Do grooming behaviours affect visual properties of feathers in male domestic canaries, Serinus canaria?

Animal Behaviour 77 (2009) 1253–1260

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Do grooming behaviours affect visual properties of feathers in male domestic canaries, Serinus canaria? Philippe Lenouvel a, *, Doris Gomez b,1, Marc The´ry b,1, Michel Kreutzer a a b

Laboratoire d’Ethologie et Cognition Compare´es, EA 3456, Universite´ Paris 10 – Nanterre Muse´um National d’Histoire Naturelle, De´partement d’Ecologie et de Gestion de la Biodiversite´, CNRS UMR 7179

a r t i c l e i n f o Article history: Received 4 July 2008 Initial acceptance 4 September 2008 Final acceptance 16 February 2009 Published online 25 March 2009 MS. number: 08-00436R Keywords: domestic canary grooming behaviour physiological model plumage coloration Serinus canaria visual signal

Elaborate secondary sexual traits, such as plumage ornaments, are important signals in reproductive communication and so it is important to maintain them in good condition. Time and energy spent in their maintenance reinforce the honesty of the ornamental traits. Variation in plumage visual properties as a function of maintenance has until now received little attention. Here, we used a combination of spectroradiometric measurements of plumage coloration, a physiological model of bird vision and behavioural observations to investigate how grooming behaviours affect plumage coloration in experimentally soiled male domestic canaries. Although showing a similar total amount of grooming, dirty males showed more feather ruffling and less preening than control males, suggesting that removal of dirt does not require an increase in grooming activity and that ruffling is likely to be more efficient for removing dirt. Grooming activities were not correlated with changes in plumage reflectance, probably because the same grooming behaviour is more efficient at removing feather dirt when performed by some individuals than by others. Dirty males were distinguishable in coloration up to 2.5 h after soiling. Shoulders and throat were the dirtiest of all body parts and took males more time to clean. Taken together, these results suggest that females are able to assess visually the difference between potential partners differing in their soiling level. If grooming activity is costly, females could base their choice on the coloration of plumage areas more susceptible to soiling and difficult to clean. Ó 2009 The Association for the Study of Animal Behaviour. Published by Elsevier Ltd. All rights reserved.

Plumage coloration is a widely investigated example of a secondary sexual trait in male birds. Theory predicts that sexual selection should foster the evolution of a trait costly to maintain in terms of time, energy or predation risk. Better quality males are expected to assume this cost more easily: they should display more conspicuous plumage and should benefit from more opportunities to mate with a female. This is the case in the house finch, Carpodacus mexicanus, where males with a brighter plumage pair more quickly and more often than control males (e.g. Hill 1991). Bird plumage coloration is potentially affected by maintenance behaviours (Zampiga et al. 2004). Numerous bird species spend considerable time and energy grooming their plumage, showing

* Correspondence: P. Lenouvel, Laboratoire d’Ethologie et Cognition Compare´es, EA 3456, Universite´ Paris 10 – Nanterre, 200 avenue de la Re´publique, Baˆtiment BSL, 92000 Nanterre, France. E-mail address: [email protected] (P. Lenouvel). 1 D. Gomez and M. The´ry are at the Muse´um National d’Histoire Naturelle, De´partement d’Ecologie et de Gestion de la Biodiversite´, CNRS UMR 7179, 4 avenue du Petit Chaˆteau, 91800 Brunoy, France.

various behaviours such as ruffling, preening, bathing, scratching, dusting and sunning (Simmons 1964, 1985, 1986). Grooming is necessary to maintain the plumage in good condition by removing dirt and dust, for example. Passerine bird species either in captivity or in the wild spend approximately 9% of their daily time budget in maintenance activities, especially grooming, which is an important component of these activities (Cotgreave & Clayton 1994; P. Lenouvel, unpublished data). Time spent grooming cannot be invested in other essential activities such as foraging, predator avoidance or sleeping and thus may reinforce the potential honesty of ornamental plumage (Redpath 1988; Christe et al. 1996; Walther & Clayton 2005). If only good-quality males are able to invest a lot of time and energy in grooming activities, they should be preferred by females as predicted by the ‘attractive preening hypothesis’ (Griggio & Hoi 2006). Indeed, Zampiga et al. (2004) showed that female budgerigars, Melopsittacus undulatus, spent more time close to clean males than to soiled males, and that these males differed in coloration. We investigated the effect of feather grooming on the visual properties of male plumage by experimentally soiling plumage of

0003-3472/$38.00 Ó 2009 The Association for the Study of Animal Behaviour. Published by Elsevier Ltd. All rights reserved. doi:10.1016/j.anbehav.2009.02.007

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male domestic canaries. We carefully monitored bird grooming activity and objectively quantified feather coloration as perceived by birds. This allowed us to follow the kinetics of change in visual contrasts and to test whether interindividual variation in grooming is responsible for interindividual variation in plumage appearance. Our work clearly expands on previous studies which suffered from three main methodological limitations. First, studies on feather grooming have rarely objectively quantified the visual properties of the plumage. Only one study has quantified the effects of preening on plumage reflectance: Zampiga et al. (2004) showed that male budgerigars allowed to preen had a brighter plumage that reflected more ultraviolet (UV) than soiled males. The effect on UV is important given that birds, in contrast to humans, are sensitive to UV (Chen & Goldsmith 1986; Hart 2001). Second, previous studies overlooked the effect of visual background on plumage conspicuousness. Yet, female canaries spend more time in front of a male contrasting more against the visual background: as an example, a yellow male in front of a white background is preferred by females to a yellow male in front of a yellow background (Heindl & Winkler 2003a). However, these authors only tested birds over the range 400–700 nm, disregarding the UV known to influence mate choice (e.g. Bennett et al. 1996). This study underlines the importance of display conditions in reproductive communication and the need for a thorough method to take this aspect into account. Third, grooming studies have not attempted to reconstruct colours as perceived by birds. Signal detectability depends on the spectral properties of the signal, on the light conditions of communication, that is ambient light and visual background (Endler & The´ry 1996; Heindl & Winkler 2003b; Gomez & The´ry 2007), and on the receiver’s visual ability (Håstad et al. 2005). The use of a physiological model of bird colour perception allowed us to include all these aspects and to extract a colour (chromatic) contrast and a brightness (achromatic) contrast, two components essential for object perception and discrimination (Osorio et al. 1999; Schaefer et al. 2006). More specifically, we asked whether grooming can affect visual properties of previously soiled feathers. If so, does grooming affect (1) the whole plumage reflectance or some plumage parts specifically or (2) the whole light spectrum or a more particular part such as UV wavelengths, for example? In addition, by monitoring the changes in plumage reflectance, we could estimate the kinetics of the visual effect produced as seen by the bird. How long does it take males to restore a plumage reflectance comparable in appearance to the presoiling level? We expected males that groomed more frequently to restore their presoiling level of conspicuousness more quickly than males that groomed less frequently. We explored these questions with a method combining reflectance and irradiance spectrometry as well as visual modelling and behavioural observations. METHODS Subjects and Breeding Conditions We used adult male domestic canaries belonging to an outbred form of heterogeneous genetic background. Eighteen males and four females were kept in individual cages (40  24 cm and 30 cm high) with ad libitum access to seeds (mainly canary grass, Phalaris canariensis, and rapeseed, Brassica rapa), vegetables and water. Individuals selected for this experiment were kept in a short-day photoperiod (8:16 h light:dark) and switched to a long-day photoperiod (16:8 h) 2 weeks before the experiment.

This length of time was sufficient to stimulate their reproductive activity, for instance for females to be receptive and show nestbuilding activity (Bentley et al. 2000) and for males to have testosterone levels comparable to those during the breeding season (Nottebohm et al. 1987; Parisot et al. 2005). Males and females were maintained in the same room (room temperature 21  2  C) during the experiment. Females were placed in the room to stimulate males; they were provided with nest bowls (10 cm in diameter) and nest material (cotton string) to stimulate their reproductive activity. It was important to maintain birds in the same social context throughout the experiment since the presence of conspecifics may influence when and how birds groom (Simmons 1986; Walther & Clayton 2005 and references therein). Experimental Design The 18 males were divided into two groups: 12 experimental males (‘dirty males’) and six control males. We performed the six steps of the following experimental design daily on each male of these two groups. First, we measured the reflectance spectra of males’ feathers on six body parts: the head, the back, the shoulders, the tail, the throat and the chest. These measures of reflectance were named ‘Clean’ measures. Second, we manually put the same quantity of flour of organic black wheat (Treblec, Maure-de-Bretagne, France) on and under all the feathers of experimental but not of control males. Similar material was used for plumage soiling by Griggio & Hoi (2006): it is comparable to natural dust and adheres well to the plumage (removal was not instantaneous but was effective within a day, P. Lenouvel, personal observation). However, the potential visual effect produced (the direction and amplitude of any possible colour change) depends on the material used for soiling and might have been different with real dust and dirt. We measured the reflectance spectra of males’ feathers on the same body parts (‘Dirty 1’ measures). Third, 1.5 h after the application of the flour on the feathers, we observed the male’s grooming behaviours. Males were observed in a random sequence in their own cage for 1 h with water only for drinking but not for bathing. Bathing could potentially be very efficient in removing flour from plumage and then could minimize or hide the effects of preening, ruffling, scratching and beak rubbing on flour removal. Limiting access to water allowed us to reveal any potential effects of the other grooming activities on change in plumage coloration. The behaviour of each male was sampled 30 times for 10 s. For each behavioural sampling, we observed whether a male groomed its feathers and its beak. We scored the following grooming behaviours: preening (the bird takes a feather in its beak and preens it), ruffling (the bird shakes its entire plumage or just the posterior part of its body), scratching (the bird scratches a part of its body with its feet), and beak rubbing (the bird rubs its beak on perches, bars, feeding dishes or other objects present in its cage). Fourth, 2.5 h after flour application, we measured the reflectance spectra of males’ feathers on the same body parts (‘Dirty 2’ measures). Fifth, 4 h after flour application, we observed the male’s grooming behaviours again. Males were observed in a random sequence for 1 h in their own cage with water both for drinking and bathing. The behaviour of each male was again sampled 30 times for 10 s. For each behavioural sampling, we observed whether a male groomed its feathers and its beak and we scored the following grooming behaviours: preening, ruffling, scratching, beak rubbing and bathing (the bird goes into water and wets either the feathers of the throat or the feathers of the entire body). Sixth, 5 h after flour application, we measured the reflectance spectra of males’ feathers on the same body parts (‘Dirty 3’ measures).

P. Lenouvel et al. / Animal Behaviour 77 (2009) 1253–1260

For each of the four daily measures of reflectance spectra, males were measured in the same order, determined at random each day. The time interval between each of these four measures was the same for each male. Moreover, each bird was in the same treatment group on each day. The six steps of this method were performed on each male and on each day on 5 consecutive days. In total, the behaviour of each male was sampled 300 times [(30 samplings þ 30 samplings)  5 days] throughout the experiment.

Colour Measurements Reflectance spectra were measured at 45 of light incidence with a spectroradiometer (Avantes AvaSpec 2048 calibrated between 290 and 838 nm, Avantes BV, Eerbeek, The Netherlands), a FCR-7UV2002-45-ME reflectance probe, and a DH-2000 Deuterium Halogen light source emitting between 215 and 1500 nm, relative to a Spectralon white standard and to dark noise. The white reference and dark noise were taken before measuring each bird. We recorded for each male the reflectance of the following plumage parts: the head, the back, the shoulders, the tail, the throat and the chest. For each plumage part, measures of Clean, Dirty 1, 2 and 3 were obtained from an average of five reflectance spectra. We also measured the reflectance of the white visual background (five measures) of the experimental room and of green vegetation (30 leaves of 10 different plant species). We computed the mean white and green background as the average of the reflectance spectra taken in each case. The irradiance spectrum of the experimental room (fluorescent UV tube Sylvania Activa F 36 W/172) was measured with the same spectrometer and a FC-UV600-2-ME optic fibre connected to a CC3 cosine-corrected sensor. Irradiance was calibrated in mmol/m2 per s using an Avalight-DH-Cal Deuterium-Halogen light source. This spectrum was typical of white light and extended down to the UV range. Irradiance used with the green vegetation background was the standard illuminant D65 (CIE, see the shape of this spectrum in Vorobyev et al. 1998). To take canary visual sensitivity into account, we used the discriminability model of Vorobyev & Osorio (1998) which computes the colour distance DS between two colour signals as perceived by the canary’s eye:



DS2 ¼ ðe1 e2 Þ2 ðDf4  Df3 Þ2 þðe1 e3 Þ2 ðDf4  Df2 Þ2 þ ðe1 e4 Þ2 ðDf2  Df3 Þ2 þðe2 e3 Þ2 ðDf4  Df1 Þ2

 þ ðe2 e4 Þ2 ðDf3  Df1 Þ2 þðe3 e4 Þ2 ðDf2  Df1 Þ2  . ðe1 e2 e3 Þ2 þðe1 e2 e4 Þ2 þðe1 e3 e4 Þ2 þðe2 e3 e4 Þ2

ð1Þ

Canaries probably have tetrachromatic colour vision based on four single-cone types (Das et al. 1999). Dfi is the difference in response for the cone type i between colour signals A and B characterized by their reflectance spectra RA ðlÞ and RB ðlÞ. We can estimate the visual contrast of a colour patch against a visual background or between two different colour patches.

Z700 Q Dfi ¼ log iA ¼ log300 QiB Z700

RA ðlÞ  IðlÞ  Si ðlÞ dl (2) RB ðlÞ  IðlÞ  Si ðlÞ dl

300

IðlÞ is the irradiance spectrum of the ambient light and Si ðlÞ is the spectral sensitivity of the cone class i. We considered the noise of

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cone class i, ei , to depend on neural and quantum noise, an improvement of the model further proposed by Osorio et al. (2004). We chose a Weber fraction u of 0.05; hi , describing the relative density of the cone classes on the retina, was set to 1:1.92:2.68:2.7, values commonly used for passerine vision (Håstad et al. 2005).

ei ¼

qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi 2=ðQiA þ QiB Þ þ u2 =hi

(3)

Not only chromatic cues but also achromatic cues are important in avian vision, as shown for example in food detection by Schaefer et al. (2006). We computed the achromatic contrast (DQ) between the colours A and B, as in Siddiqi et al. (2004):

    Z700     l l l l R ð ÞIð ÞS ð Þd Q A ,       DfQ   Q    Q A 300   DQ e¼ log ¼ log  e  700   QQ B e Z     l l l l R ð ÞIð ÞS ð Þd B Q    

(4)

300

SQ ðlÞ was the spectral sensitivity function of double cones and e described the neural noise associated with double cones (see equation 3). For double cones, we took 1 for the relative density of the double cones on the retina. We built the sensitivity functions for canary cone spectral sensitivity by using visual pigment spectrometric characteristics (Das et al. 1999), visual pigment templates (Govardovskii et al. 2000), oil droplet characteristics and templates (Hart & Vorobyev 2005) and the ocular media transmission spectrum. This latter information was not available for the canary, so, as suggested by Hart & Vorobyev (2005), we took that of the starling, Sturnus vulgaris (Hart et al. 1998), a species with a spectral sensitivity highly similar to that of the domestic canary. All spectral data analyses were conducted using Avicol (available on request from D.G.; Doutrelant et al. 2008). The visual contrast was expressed in just noticeable differences (jnds). A value of 1 jnd is commonly taken as a relevant discrimination threshold (e.g. Schaefer et al. 2006), below which two colours cannot be distinguished because cone response does not exceed the noise of the visual system (Vorobyev et al. 1998). Increasing values of contrast could be interpreted as an increasing facility to detect a difference between any two colour signals. We first examined the visual contrast of a bird against the background by computing the contrast between (1) a plumage patch and the laboratory white background seen in the fluorescent tube light, hereafter referred to as laboratory visual environment, and (2) a plumage patch and a natural green foliage background seen in the D65 daylight (CIE), hereafter referred to as natural visual environment. We then examined the kinetics of changes in plumage reflectance and computed the difference, as seen by the bird, between two plumage patches, hereafter referred to as ‘comparing patches two by two’, from the same male (3) seen in the laboratory light or (4) in the D65 daylight illumination. For instance, the difference between Dirty 1 and Dirty 2 represented the difference in appearance between these two signals if they could be assessed simultaneously by a female. We could thus estimate whether they appeared different to the female’s eye and how different they appeared.

Statistical Analysis As our data were normally distributed, we used parametric statistics for data analysis (Sokal & Rohlf 1995) computed with SPSS

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11.5 for Windows (SPSS Inc., Chicago, IL, U.S.A.). When a normality test failed even after transformation, we used nonparametric statistics (Siegel & Castellan 1988). To analyse grooming behaviours we performed (1) paired t tests to examine whether the total number of grooming behaviours differed between the two sessions of behavioural observations, (2) one-way ANOVA for repeated measures (RM ANOVA) to examine whether males’ total number of grooming behaviours varied over the experiment, (3) t tests to compare the different kinds of grooming behaviours between dirty and clean males, except for scratching and bathing. In these last two cases, we used a MannWhitney rank sum test. To test interrelations between the different kinds of grooming behaviours, we performed Spearman correlations corrected for multiple testing using Bonferroni corrections. We analysed feather reflectance using (1) paired t tests to compare colour and brightness contrasts between natural and laboratory visual environments, (2) paired t tests to compare colour and brightness contrasts (values in jnd) considering either daylight or fluorescent tube illumination and (3) one-sample t tests to test whether colour and brightness contrasts, according to the daylight or fluorescent tube illumination, were higher than 1 jnd. To compare colour and brightness contrasts (1) with the different kinds of grooming behaviours, we performed multiple linear regressions, and (2) with all grooming behaviours together, we performed linear regressions. We performed power analyses using G*power 3.0.10 software (Faul et al. 2007) following the method described in Cohen (1988). We considered power was high when it was at least equal to 0.8 (Cohen 1988). All tests were two tailed. Significance level was set at 0.05. Ethical Note Fifteen days after this experiment, all birds were put in aviaries on a short-day photoperiod (8:16 h). The black wheat flour is a bioorganic substance without any pesticide and as such is not expected to have detrimental effects on the birds’ welfare. Although this material adhered to the plumage during the experiment, the birds easily removed it within a few hours. Experimental authorization was given by the French Ministry of Agriculture and Fisheries. RESULTS Grooming Behaviours During the 5 days of the experiment, from a total of 300 behavioural observations per bird, we observed from 20 to 83 (X  SE ¼ 46:8  4:2) grooming behaviours per bird, which represent 15.6  1.4% of behaviours observed. These 15.6  1.4% of grooming behaviours were subdivided into five types of grooming behaviours for dirty and control males (Table 1). Total number of grooming behaviours observed was similar between the two periods of behavioural observations, namely without and with access to a bath (paired t test: dirty males: t11 ¼ 0.420, P ¼ 0.683; control males: t5 ¼ 2.384, P ¼ 0.063). The daily total number of grooming behaviours did not vary throughout the experiment for both dirty males (one-way RM ANOVA: F11,4 ¼ 0.546, P ¼ 0.702) and control males (F5,4 ¼ 0.758, P ¼ 0.565). We therefore pooled data for all days in the subsequent analysis. The total number of grooming behaviours did not vary between dirty males and control males. However, dirty males ruffled their plumage more than control males when observed without a bath. Control males preened more frequently than dirty males when observed without a bath. There was no significant difference in beak rubbing, scratching and bathing activities between dirty and control males (Table 2). The different

Table 1 Percentage of each type of grooming behaviour observed in dirty and control males (X  SD)

Preening Beak rubbing Ruffling Scratching Bathing

Dirty males

Control males

9.22.6 47.84.6 38.82.9 0.80.3 3.31.3

18.42.8 45.43.8 24.84.5 1.40.3 10.03.5

kinds of grooming behaviours were not interrelated for dirty males and control males (all Spearman correlations nonsignificant after Bonferroni correction for multiple testing). Feather Reflectance After flour application, plumage mean reflectance showed an overall increase and then decreased until the presoiling level (Fig. 1). For all body parts, colour contrast was significantly lower in a natural than a laboratory visual environment (all paired t tests: t < 7, all P < 0.001; Fig. 1). In contrast, brightness contrast was significantly higher in a natural than a laboratory visual environment (all paired-t tests: t > 35, all P < 0.001; Fig. 1). The impact of flour application on feathers on the visual contrast between the bird and the background depended on the visual conditions (ambient light and background reflectance). In a natural environment, flour application increased both colour and brightness contrasts (paired t tests: Clean versus Dirty 1: DS: t11 ¼ 3.2, P ¼ 0.008; DQ: t11 ¼ 16.2, P < 0.001; Table 3); these contrasts subsequently decreased over the day (paired t tests: Dirty 1 versus Dirty 3: DS: t11 ¼ 7.6, P < 0.001; DQ: t11 ¼ 27.5, P < 0.001; Table 3). In a laboratory environment, colour and brightness contrasts both decreased after flour application (paired t tests: Clean versus Dirty 1: DS: t11 ¼ 9.9, P < 0.001; DQ: t11 ¼ 16.4, P < 0.001; Table 3) and then increased over the day (paired t tests: Dirty 1 versus Dirty 3: DS: t11 ¼ 11.8, P < 0.001; DQ: t11 ¼ 31.1, P < 0.001; Table 3). When we compared patches two by two, the results showed identical patterns of significance with daylight and fluorescent tube illumination, although values of colour and brightness contrast were significantly greater with fluorescent tube illumination (paired t tests: DS: t11 < 8.7, P < 0.001; DQ: t11 < 10.4, P < 0.001 for all values). Consequently, we give below results for the more natural illumination. Control males (N ¼ 6) did not

Table 2 Comparison of numbers of each type of grooming behaviour observed in dirty and control males, with and without a bath Bath

Test statistic t16/U

P

Total grooming activity

Without With

1.312* 0.405*

0.208 0.691

Preening

Without With

2.933* 0.986*

0.010 0.339

Beak rubbing

Without With

0.936* 0.436*

0.363 0.668

Ruffling

Without With

2.798* 1.076*

0.013 0.298

Scratching

Without With

53.0y 69.0y

0.741 0.272

Bathing

With

66.0y

0.425

Statistically significant differences are shown in bold. * Pained t test. y Mann-Whitney rank sum test.

P. Lenouvel et al. / Animal Behaviour 77 (2009) 1253–1260

application, males had restored their initial plumage reflectance to the presoiling level, except for the mean value of colour contrast for shoulders (Clean versus Dirty 3: one-sample t tests: all DS and DQ < 1, all P > 0.05; except DS of shoulders: P < 0.001; Table 4). Finally, our results show that males did not significantly modify their plumage reflectance between 2.5 and 5 h after feather soiling (Dirty 2 vesus Dirty 3: one-sample t tests: DS and DQ < 1, P > 0.05 for all; Table 4).

100 90 Reflectance (%)

80 70 60 50 40 30

Grooming Behaviours and Feather Reflectance

20 10 0 300

1257

350

400

450

500

550

600

650

700

Wavelength (nm) Laboratory white background Dirty feathers t=0 Dirty feathers t=2.5 h

Dirty feathers t=5 h 'Clean' feathers Natural green background

Figure 1. Mean reflectance spectra  SE of the throat feathers of dirty males (N ¼ 12) at different times after soiling compared to the mean reflectance spectra of two types of visual background, ‘white’ and ‘green vegetation’.

show any detectable change in coloration throughout the daily measurement sequence (one-sample t tests: DS and DQ < 1, P > 0.05 for all pairs). In contrast, males’ dirty plumage (Dirty 1) could be detected as different from the clean plumage, as shown by colour contrasts for all males’ body parts (Clean versus Dirty 1: one-sample t tests: DS > 1, P < 0.02 for all; Table 4), and by brightness contrasts for shoulders, throat and head (Clean versus Dirty 1: one-sample t test: DQ > 1, P < 0.03; Table 4). Shoulders and throat were the dirtiest parts of males’ plumage both for colour and brightness contrasts. Two and a half hours after flour application, males’ plumage reflectance was significantly modified (Dirty 1 versus Dirty 3: one-sample t tests: DS > 1, P < 0.014 for all; DQ > 1, P < 0.002 for all; except for back, chest, tail and head: DQ < 1, P > 0.05 for all; Table 4). Five hours after flour

Most changes in feather reflectance occurred between Dirty 1 and Dirty 2 and none were seen between Dirty 2 and Dirty 3 Consequently, we tested the possible effects of grooming behaviours only on the former interval. Grooming activity was not correlated with the change in reflectance over this period considering all behaviours together (linear regressions: all models with DS and DQ, P > 0.05) or separately, regardless of the ambient light (multiple linear regressions: all models with DS and DQ, P > 0.05). Grooming activity was not correlated with plumage reflectance before soiling (Clean), considering all behaviours together (linear regressions: all models with DS and DQ, P > 0.05) or separately, regardless of the ambient light (multiple linear regressions: all models with DS and DQ, P > 0.05). However, all these models of regression show low statistical power, except for the brightness contrast of throat in a laboratory environment (0.86; see Appendix). DISCUSSION Our results show that male domestic canaries can remove most of the flour from their plumage 2.5 h after application. In addition, the absence of any detectable difference in coloration between clean feathers and feathers 5 h after application demonstrates that nearly all flour was removed by then. It took male canaries a substantial length of time to restore their original plumage reflectance. Although the knowledge of kinetics is important to estimate the potential impact of grooming on feather coloration, this parameter

Table 3 Variation in colour and brightness contrasts (X  SE) for each body part over the day, according to the type of visual environment, either natural or laboratory Body part

Visual environment

Contrast

Clean

Dirty 2

Dirty 3

Shoulders

Natural

DS DQ DS DQ

10.30.2 13.10.2 21.10.8 3.70.1

9.30.2 15.10.2 13.90.2 2.40.1

9.20.1 13.20.2 17.90.5 3.90.1

9.30.1 12.50.2 18.60.4 4.40.1

DS DQ DS DQ

10.70.3 14.30.2 14.70.6 3.40.1

11.50.3 15.50.1 12.50.1 2.40.1

10.70.3 14.40.2 14.10.5 3.30.2

10.70.3 14.10.3 14.20.5 3.60.2

DS DQ DS DQ

9.10.2 11.20.2 17.10.5 5.90.1

10.00.3 13.90.2 13.00.2 3.60.1

9.20.3 12.10.2 15.30.4 5.20.1

9.10.2 11.50.2 16.20.5 5.70.1

DS DQ DS DQ

9.30.2 13.80.2 16.40.5 3.60.2

10.30.3 15.10.1 12.90.2 2.60.1

9.50.2 13.90.2 15.00.4 3.60.1

9.30.2 13.20.2 15.80.3 4.20.1

DS DQ DS DQ

10.00.3 14.90.1 14.70.2 2.80.1

10.20.2 15.90.1 13.6 0.2 1.90.1

9.70.2 14.60.1 15.50.3 3.00.1

9.70.2 14.00.1 15.50.3 3.60.1

DS DQ DS DQ

10.20.3 14.40.2 15.00.7 3.20.1

11.10.4 15.80.2 12.60.3 2.00.1

10.60.4 14.80.2 13.60.4 2.90.1

10.30.3 14.10.2 14.00.5 3.50.2

Laboratory Back

Natural Laboratory

Throat

Natural Laboratory

Chest

Natural Laboratory

Tail

Natural Laboratory

Head

Natural Laboratory

Dirty 1

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P. Lenouvel et al. / Animal Behaviour 77 (2009) 1253–1260

Table 4 Mean values  SE of colour (DS) and brightness (DQ) contrasts (expressed in jnds, just noticeable differences) of males’ body parts (N ¼ 12) Body part

Contrast

Clean–Dirty 1

Clean–Dirty 2

Clean–Dirty 3

Dirty 1–Dirty 2

Dirty 2–Dirty 3

Shoulders

DS DQ

8.20.7* 1.30.1*

3.10.3* 0.30.0

2.30.3* 0.60.1

5.00.6* 1.50.1*

0.90.2 0.50.1

Back

DS DQ

3.10.6* 1.00.1

1.00.1 0.30.1

1.00.2 0.40.1

2.50.4* 0.90.1

0.60.1 0.30.1

Throat

DS DQ

5.50.4* 2.10.2*

2.20.3* 0.70.1

1.40.2 0.40.1

3.40.3* 1.50.1*

1.20.2 0.50.1

Chest

DS DQ

4.90.3* 1.00.1

1.70.3* 0.30.1

0.90.2 0.60.1

3.20.3* 1.00.1

1.10.2 0.50.1

Tail

DS DQ

1.70.2* 0.80.1

1.40.3 0.30.1

1.40.3 0.80.1

2.60.2* 1.10.1

0.60.2 0.50.1

Head

DS DQ

3.50.5* 1.10.1*

2.00.3* 0.30.1

1.30.3 0.30.1

1.60.2* 0.90.1

0.80.1 0.60.1

Each body part was compared in two different steps of the experiment, Clean, Dirty 1, Dirty 2 and Dirty 3, using daylight illumination. * Values statistically higher than l jnd.

had not been estimated in previous studies. Zampiga et al. (2004) noted that male budgerigars removed all dirt from their plumage by grooming but they ignored the precise kinetics of dirt removal since they measured males’ reflectance only 24 h after soiling. In our experiment, male domestic canaries spent an average of 15.6% of their time in grooming activities. This time is comparable to that found in other bird species, such as captive budgerigars (10–20%, Zampiga et al. 2004; Griggio & Hoi 2006) and other domestic bird species (15.75%; Walther & Clayton 2005) but higher than the time spent in grooming by passerine species in the wild (8.66%; Cotgreave & Clayton 1994; Walther & Clayton 2005), and is in accordance with the fact that captive birds spend twice as much time in grooming activities as wild birds (Walther & Clayton 2005). Birds’ plumage is continuously damaged through mechanical abrasion, ectoparasites, microbes, exposure to UV light or soiling. To compensate for this damage, birds have to groom their plumage regularly and lengthily. Dirty and control males differed in the type of grooming activities they performed. Compared to control males, dirty males showed significantly more ruffling activity and less preening activity. Ruffling involves a large part of the plumage whereas preening concerns a single or a few feathers. It is thus reasonable to assume that ruffling is a more efficient strategy for removing dirt when this dirt (here flour) covers a large part of the plumage. Conversely, dirty and control males did not differ in their bathing activity and most of the flour was removed without the birds having access to water for bathing. Moreover, dirty and control males did not differ in their scratching activity which did not occur very often. Control males preened more than dirty males. As in numerous bird species, this result suggests that control males invest a lot of time in preening (Cotgreave & Clayton 1994) which is usually done as a routine activity to order feathers (Campbell & Lack 1985). Preening usually goes together with feather re-/positioning, or application of uropygial gland secretions (Delhey et al. 2007). These types of grooming behaviour ensure that feathers can perform essential functions in flight and insulation (Stettenheim 2000). Moreover, preening activities allow birds to remove parasites and to modify plumage coloration (Clayton 1990; Zampiga et al. 2004). In fact, birds with more intact and colourful plumage are preferred by females (Zampiga et al. 2004). Thus, we hypothesize that birds that tend to ruffle more (and thus preen less) when their plumage is soiled are likely to get fewer of the benefits they would get from preening. Our results show that males’ grooming activity was not correlated with changes in colour and brightness contrasts of their plumage, either in a natural or an artificial illumination. The absence of a correlation could be for several reasons. (1) Control

and dirty males showed a similar total amount of grooming behaviours. Without changing their basal grooming activity level, dirty males removed a large amount of flour from their feathers. If females avoid males showing grooming activity (‘preening avoidance hypothesis’, Griggio & Hoi 2006), males may be selected to increase not their total amount of grooming behaviours but the efficiency of such behaviours. They do not need to increase their basal maintenance activity in terms of total number of grooming behaviours. This means that the same grooming behaviour probably has a different impact on feather appearance depending on the level of dirt present on the feathers. (2) With our methodology, we could not estimate the efficiency of one grooming behaviour (for instance ruffling) at removing flour for each male separately. However, based on points (1) and (2), we can speculate that, within dirty males, the same grooming behaviour may have a different effect on feather reflectance depending on the individual considered, some birds being more efficient than others at removing flour with the same grooming behaviour. Moreover, we cannot exclude the possibility that individuals differ for parameters that we have not quantified such as skin secretions and preen wax (from the uropygial gland) application. These components may have contributed to changing feather reflectance during dirt removal (reviewed in Delhey et al. 2007; Surmacki & Nowakowski 2007). However, as grooming activity was not correlated with changes in colour and brightness contrast of males’ plumage, we cannot exclude the hypothesis that plumage colour and brightness can change passively over time because the flour just comes off as a consequence of the birds’ normal activities. (3) We started observing males’ grooming behaviours 1.5 h after flour application and we may have missed the time window when birds differed most in their amount of grooming behaviours. However, given that feather coloration at 2.5 h after flour application was still significantly different from the presoiling level, it is reasonable to think that, if birds differed in the missed time window, they might have extended their differential grooming effort during the first hour of observation (between 1.5 and 2.5 h). (4) We might not find a significant difference between grooming behaviours and plumage reflectance because of the relatively small sample size of our two groups of males as revealed by low statistical power values. Feather soiling with flour significantly affected plumage reflectance in male canaries. It increased overall plumage reflectance, which encompassed the whole range of birds’ sensitivity, including the UV range, and did not affect specific ranges of wavelengths more strongly than others. The direction and spectral distribution of the change in reflectance depend strongly on the material used

P. Lenouvel et al. / Animal Behaviour 77 (2009) 1253–1260

for soiling, and they are likely to be different with real dirt instead of black flour. For instance, Zampiga et al. (2004) found that soiling plumage using sand and soil decreased plumage reflectance mostly in the UV range. On the other hand, feather soiling had a different impact on visual contrast depending on the visual environment considered. Values of colour contrast were always lower in a natural than in a laboratory visual environment. Conversely, values of brightness contrast were always higher in a natural than in a laboratory visual environment. Since both brightness and colour cues are important for object detection in birds (Schaefer et al. 2006), it is difficult to infer from these results whether birds are more conspicuous against the laboratory or the natural environment. Nevertheless, we underline the importance of taking into account the nature of the visual environment (background and source of illumination) when analysing visual signals, as shown by previous studies. Animal conspicuousness varies strongly according to the ambient light illumination (e.g. Endler & The´ry 1996; The´ry et al. 2008). For instance, wire-tailed manakins, Pipra filicauda, mainly display in the shade, which reduces their visibility to conspecifics but also reduces their risk of being detected by predators (Heindl & Winkler 2003b). Moreover, the nature of the visual background is also important, as shown by Heindl & Winkler (2003a) in the domestic canary. Female canaries spent more time in front of males displaying against a background that increased the visual contrast produced. When we compared patches two by two, flour application on feathers induced a stronger increase in colour contrast than in brightness contrast. Consequently, a clean male and a dirty male appeared easily distinguishable by their coloration, not only immediately after soiling (difference between Clean and Dirty 1) but also 2.5 h after soiling (difference between Clean and Dirty 2). Zampiga et al. (2004) showed that females spent more time in front of clean than dirty males but they could not determine whether females could visually assess the difference between their potential partners. Although we have not conducted female mate choice experiments, we can assert that females are able to detect visually the difference between clean and experimentally soiled males, even after a certain amount of time. Our results show that shoulders and throat were the dirtiest of all body parts and that males needed more time to clean them (Table 4). In our experiment, these plumage areas were most affected by flour application, may be because of their location on the bird’s body and/or because of their feather structure. As grooming activities represent an important part of time budgets, males in low general condition should invest more time in essential activities such as foraging or predation avoidance and then may be less likely to invest time in plumage grooming (Redpath 1988). In fact, great tits, Parus major, infested with ectoparasites spent less time sleeping and devoted more time to nest sanitation than noninfested great tits (Christe et al. 1996). From these characteristics, feather grooming can be considered as a condition-dependent signal (Zahavi 1975). If so, high- and low-quality males are expected to differ in their investment in this costly grooming activity and thus in their coloration, especially on plumage areas that may be more difficult to clean, such as throat or shoulders. The ‘attractive preening hypothesis’ states that females may use males’ preening activity as an indicator of quality because only high-quality males should be able to invest both time and energy in preening. However, there is no indication that females use grooming cues when choosing a mate: female budgerigars show preferences for males irrespective of the time males spent grooming in their presence (Zampiga et al. 2004; Griggio & Hoi 2006). But, female rock doves, Columbia livia, and female budgerigars prefer clean males to soiled or parasitized males (Clayton

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1990; Zampiga et al. 2004). In domestic canaries, we know that females are physiologically able to distinguish a clean male from a dirty male. So, female canaries could assess male coloration and prefer males displaying a clean plumage, especially on body areas difficult to clean. However, our results do not yet mean that such a result could be translated into a change in female mate preference. Further experiments are planned to investigate (1) the mechanisms (behavioural, physiological) involved in male plumage maintenance, (2) whether female canaries are really able to assess differences in coloration between a male that tends to preen and a male that tends to ruffle, and (3) which of these two kinds of male females prefer. Acknowledgments We thank Mathieu Amy, Dalila Bovet, Gisel Dias, Philippe Groue´, Franck Pe´ron and Julie Platel for their help during colour measurements as well as Giorgio Malacarne for stimulating discussions and useful suggestions about preening. We also thank Colette Desaleux and Philippe Groue´ for taking care of the birds. We are grateful to Thomas Bugnyar and two anonymous referees for their useful comments and suggestions that greatly improved the manuscript. This study was supported by Universite´ Paris X – Nanterre through EA 3456, and by the Centre National de la Recherche Scientifique and the Muse´um National d’Histoire Naturelle through UMR 7179. References Bennett, A. T. D., Cuthill, I. C., Partridge, J. C. & Maier, E. J. 1996. Ultraviolet vision and mate choice in zebra finches. Nature, 380, 433–435. Bentley, G. E., Wingfield, J. C., Morton, M. L. & Ball, G. F. 2000. Stimulatory effects on the reproductive axis in female songbirds by conspecific and heterospecific male song. Hormones and Behavior, 37, 179–189. Campbell, B. & Lack, E. 1985. A Dictionary of Birds. Vermillion, South Dakota: Buteo Books. Chen, D.-M. & Goldsmith, T. H. 1986. Four spectral classes of cone in the retinas of birds. Journal of Comparative Physiology, Series A, 159, 473–479. Christe, P., Richner, H. & Oppliger, A. 1996. Of great tits and fleas: sleep baby sleep. Animal Behaviour, 52, 1087–1092. Clayton, D. H. 1990. Mate choice in experimentally parasitized rock doves: lousy males lose. American Zoologist, 30, 251–262. Cohen, J. 1988. Statistical Power Analysis for the Behavioral Sciences, 2nd edn. Hillsdale, New Jersey: L. Erlbaum. Cotgreave, P. & Clayton, D. H. 1994. Comparative analysis of time spent grooming by birds in relation to parasite load. Behaviour, 131, 171–187. Das, D., Wilkie, S. E., Hunt, D. M. & Bowmaker, J. K. 1999. Visual pigments and oil droplets in the retina of a passerine bird, the canary Serinus canaria: microspectrophotometry and opsin sequences. Vision Research, 39, 2801–2815. Delhey, K., Peters, A. & Kempenaers, B. 2007. Cosmetic coloration in birds: occurrence, function, and evolution. American Naturalist, 169, S145–S158. Doutrelant, C., Gre´goire, A., Grnac, N., Gomez, D., Lambrechts, M. M. & Perret, P. 2008. Female coloration indicates female reproductive capacity in blue tits. Journal of Evolutionary Biology, 21, 226–233. Endler, J. A. & The´ry, M. 1996. Interacting effects of lek placement, display behavior, ambient light and color patterns in three neotropical forest-dwelling birds. American Naturalist, 148, 421–452. Faul, F., Erdfelder, E., Lang, A.-G. & Buchner, A. 2007. G*Power 3: a flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behavior Research Methods, 39, 175–191. Gomez, D. & The´ry, M. 2007. Simultaneous crypsis and conspicuousness in color patterns: comparative analysis of a Neotropical rainforest bird community. American Naturalist, 169, S42–S61. Govardovskii, V. I., Fyhrquist, N., Reuter, T., Kuzmin, D. G. & Donner, K. 2000. In search of the visual pigment template. Visual Neuroscience, 17, 509–528. Griggio, M. & Hoi, H. 2006. Is preening behaviour sexually selected? An experimental approach. Ethology, 112, 1145–1151. Hart, N. S. 2001. The visual ecology of avian photoreceptors. Progress in Retinal and Eye Research, 20, 675–703. Hart, N. S. & Vorobyev, M. 2005. Modelling oil droplet absorption spectra and spectral sensitivities of bird cone photoreceptors. Journal of Comparative Physiology, Series A, 191, 381–392. Hart, N. S., Partridge, J. C. & Cuthill, I. C. 1998. Visual pigments, oil droplets and cone photoreceptor distribution in the European starling (Sturnus vulgaris). Journal of Experimental Biology, 201, 1433–1446.

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APPENDIX Table A1 Relationships between grooming behaviours (considering each behaviour separately or all together) and feather reflectance of dirty males, in natural or laboratory environments, either after (Dirty 1–Dirty 2) or before (Clean) flour application, and corresponding power values Interval

Natural

Laboratory

DS R2

DQ P

DS

DQ

Power (1-b)

R2

P

Power (1-b)

R2

P

Power (1-b)

R2

P

Power (1-b)

Dirty 1–Dirty Shoulders Back Throat Chest Tail Head

2, separate behaviours 0.643 0.088 0.502 0.240 0.590 0.135 0.214 0.753 0.152 0.859 0.092 0.943

0.77 0.50 0.66 0.16 0.12 0.09

0.335 0.476 0.504 0.127 0.290 0.407

0.521 0.277 0.238 0.898 0.607 0.389

0.27 0.46 0.50 0.10 0.22 0.35

0.640 0.504 0.589 0.197 0.159 0.099

0.091 0.238 0.136 0.785 0.849 0.935

0.76 0.50 0.66 0.15 0.12 0.09

0.320 0.477 0.496 0.117 0.293 0.391

0.549 0.276 0.249 0.911 0.601 0.418

0.25 0.46 0.49 0.10 0.22 0.33

Dirty 1–Dirty Shoulders Back Throat Chest Tail Head

2, all behaviours 0.008 0.771 0.083 0.364 0.006 0.815 0.008 0.779 0.103 0.309 0.019 0.672

0.06 0.16 0.06 0.06 0.19 0.07

0.051 0.006 0.013 0.000 0.040 0.011

0.478 0.813 0.719 0.928 0.535 0.742

0.11 0.06 0.06 0.05 0.10 0.06

0.008 0.083 0.005 0.008 0.115 0.023

0.781 0.362 0.833 0.774 0.280 0.639

0.06 0.16 0.06 0.06 0.20 0.08

0.048 0.007 0.019 0.002 0.045 0.006

0.493 0.788 0.671 0.890 0.507 0.804

0.11 0.06 0.07 0.05 0.10 0.06

Clean, separate behaviours Shoulders 0.162 Back 0.221 Throat 0.488 Chest 0.130 Tail 0.089 Head 0.279

0.935 0.872 0.430 0.960 0.984 0.791

0.10 0.13 0.38 0.09 0.08 0.17

0.458 0.235 0.456 0.311 0.344 0.203

0.483 0.853 0.487 0.740 0.686 0.893

0.34 0.14 0.33 0.19 0.22 0.12

0.177 0.343 0.206 0.115 0.297 0.265

0.920 0.688 0.890 0.970 0.763 0.812

0.11 0.22 0.13 0.09 0.18 0.16

0.593 0.344 0.745 0.380 0.543 0.333

0.257 0.686 0.079 0.623 0.336 0.705

0.55 0.22 0.86 0.25 0.46 0.21

Clean, all behaviours Shoulders 0.005 Back 0.019 Throat 0.103 Chest 0.001 Tail 0.001 Head 0.001

0.816 0.609 0.310 0.917 0.935 0.975

0.06 0.07 0.19 0.05 0.05 0.05

0.086 0.001 0.003 0.004 0.009 0.005

0.353 0.984 0.862 0.833 0.769 0.813

0.16 0.05 0.05 0.05 0.06 0.05

0.003 0.002 0.090 0.040 0.131 0.001

0.956 0.898 0.343 0.508 0.248 0.980

0.05 0.05 0.17 0.10 0.23 0.05

0.158 0.001 0.026 0.001 0.017 0.026

0.201 0.927 0.612 0.937 0.685 0.613

0.27 0.05 0.08 0.05 0.07 0.08