Volume 114, Issue 1 pp. 82-91
Research Article
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Population differences in the structure and coloration of great tit contour feathers

Anna Gamero

Anna Gamero

Department of Biology, University of Oulu, FIN-90014 Oulu, Finland

Department of Sociobiology/Anthropology, University of Göttingen, D-37077 Göttingen, Germany

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Juan C. Senar

Juan C. Senar

Unitat Associada d'Ecologia Evolutiva i de la Conducta, CSIC, Museu de Ciències Naturals de Barcelona, 08003 Barcelona, Spain

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Esa Hohtola

Esa Hohtola

Department of Biology, University of Oulu, FIN-90014 Oulu, Finland

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Jan-Åke Nilsson

Jan-Åke Nilsson

Department of Ecology, Animal Ecology, University of Lund, S-22362 Lund, Sweden

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Juli Broggi

Corresponding Author

Juli Broggi

Estación Biológica Doñana, CSIC, 41092 Sevilla, Spain

Corresponding author. E-mail: [email protected]Search for more papers by this author
First published: 24 October 2014
Citations: 6

Abstract

Contour feathers cover most of the avian body and play critical roles in insulation, social communication, aerodynamics, and water repellency. Feather production is costly and the development of the optimum characteristics for each function may be constrained by limited resources or time, and possibly also lead to trade-offs among the different characteristics. Populations exposed to different environmental conditions may face different selective pressures, resulting in differences in feather structure and coloration, particularly in species with large geographical distributions. Three resident populations of great tit Parus major L. from different latitudes differed in feather structure and coloration. Individuals from the central population exhibited less dense and longer contour feathers, with a higher proportion of plumulaceous barbs than either northern or southern birds, which did not differ in their feather structure. Ultraviolet reflectance and brightness of the yellow of the contour feathers of the breast was higher for the southern than for the northern population. Birds with greener plumage (higher hue) had less dense but longer feathers, independently of the population of origin. Differences in feather structure across populations appear to be unrelated to the contour feather colour characteristics except for hue. Nutritional and time constraints during molt might explain the pattern of feather structure, whereas varying sexual selection pressure might underlie the coloration patterns observed. Our results suggest that different selective pressures or constraints shape contour feather traits in populations exposed to varying environmental conditions. © 2014 The Linnean Society of London, Biological Journal of the Linnean Society, 2014, 114, 82–91.

Introduction

Contour feathers, which cover most of the avian body, provide aerodynamic shape, insulation, and surface for visual signals. Plumage is a crucial insulative layer that helps birds in maintaining water and temperature homeostasis (Stettenheim, 2000). Within species, variation in the total contour feather mass has been found both within and among populations as a consequence of a seasonal acclimatization process, presumably related to changes in thermal insulation (Swanson, 1991; Saarela, Klapper & Heldmaier, 1995). Furthermore, populations experiencing varying winter conditions have been found to differ in their thermal conductance and metabolic adjustments (Dawson et al., 1983; Swanson, 1993; Broggi et al., 2004). Contour feather structure is a plastic trait, which varies according to the environmental, nutritional and physiological conditions experienced during molt (Broggi et al., 2011; Vágási et al., 2012). However, although feather structure appears to play an important role in thermal insulation (Middleton, 1986), population variation in contour feather structure and thermal conductance remains unclear; but see also Wolf & Walsberg (2000).

Birds strongly rely on visual traits for social communication and plumage is the main trait involved in such information exchange (Savalli, 1995; Hill & McGraw, 2006). Plumage coloration results from the deposition of pigments in feathers (melanins, carotenoids, and porphyrins) and differences in feather microstructure, as well as a combination of both. Differences in plumage coloration have been intensively studied with respect to individual quality (Hill & McGraw, 2006). In particular, carotenoid-based coloration has been studied as a condition-dependent signal. Because carotenoids cannot be synthesized de novo by animals and need to be acquired (Fox, 1976), individuals may be constrained by limited access to such compounds (Olson & Owens, 1998). Carotenoids also play a role as antioxidants and immune-modulators, and individuals balance their physiological use with the signalling properties, making carotenoids good candidates as honest signals of individual quality (Pérez-Rodríguez, 2009). Besides pigments, plumage coloration can arise as a consequence of changes in feather microstructure (structural coloration) producing blue, green, purple and iridescent coloration (Finger, Burkhardt & Dyck, 1992; Prum, 2006). The final appearance of plumage coloration often results from the interaction between pigmented and structural colours (Shawkey & Hill, 2005; D'Alba et al., 2014), as well as other factors such as the shape of the feathers (Badyaev & Landeen, 2007).

Besides serving a signalling function, the development of colourful feathers can have a physical influence on feather microstructure. For example, deposition of melanin can directly affect the physical properties of the feather by improving resistance to abrasion (Burtt, 1986; Bonser, 1995; Roulin et al., 2013) and decrease bacterial and lice-chewing degradation (Kose & Møller, 1999; Gunderson et al., 2008; Burtt, 2009); but see also Grande, Negro & Torres (2004). Recent studies also suggest that populations may adaptively increase feather melanization when exposed to unfavourable conditions for the plumage (Peele et al., 2009). Furthermore, structurally-based coloration such as in iridescent feathers is known to impair plumage hydrophobicity (Eliason & Shawkey, 2011). Therefore, understanding microstructure variation in colourful contour feathers requires the consideration of the different kinds of pigments and structural coloration involved.

Feather development costs may arise from different selective pressures derived from varying ecological, social or physiological circumstances. Honest advertisement models posit that sexually-selected traits are costly to produce, maintain or bear, with brightly coloured feathers being classic examples of such traits. The cost of pigmented feathers is often ascribed to the value of the pigment itself, whereas the physiological cost of producing the pigmented feather and the survival implications of the general appearance of the plumage (e.g. increased predation risk) should also be considered as important costs (Hill & McGraw, 2006).

Plumage is replaced by periodic molts as it wears and deteriorates over time. Environmental and physiological conditions during feather growth are known to affect feather quality (Strochlic & Romero, 2008; Butler, Leppert & Dufty Jr, 2010; Moreno-Rueda, 2010; Pap et al., 2013). Furthermore, molting is energetically costly (Hoye & Buttemer, 2011) and molt speed is known to adversely affect feather structure (Vágási et al., 2012) and the expression of certain plumage ornaments (Vágási, Pap & Barta, 2010). Feather production is a demanding process in terms of time and resources, and molting individuals may be exposed to trade-offs with other costly activities such as reproduction (Bensch et al., 1985; Siikamäki, Hovi & Rätti, 1994), migration (de la Hera, Pérez-Tris & Tellería, 2009) or molting speed (Dawson et al., 2000). Indeed, few bird species do overlap breeding and molting on a regular basis, particularly in seasonal environments (Dawson, 2008). Thus, the final characteristics of feathers may depend on the balance between the available energy, the requirements for plumage development (Butler, Rohwer & Speidel, 2008) and the different functions that feathers serve. Additionally, as individuals are exposed to different environmental and feeding conditions across their geographical range, selective pressures and/or constraints upon different functions of the birds' plumage may change accordingly.

The great tit Parus major L. is a resident passerine distributed across Eurasia, with populations subjected to very different ecological conditions such as seasonality and food availability (Sanz, 1998). This has led to maladaptive life-history strategies at the borders of their distribution (Rytkönen & Orell, 2001), where great tits are often confronted with time and nutritional constraints affecting molting phenology and speed (Nilsson & Svensson, 1996). Previous studies have shown that great tits from different populations differ in their feather structure, and these differences are likely determined by nutritional constraints (Broggi et al., 2011). We studied population variation in contour feather structure and coloration (carotenoid-based and structural) among three wild European great tit populations located in the southern, middle, and northern portions of the species distribution range, which are exposed to very different environmental and ecological conditions, particularly during the nonbreeding season. We investigated the relationship between different contour feather traits across populations to find out whether feather traits vary in concert or independently, and in accordance with the different ecological/environmental circumstances encountered.

Material and Methods

We captured 61 wild great tits from three locations: 25 in Oulu, Finland (65°N, 25°30′E); 12 in Lund, Sweden (55°40′N, 13°25′E); and 24 in Barcelona, Spain (41°23′N, 2°9′E), hereafter referred to as the northern, central, and southern populations, respectively. Birds from the northern and central populations were sampled from January to March 2001 and birds from the southern population were sampled from February to March 2002. Oulu study area consists of mid-boreal forests with winters characterized by mean temperatures of approximately −8 °C, minimum day length of less than 4 h, and permanent snow cover. Lund study area consists of mixed forests of pine and deciduous trees, with mean winter temperatures of approximately 0 °C, minimum day length of 7 h, and nonpermanent snow cover. The southern study site in Barcelona consists of mixed forests of pine and oaks, winters with a mean temperature of approximately +8 °C, minimum day length of 9 h, and an absence of snow cover.

Birds were captured using baited funnel traps (Senar et al., 1997), and a few yellow contour feathers were plucked from an area on the right side of the breast, between the shoulder and the breast black stripe of each individual. All feathers were stored under equal conditions (i.e. dry and dark) for subsequent analyses in the laboratory. Feather structure analyses in the central and northern populations were undertaken in 2004, whereas the feather structure from the southern population and all colour measurements were undertaken in 2005 in the Natural History Museum facilities in Barcelona. Age (adult, N = 31, or yearling, N = 30) and sex (30 males and 31 females) were determined, sensu Jenni & Winkler (1994).

All procedures were approved by the ethical committee of the University of Oulu (097/04), Malmö/Lund Animal Care Committee (M126-00), and the Departament de Medi Ambient, Generalitat de Catalunya (2002).

Feather structure analysis

Two contour feathers per individual were analyzed with the help of a stereoscopic microscope with an ocular grid. Structurally, contour feathers are formed by a series of barbs attached on each side of a central rachis, with each barb supporting regular ramifications or barbules (Stettenheim, 2000). To describe contour feather structure, we measured six different variables that may explain differences in insulation capacity (Middleton, 1986): density of barbs and barbules from the plumulaceous and pennaceous portions of the feather, proportion of plumulaceous barbs; and the total vane length. Details on the measuring procedures of feather structure' variables are provided elsewhere (Broggi et al., 2011). All variables measured were significantly repeatable within an individual (all P < 0.001; repeatability between 0.33 and 0.71), as measured by means of a one-way analysis of variance with individual as grouping factor. For later analyses, mean values of the two measurements were used. All feather structure measurements were carried out by the same person (A.G.). Data on feather structure from Oulu and Lund wild birds correspond to the same birds as in Broggi et al. (2011). One bird from the Oulu population was excluded from the data set because the feather coloration could not be measured.

Plumage colour measurements

Coloration of yellow contour feathers from each individual was measured in the laboratory by superimposing all feathers on a black velvet surface (absolute reflectance 0%), replicating the plumage of the bird. This method is repeatable within individuals, and reliably reflects plumage coloration whenever the number of measured feathers are accounted for [details on the method are provided in Quesada & Senar (2006)]. The colour of the feathers was measured using the tri-stimulus approach by means of a spectrophotometer Minolta CM-2600d, which provides values of brightness, chroma, and hue on the visible scale and reflectance data from 360 to 700 nm (Quesada & Senar, 2006). Brightness corresponds to the physical light intensity on a scale from 0 (black) to 100 (white). Chroma (colour intensity) is positively correlated with colour purity on a scale of 0 for white to 100 for pure colour. Hue corresponds to the wavelength of the colour and it is expressed in degrees of a circle starting with red, continuing through yellow, green, blue, and back to red. In the case of great tits, hue values increase from an orange–yellow to a greenish yellow (Quesada & Senar, 2006). The algorithms to calculate the brightness, chroma and hue variables refer only to the 400–700 nm range and omit the ultraviolet (UV) region. Because great tit yellow plumage coloration also reflects in the UV (Quesada & Senar, 2006) and given that the maximum peak of absorbency of the fourth cone of vision in the UV range in the closely-related blue tit Cyanistes caeruleus L. is λ = 371 nm (Hart et al., 2000), we included reflectance at 370 nm as a measure of UV reflection (Prum, 2006). We measured all spectra in reference to a white standard (WS-1, Diffuse Reflectance Standard) (reflectivity over 98%). Dark reference measurements were taken as control for nonspecific activity of the sensor in the absence of light. We used the tri-stimulus methodology instead of alternative spectral visual models or principal component analysis (PCA) methods because this approach is the most appropriate to analyze data from incomplete spectra, without yielding substantial differences in the estimates (Evans et al., 2010).

Statistical analysis

All variables were normally distributed (Shapiro–Wilk test) and parametric statistics were applied. Feather structure was described by the first factor in a PCA including the six variables measured for feather structure. The rest of the factors had an eigenvalue lower than one.

Variation in feather structure was analyzed by linear models with sex, age, population of origin, and the respective interactions as fixed effects. Similarly, variation in each colour component (chroma, hue, brightness and UV) was analyzed by linear models with sex, age, population of origin and the respective interactions as fixed effects, and feather structure and the number of feathers used in the colour analyses as covariates. Residuals from all these models were normally distributed, and the colour variables were linearly related to the number of feathers measured as found in previous studies (Quesada & Senar, 2006). We tested the effect of the interactions for all models by comparing each model with a reduced model without the interactions by means of likelihood ratio tests. None of the interactions were significant (all P > 0.1) and were finally dropped from the final models. Only the results from final models are shown. All statistical tests were consucted using IBM SPSS, version 20 (IBM SPSS Statistics).

Results

Feather structure variables and colour components varied significantly among great tit populations (Tables 1, 2). General contour feather structure was studied by means of a PCA, with a first factor explaining 57.6% of the variance and an eigenvalue of 3.45. Densities of plumulaceous and pennaceous barbs (0.72 and 0.75, respectively), and plumulaceous and pennaceous barbules (0.76 and 0.72, respectively) were positively loaded in the first component of the PCA, whereas feather length (−0.86) and the proportion of plumulaceous barbs (−0.70) were negatively loaded. In summary, high positive values of feather structure correspond to short dense feathers with a low proportion of plumulaceous barbs.

Table 1. Mean ± SE of contour feather structure of three great tit populations for different sex and age classes
Southern Central Northern
Percentage of plumulaceous barbs (%)
Adult males 71.3 ± 0.67 (6) 73.0 ± 0.73 (6) 71.5 ± 1.15 (6)
Adult females 71.2 ± 0.80 (5) 74.3 ± 3.57 (4) 69.5 ± 1.85 (4)
Juvenile males 67.2 ± 1.45 (6) 72.0 (1) 72.0 ± 1.22 (5)
Juvenile females 69.3 ± 1.29 (7) 75.0 (1) 69.8 ± 0.55 (9)
Total 69.7 ± 0.64a 73.5 ± 1.16b 70.6 ± 0.53a
Density of pennaceous barbs (per 1 mm)
Adult males 1.41 ± 0.07 1.31 ± 0.04 1.56 ± 0.10
Adult females 1.42 ± 0.09 1.31 ± 0.14 1.68 ± 0.08
Juvenile males 1.61 ± 0.05 1.54 1.59 ± 0.12
Juvenile females 1.57 ± 0.03 1.24 1.60 ± 0.06
Total 1.51 ± 0.03a 1.32 ± 0.05b 1.60 ± 0.04a
Density of plumulaceous barbs (per 1 mm)
Adult males 3.20 ± 0.11 2.69 ± 0.11 3.27 ± 0.14
Adult females 3.16 ± 0.15 2.62 ± 0.19 3.21 ± 0.14
Juvenile males 3.39 ± 0.10 3.20 3.06 ± 1.16
Juvenile females 3.14 ± 0.08 3.68 3.01 ± 0.06
Total 3.22 ± 0.05a 2.71 ± 0.09b 3.12 ± 0.06a
Density of pennaceous barbules (per 0.1 mm)
Adult males 2.10 ± 0.07 1.88 ± 0.05 2.34 ± 0.08
Adult females 2.38 ± 0.09 1.89 ± 0.07 2.39 ± 0.02
Juvenile males 2.08 ± 0.05 2.04 2.31 ± 0.08
Juvenile females 2.20 ± 0.07 1.98 2.27 ± 0.06
Total 2.18 ± 0.04a 1.90 ± 0.04b 2.31 ± 0.03c
Density of plumulaceous barbules (per 0.1 mm)
Adult males 3.05 ± 0.07 2.59 ± 0.08 2.93 ± 0.11
Adult females 3.07 ± 0.08 2.38 ± 0.05 2.91 ± 0.05
Juvenile males 3.01 ± 0.06 2.91 2.81 ± 0.13
Juvenile females 3.01 ± 0.15 2.27 2.86 ± 0.06
Total 3.03 ± 0.05a 2.52 ± 0.07b 2.88 ± 0.04a
Feather length (mm)
Adult males 20.5 ± 0.95 24.4 ± 0.69 18.8 ± 0.84
Adult females 19.5 ± 1.05 25.1 ± 0.53 17.9 ± 0.52
Juvenile males 20.2 ± 0.62 21.8 19.9 ± 1.25
Juvenile females 18.9 ± 0.65 22.3 19.7 ± 0.75
Total 19.7 ± 0.40a 24.2 ± 0.48b 19.2 ± 0.44a
  • Feather structure data from the central and northern populations from Broggi et al. (2011). Numbers in brackets indicate sample sizes and different superscript letters represent statistically significant differences (P < 0.05) obtained from linear models with Tukey post-hoc tests for the feather structure variables.
Table 2. Mean ± SE for coloration of three great tit populations for different sex and age classes
Southern Central Northern
Chroma (%)
Adult males 22.1 ± 1.52 (6) 23.6 ± 1.59 (6) 25.9 ± 1.59 (6)
Adult females 19.1 ± 1.58 (5) 20.6 ± 1.71 (4) 22.8 ± 1.59 (4)
Juvenile males 21.2 ± 1.68 (6) 22.7 (1) 25.0 ± 1.42 (5)
Juvenile females 18.1 ± 1.59 (7) 19.7 (1) 21.9 ± 1.31 (9)
Total 20.1 ± 1.31a 21.7 ± 1.53a 23.9 ± 1.15a
Hue (°)
Adult males 94.1 ± 0.48 95.0 ± 0.50 94.3 ± 0.48
Adult females 93.8 ± 0.50 94.8 ± 0.54 94.0 ± 0.50
Juvenile males 94.1 ± 0.53 95.0 94.3 ± 0.45
Juvenile females 93.8 ± 0.50 94.8 94.0 ± 0.41
Total 94.0 ± 0.41a 94.9 ± 0.48a 94.1 ± 0.36a
Lightness (%)
Adult males 61.5 ± 1.43 58.2 ± 1.50 56.6 ± 1.43
Adult females 59.7 ± 1.49 56.4 ± 1.76 54.7 ± 1.23
Juvenile males 62.3 ± 1.58 59.0 57.4 ± 1.33
Juvenile females 59.7 ± 1.49 55.6 53.9 ± 1.49
Total 60.6 ± 1.23a 57.3 ± 1.43a,b 55.6 ± 1.08b
Ultraviolet (%)
Adult males 21.6 ± 1.04 18.1 ± 1.09 16.3 ± 1.04
Adult females 19.8 ± 1.08 16.3 ± 1.17 14.5 ± 1.08
Juvenile males 22.4 ± 1.15 18.9 17.1 ± 0.97
Juvenile females 20.6 ± 1.09 17.1 15.3 ± 0.90
Total 21.1 ± 0.90a 17.6 ± 1.04a,b 15.8 ± 0.78b
  • Feather structure data from the central and northern populations from Broggi et al. (2011). Predicted values for each colour component are derived from linear models standardized by the number of feathers used in the measurements. Numbers in brackets indicate sample sizes and different superscript letters represent statistically significant differences (P < 0.05) obtained from pairwise comparisons for feather coloration components.

Feather structure varied significantly across populations (Fig. 1, Table 3): both northern and southern birds differed from the middle range population by having short and dense feathers, with lower proportion of plumulaceous barbs (post-hoc Tukey's test, both P < 0.001; Table 1). Feathers from southernmost and northernmost birds did not differ from each other (post-hoc Tukey's test, P = 0.98; Fig. 1, Table 1). Neither age or sex, nor their interactions, had any effect on feather structure (Table 3). Feather structure correlated negatively with plumage hue, after correcting for the number of feathers used in measuring the colour, so that birds with a more greenish plumage (higher hue) had less dense but longer feathers (Fig. 2, Table 3). Chroma, brightness, and UV reflectance were not affected by feather structure (Table 3). Plumage brightness and UV reflectance were higher in the southern than in the northern population (pairwise comparison, P < 0.05; Fig. 3). Birds from the central population had intermediate values of brightness, not differing from the other two populations (pairwise comparison, both P > 0.05) but differing from the northern population in UV reflectance (pairwise comparison, P = 0.020). Chroma and hue did not differ among populations (Table 3). Males had higher values of chroma, brightness, and UV reflectance than females, whereas hue variation was independent of sex (Table 3).

figure

Mean ± SE of contour feather structure derived from the first factor of a principal component analysis (see text) for each great tit population.

Table 3. Results from the linear models explaining the variation in feather structure and in each colour component of great tit contour feathers that is accounted for by population of origin, sex and age
r2 d.f. β SE F P
Feather structure 0.54
Population 2,55 28.12 < 0.001
Sex 1,55 0.00 0.995
Age 1,55 0.09 0.772
Chroma 0.49
Population 2,53 1.66 0.201
Sex 1,53 6.23 0.016
Age 1,53 0.53 0.466
Number of feathers 1,53 1.38 0.27 26.02 < 0.001
Feather structure 1,53 1.05 0.90 1.36 0.249
Hue 0.48
Population 2,53 0.13 0.882
Sex 1,53 0.56 0.451
Age 1,53 0.01 0.994
Number of feathers 1,53 −0.28 0.83 11.28 < 0.001
Feather structure 1,53 −0.59 0.28 4.47 0.039
Brightness 0.65
Population 2,53 4.16 0.021
Sex 1,53 5.22 0.026
Age 1,53 0.37 0.547
Number of feathers 1,53 0.95 0.25 14.08 < 0.001
Feather structure 1,53 1.20 0.84 2.04 0.159
Ultraviolet 0.55
Population 2,53 7.49 0.001
Sex 1,53 4.64 0.036
Age 1,53 0.78 0.382
Number of feathers 1,53 0.27 0.19 2.08 0.155
Feather structure 1,53 0.31 0.62 0.25 0.619
  • For colour components, feather structure and number of feathers (to account for the variation induced by using different number of feathers for colour measurements) were also included as independent factors. Significant effects are shown in bold.
figure

Relationship between feather structure and hue of great tit contour feathers. Feather structure is derived from the first factor of a principal component analysis (see text) and hue is standardized by the number of feathers used in the measurements.

figure

Mean ± SE of each colour component of yellow contour feathers for each great tit population, standardized by the number of feathers used in the measurements. *P < 0.05. UV, ultraviolet.

Discussion

We found differences between great tit populations in contour feather structure and coloration. Feather structure did not change according to winter severity because the central population had significantly longer feathers with higher percentage of plumulaceous barbs than the two marginal populations. Considering that longer contour feathers with more plumulaceous barbs have lower thermal conductance, and better insulating properties than shorter feathers with a higher proportion of pennaceous barbs (Dove et al., 2007), our results suggest that thermal insulation does not drive countour feather differences among the populations studied. Furthermore, because great tits from southern and northern populations exhibited contour feathers with similar microstructure, both populations living at the distribution margins, and therefore exposed to suboptimal environmental conditions (Sanz, 1998), may be constrained in developing optimal feather structure.

Broggi et al. (2011) suggested that birds from the central population could be less constrained during feather molt, thereby developing higher quality feathers than those from northern regions. Our results suggest that southern populations could also be constrained during the molting period because they developed feathers of a structure similar to that of northern populations. Time constraints for molting in the southern population may arise from the higher prevalence of double brooding in great tit populations at low latitudes (Sanz, 1998), or the harshness of summer conditions (Hemborg, Sanz & Lundberg, 2001). Vágási et al. (2012) recently showed a causal link between molt speed and contour feather structure by experimentally increasing molt rate of caged house sparrows Passer domesticus L., which developed feathers with similar characteristics to the ones we found in the two marginal populations of great tits (short, dense feathers with low percentage of plumulaceous barbs). Molting late in the season, as observed in populations at higher latitudes (Holmgren, Jönsson & Wennerberg, 2001), is usually compensated for by accelerating molting rate (Dawson, 2004), which can in turn decrease feather quality (Dawson et al., 2000; de la Hera et al., 2009). Similarly, great tit breeding success (Sanz, 1998) and yolk carotenoid composition in pied flycatchers Ficedula hypoleuca P. (Eeva et al., 2011) present nonlinear latitudinal patterns similar to those we found for feather structure, which are claimed to result from time constraints (Sanz, 1998) and the mismatch between laying time and caterpillar availability (Rytkönen & Orell, 2001; Eeva et al., 2011). Thus, great tits from the northern and southern populations appear to grow suboptimal feathers, which may be related to constraints on the length and/or the access to nutrients during the molting period, compared to birds from the central population. Alternatively, birds from the southern population may be released from the selective pressure for high insulation capacity, and therefore grow an adequate plumage adapted to milder winter conditions.

Despite recent demographic studies suggesting that the northern population is a ‘sink’ (Karvonen et al., 2012), Broggi et al. (2005) showed that northern great tits locally adapt their winter metabolism. However, they appear to be unable to develop a highly insulative plumage structure in line with previous results showing higher thermoregulatory costs for great tits from the northern population (Broggi et al., 2004). These results suggest that selective pressure for an optimal feather structure is weak, or otherwise constrained by other more important traits (e.g. timing of breeding) (Eeva, Veistola & Lehikoinen, 2000; Rytkönen & Orell, 2001).

Variation in the pattern in feather coloration was mostly unrelated to structure, and only hue exhibited a significant relationship to feather structure. Independent of the population of origin, hue increased with the inferred quality of the contour feathers (negative values of feather structure; Fig. 2). Because carotenoid-based hue is related to the ability to acquire food (Senar, Figuerola & Pascual, 2002; Senar et al., 2008) and to general body condition (as inferred from ptilochronology) (Senar, Figuerola & Domènech, 2003), contour feather structure may be a reliable indicator of individual quality in all populations. Higher values of hue are also found in great tit populations inhabiting good quality habitats (Ferns & Hinsley, 2008), suggesting that poorer nutritional condition could constrain both signalling properties and the structural quality of feathers, thus giving no support for a trade-off between carotenoid-based coloration and the structure of great tit feathers.

In accordance with previous studies, we found that yellow contour feathers of great tits were sexually dichromatic, with males having higher values for chroma, brightness and UV (Ferns & Hinsley, 2008; Isaksson et al., 2008) but not hue. Population of origin did not explain the variation in hue or chroma, although we found a decrease in contour feather brightness and UV with increasing latitude. Thus, molt speed does not appear to affect contour feather brightness and UV, as it does with feather structure, in contrast to reports in other species (Serra et al., 2007; Griggio et al., 2009). Higher values of contour feather brightness and UV in the southern population could be the result of a stronger sexual selection pressure in this population, which may be related to higher population density (Irwin, 2000; Forsman & Mönkkönen, 2003) or higher parasite pressure at lower latitudes (Møller, 1998). However, it should be considered that inter-individual variation in plumage coloration is often considerable (i.e. as a result of sex, age or season) (Figuerola & Senar, 2005). Although we controlled for several of these potentially confounding factors, further studies including more populations at different latitudes would be required to properly interpret the latitudinal pattern found in the present study.

In summary, great tit contour feather structure and coloration differs among the studied populations. The different feather traits do not generally vary in concert, although some patterns of co-variation emerge. The results suggest that feather structure could result from constraints during molting among populations at the distribution margins, whereas coloration may depend on other factors, such as a latitudinal decrease on the strength of sexual selection. The present study also shows that, except for hue, other signalling aspects of carotenoid-based and structural coloration are independent of feather microstructure. Great tits from different populations prioritize the development of certain feather characteristics over others, although the different traits do not appear to interact with each other. Experimental manipulations of feather coloration and/or structure in captivity would be required to further study covariation patterns and possible constraints on the development of feather traits.

Acknowledgements

We thank the staff from the Oulu University Biological Research Facility, Kent Andersson, Javier Quesada, and Lluïsa Arroyo, for their help with field and laboratory work. Professor J. A. Allen, Dr E. H. Burtt Jr, Dr G. Moreno-Rueda, Dr L. Pérez-Rodríguez, and two anonymous referees greatly improved earlier versions of this manuscript. AG was funded by Volkswagen Stiftung doctoral fellowship I/84 849, JB was funded by JAE-doc and Juan de la Cierva postdoctoral programs, and JCS was funded by GCL2012-38262 research project from the Ministry of Science and Innovation, Spanish Research Council. The study was supported by the Thule Institute of the University of Oulu and the Swedish Research Council.

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