses are described in Dreiss et al. (2006). All offspring were used for the molecular analyses, including dead embryo. The five highly polymorphic microsatellite loci used [Dawson et al., 2000 and GenBank accession number AF041466] have a combined power of exclusion of 99% (Dreiss et al., 2006) (polymorphism in total number of alleles: Pk12: 24, Pca8: 60, Pca7: 19, Pca2: 15, Pca5: 26). We could not identify any extrapair fathers among the males sampled in the population (23% of the males reproducing in nest boxes i.e. producing eggs were sampled). Heterozygosity was estimated by standardized observed heterozygosity at microsatellite loci (Coltman et al., 1999). This measure is given by the proportion of heterozygous loci divided by mean heterozygosity of typed loci. We estimate genetic similarity between mates for 87 couples by using the Queller & Goodnight (1989) measure of relatedness, calculated by the computer program RELATEDNESS 5.0 (Keck Center for Computational Biology, Rice University, Houston, TX, USA; This estimate ranges from )1.0 to 1.0, in which negative values indicate that individuals share fewer identical alleles than the mean level in the population. In a randomly mating population, the genetic similarity is expected to be 0.5 on average for full siblings and 0.25 for half siblings, which was the case in our population. ª T H E A U T H O R S. J. E V O L. B I O L. 21 ( ) J O U R N A L C O M P I L A T I O N ª E U R O P E A N S O C I E T Y F O R E V O L U T I O N A R Y B I O L O G Y

221 Extrapair young and genetic benefits 1817 Statistical analyses We performed two generalized linear model analyses (procedure GENMOD; SAS Institute, Cary, NC, USA) to analyse factors affecting the probability of cuckoldry (presence vs. absence of EPY within clutches). In the first global analysis we examined the relative role of male sexual displays and pair genetic similarity: the independent variables were male sexual display (F1-global and F2-global of global PCA), female tarsus length and body mass (continuous variables), pair genetic similarity and year. In the second analysis, we investigated the relative role of male song and colour separately: the independent variables were male song display (F1-song and F2-song), crown colour (F1-colour) and year. We also performed parallel analyses of paternity with the proportion of EPY the as dependent variable: each chick was assigned a paternity status (extrapair or within pair) that we analysed as a binary dependent variable with a macro using a linear mixed model adapted for discrete variables (SAS macro GLIMMIX; SAS Institute), with nest and year set as random effects. Because this latter analysis gave the same results (same variables and interactions significant in the final model) as the analysis of probability of cuckoldry, we do not report these latter results. In order to understand the role of female body mass revealed in the global analysis, we performed complementary analyses. We divided our samples into three classes according to female body mass: low, medium and high, each containing one-third of the females (n = 28 per class). Paternity analyses were then performed for females of low, medium and high body mass separately. Offspring heterozygosity and size (tarsus length and body mass) in relation to their origin (WPY or EPY) were then analysed using linear mixed models (Procedure MIXED with origin and female body mass as independent variables and chick heterozygosity and size as dependent variables, with nest and year as random effects). For the analysis of chick size, we included chick age since hatching (in days) in the models. As we found an interaction between female body mass and chick origin, we analysed this interaction by performing separate tests for each of the three classes of female body mass. We performed backward model selection using P=0.05 as the threshold value for elimination. Final models only contained significant effects, and main effects involved in significant interactions (McCullagh & Nelder, 1989). The final models and the initial models (all explanatory variables and interactions) did not differ significantly in change of deviance, suggesting that no other variable improved the final model. Strophe bout length, proportion of extrapair young in the nests and individual heterozygosity differed significantly from normality (Kolmogorov Smirnov tests). Strophe bout length was normalized as )log(1 x) for PCA. We used the tests of Pearson or Kendall (the latter for non-normal variables) to analyse the correlations between variables. We analysed correlations between male heterozygosity, dawn chorus, crown colour and biometrics. Heterozygosity was not significantly correlated with biometrics and laying date in males (tarsus: tau-b = )0.07, P = 0.50, n = 88; body mass: tau-b = )0.0063, P=0.56, n = 86) or females (tarsus: tau-b = 0.02, P = 0.83, n = 82; body mass: tau-b = 0.13, P=0.26, n = 80). Furthermore, laying date was not significantly correlated with any trait of individual phenotype [female: body mass: r = )0.07, P=0.50; tarsus length: r = )0.07, P=0.48; male: song performance (F1-song): r = )0.06, P = 0.54; song diversity (F2-song): r = 0.10, P = 0.29; crown brightness (F1-colour): r = 0.10, P = 0.34], nor was neighbour density [female: body mass: r = )0.05, P = 0.63; tarsus length: r = )0.01, P = 0.89; male: song performance (F1- song): r = )0.01, P = 0.92; song diversity (F2-song): r = 0.08, P = 0.46; crown brightness (F1-colour): r = 0.13, P = 0.26]. Crown colour variables were not significantly correlated with dawn chorus variables (all r < 0.2, P>0.1). No individual was present in both years. A few missing observations for some of the birds explain slight variation in sample sizes among tests. Trait values are reported as mean ± SD. Statistical analyses were performed using SAS Institute Inc (1999). Results and discussion Effect of male display and pair genetic similarity on EPP We found that 49% of the 90 nests contained EPY, in a proportion of 0.31 ± The presence of EPY in the nest was explained by two interaction terms (Table 3): (i) the interaction between male secondary sexual traits (F2-global) and female body mass (Fig. 1) and (ii) the interaction between pair genetic similarity and female body mass (Fig. 2). As expected from the good genes hypothesis, the occurrence of EPY was higher in nests of low-quality Table 3 Analysis of the probability of extrapair fertilization (presence vs. absence of extrapair young in clutch; df = 57). Variables Estimate SE v 2 P Parent genetic similarity (GS) Female body mass (FBM) ) Male sexual display (F2-global) FBM GS ) FBM F2-global ) Starting model contained male secondary sexual characters (summarized by the F1-global and F2-global of the global PCA on all parameters of male sexual display), female body mass and tarsus length, pair genetic similarity and year, as well as all possible twoway interactions as explanatory variables. Only significant or required effects are shown. ª T H E A U T H O R S. J. E V O L. B I O L. 21 ( ) J O U R N A L C O M P I L A T I O N ª E U R O P E A N S O C I E T Y F O R E V O L U T I O N A R Y B I O L O G Y

222 1818 A. N. DREISS ET AL. Fig. 1 Probability of occurrence of extrapair fertilization in female blue tits as a function of female body mass and male sexual displays (F2-global) (predicted values). Heavy females (dark grey) had a higher probability of producing EPY when mated to males with less conspicuous display (df = 17, v 2 = 7.84, P=0.0051, n = 19), while leaner females (white and light grey) did not (df = 50, v 2 = 0.01, P=0.94, n = 52). The interaction between female body mass and male sexual display was significant (df = 1, 57, v 2 = 6.33, P=0.012; see Table 3). males, as revealed by their sexual display (Fig. 1, Table 3). Males with low F2-global (low crown brightness, low UV-chroma and low song performance) suffered more frequently from cuckoldry than males with high F2-global (high crown brightness, high UV-chroma and high song performance, Fig. 1). The significant interaction between female body mass and F2-global, however, showed that this relation varied among females: only heavy females had a higher probability of producing EPY when mated with lower quality males (df = 17, v 2 = 7.84, P=0.0051, n = 19; dark grey area in Fig. 1). This relation was not found in medium-sized or lean females (df = 21, v 2 = 0.95, P=0.33, n = 23; white or light grey area in Fig. 1). As expected under the hypothesis of genetic complementarity, the presence of EPY in nests depended on genetic similarity between members of social pairs (Fig. 2, Table 3). However, this result differed depending on female body mass, as indicated by the significant interaction between female body mass and pair genetic similarity: only females in poor body condition had a higher percentage of EPY when mated with genetically similar males (df = 26, v 2 = 7.30, P=0.007, n = 28; light grey area in Fig. 2), while this relationship was not found in heavy females (df = 25, v 2 = 0.73, P=0.34, n = 27; Fig. 2 Probability of occurrence of extrapair fertilization in female blue tits as a function of female body mass and pair genetic similarity (predicted values). Lean females (light grey) had a higher probability of producing EPY when mated with genetically similar males (df = 26, v 2 = 7.30, P=0.007, n = 28), while heavier females (white and dark grey) did not (df = 58, v 2 = 0.77, P=0.38, n = 60). The interaction between female body mass and pair genetic similarity was significant (df = 1, 57, v 2 = 12.08, P=0.0005; see Table 3). dark grey area in Fig. 2). As in Foerster et al. s (2003) population, the degree of genetic similarity between pair members did not differ significantly from that of all other possible combinations (t-tests: 2002: t 831 = 1.66, P= 0.10, n = 47; 2003: t 800 = )0.02, P=0.98, n = 41; social pairs genetic similarity: 2002: ± 0.160; 2003: )0.020 ± 0.149; possible pairs genetic similarity: 2002: )0.010 ± 0.147; 2003: )0.019 ± 0.143). It is likely that extrapair males originated from within the study area because there was no other suitable habitat around. Contrary to the population of the Viennese Forest (Foerster et al., 2003), geographic and genetic distances between individuals were not correlated in our population (r = 0.01, n = 3 965, P=0.65), suggesting that geographic distance cannot reveal genetic similarity. This difference in genetic structure between populations may be due to higher immigration or mortality rates and higher turnover of breeders in our area. Indeed, only 12% of the breeders that we captured in 2003 were ringed as adult or nestling in This is much lower than the usual recapture rate reported for other blue tit populations, in particular in the Viennese Forest (around 50%, Foerster et al., 2006), although our capture efficiency was relatively high (58% of the breeders and 81% of the juveniles were captured in 2002, 77% of the breeders in 2003). ª T H E A U T H O R S. J. E V O L. B I O L. 21 ( ) J O U R N A L C O M P I L A T I O N ª E U R O P E A N S O C I E T Y F O R E V O L U T I O N A R Y B I O L O G Y