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The developmental stress hypothesis offers a mechanism to maintain honesty of sexually selected ornaments, because only high quality individuals will be able to develop full ornamentation in the face of stress during early development. Experimental tests of this hypothesis have traditionally involved the manipulation of one aspect of the rearing conditions and an examination of effects on adult traits. Here, we instead use a statistically powerful quantitative genetic approach to detect condition dependence. We use animal models to estimate environmental correlations between a measure of early growth and adult traits. This way, we could make use of the sometimes dramatic differences in early growth of more than 800 individually cross-fostered birds and measure the effect on a total of 23 different traits after birds reached maturity. We find strong effects of environmental growth conditions on adult body size, body mass and fat deposition, moderate effects on beak colour in both sexes, but no effect on song and plumage characters. Rather surprisingly, there was no effect on male attractiveness, both measured in mate choice trials and under socially complex conditions in aviaries. There was a trend for a positive effect of good growth conditions on the success at fertilizing eggs in males breeding in aviaries whereas longevity was not affected in either sex. We conclude that zebra finches are remarkably resilient to food shortage during growth and can compensate for poor growth conditions without much apparent life-history trade-offs. Our results do not support the hypothesis that sexually selected traits show heightened condition dependence compared to nonsexually selected traits.
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Current models of sexual selection assume that ornamental traits should be costly to develop or maintain to serve as honest indicators of quality (Zahavi, 1975; Grafen, 1990; Getty, 2006). This has lead to the wide-held assumption that condition dependence is a common feature of sexual traits (e.g. Johnstone, 1995; Rowe & Houle, 1996). Quality indicators could signal either (1) genetic and/or (2) environmental quality variation among males (Iwasa & Pomiankowski, 1999; Cotton et al., 2004). Thus, the condition dependence of sexual traits might evolve to signal male genetic or environmental quality, or both, and females might benefit from choosing elaborated males either via good genes (if 1) or direct benefits (if 1 and/or 2). Because most traits will exhibit some degree of condition dependence, a convincing demonstration of condition dependence of sexual ornaments requires that the relative condition dependence of sexual traits are compared to that of naturally selected traits (Hamilton & Zuk, 1982; Zuk et al., 1990; Cotton et al., 2004).
Condition dependence could come about through developmental or maintenance costs of ornament elaboration. Environmental conditions during early development might be especially influential, because stress during this crucial period might have strong effects on the development of sexual ornaments, either because the traits are fixed during early ontogeny (like song learning in close-ended learners, Nowicki et al., 1998) or because early conditions have knock-on effects later on in life. Thus, if individuals that fared better in the face of early environmental stress have more elaborate ornaments, these ornaments can signal past condition. This was termed the developmental stress hypothesis by Nowicki et al. (1998).
From this outline, it becomes clear that the measurement and definition of condition is not a straightforward issue. Here, we will mainly focus on the effects of the early environment on the expression of secondary sexual traits in adulthood (i.e. the potential to signal past condition in the sense of the developmental stress hypothesis). However, we will also devote some attention to the genetic basis of condition dependence (the genic capture hypothesis, Rowe & Houle, 1996; Tomkins et al., 2004).
If ornaments reflect past condition, a female choosing a male with an elaborate ornament might receive more direct benefits or indirect benefits, or both. However, there also exists a line of evidence showing that individuals that grow up under poor conditions are often able to compensate for this when conditions improve (Metcalfe & Monaghan, 2001). To be adaptive, this compensatory growth should bring potential fitness benefits that outweigh the potential long-term costs (Metcalfe & Monaghan, 2001). For example, it might be beneficial to trade-off investment in favour of a sexual ornament if this leads to short-term fitness benefits (reproductive success) that outweigh long-term costs because of the reduced somatic maintenance (e.g. shortened life-span, Lindström et al., 2005). Therefore, more studies are needed that look at life-time effects of early condition, not only on subsequent growth and development of secondary sexual characters, but also on life-history consequences.
The ease with which environmental quality can be manipulated in the laboratory has lead to a surge of studies that have tested the developmental stress hypothesis in a range of taxa and found effects on sexual ornaments (e.g. David et al., 2000; Nowicki et al., 2002; Ohlsson et al., 2002; Scheuber et al., 2003). The zebra finch, Taeniopygia guttata, has become a model species to study the effects of developmental stress. Typically, two treatment groups are created by manipulating the early environment (e.g. brood size or food access or quality), and then traits of interest are compared between the two groups in adulthood (see Table 1). However, because of the ethical considerations, relatively mild treatments have been applied, such that, typically the mean mass at the age of 8 days was about 10–15% less in the food stress treatment than in the control group (e.g. Spencer et al., 2003; Arnold et al., 2007). Results, particularly those regarding sexually selected traits, have not always been consistent among studies (Table 1), and it might be argued that this is because the applied food restriction treatments might be ineffective under ad libitum food supply in the laboratory.
Table 1. Overview of zebra finch studies relating early growth conditions to the same adult traits that are investigated in the present study. When possible, effect sizes (r-values) are given. Effect sizes were either obtained directly or, in most cases, estimated from figures in the original publications. Significant effects are marked in bold and the direction of the effect is indicated with + and − (for studies where an estimation of effect sizes was not possible, the effect is indicated only with + and −, cases where the direction of the effect was not indicated in the original study is denoted by ?). To calculate effect sizes, we first calculated Cohen’s d and then transformed it to r as a standardized measure of the strength of the relationship. We calculated d based on means and standard deviations (σ) for the two treatment groups as: d = M1 − M2/σpooled, where (Cohen, 1988). We then used the following formula to convert d to r: r = d/√(d2 + 4) (Cooper et al., 2009).
|Trait||Direction and strength of effects|
|Mass||+|| ||+|| ||?||+0.24||+0.44||+0.45||+||+||+0.43||+0.54|
|Tarsus|| || ||+||+0.42|| ||+0.24||+0.57||+0.45||+||+0.37|| ||+0.55|
|Wing|| || ||+|| ||+0.66|| ||+0.47|| ||+||+0.58|| ||+0.30|
|Condition|| || ||+|| || || || ||+0.12|| || || ||+0.41|
|Beak colour|| || || || || ||?|| ||+0.33||−||+||−||+0.33|
|Attractiveness||+|| ||+|| || || || ||+||+|| || ||0.06|
|Song rate||?|| ||?|| || ||−0.32|| ||+0.32|| || ||−||+0.11|
|Syllable rate|| ||+0.4|| ||−|| || || || || || || ||−0.10|
|Repertoire size||+||?||?||+||?|| || || || || || ||+0.05|
|Motif duration||+0.24||–0.36||?||+||?|| || || || || || ||0.01|
|Longevity|| || || || || || || ||+|| || ||+||−0.03|
|Type of stress||Food access||Food access||Brood size||Brood size||Food access||Brood size||Food quality||Brood size||Food quality||Food quality||Food quality||Natural variation|
|Approximate duration||D 5–30||D 0–30||D 2–35||D 0–35||D 5–30||D 0–35||D 0–100||D 0–50||D 0–15||D 0–15||D 0–35||D 0–35|
|Study||Spencer et al. (2003, 2005)||Zann & Cash (2007)||Naguib et al. (2004); Gil et al. (2006); Naguib et al. (2008)||Holveck & Riebel (2007)||Brumm et al. (2009)*||Tschirren et al. (2009)†||Boag (1987)||de Kogel & Prijs (1996); de Kogel (1997)‡||Blount et al. (2003)||Arnold et al. (2007)§||Birkhead et al. (1999)¶||This study|
However, even under ad libitum food supply, a substantial number of nestlings actually experience very harsh rearing conditions, for instance because of their late hatching within a larger brood or because their parents are very poor provisioners. In our population, this variation in early growth is quite dramatic (Schielzeth et al., 2008), with offspring mass at day 8 varying between 1.9 and 12.2 g (7.5 ± 1.7, mean ± SD, N = 974). Although this enormous variation in rearing conditions is difficult to accommodate within the classical fixed-effect treatment approach (where it represents noise around treatment means), it is readily accessible for analysis of condition dependence with a quantitative genetic approach. This approach requires that birds are randomly cross-fostered among broods, because this allows us to separate the environmental effects from the genetic differences in early growth.
Here, we test the effects of this full range of early growth conditions on a range of traits in a large sample. We employ full individual cross-fostering of the offspring at the egg stage within 1 day of laying, so that environmental conditions are independent of genetic or parental qualities. The cross-fostering ensures that each egg is randomly assigned with regard to clutch size, hatch order and foster parents, and siblings are spread randomly across foster pairs. We use a quantitative genetic approach employing an ‘animal model’ to account for the effect of the individual’s own genotype on its early growth and adult traits (Kruuk, 2004). Our main focus is on environmental correlations (i.e. the extent to which the experienced environmental growth conditions have correlated effects on early growth and adult traits). However, the use of multi-trait animal models allows us to also look at genetic correlations (i.e. the extent to which the genotypes of individuals have correlated effects on early growth and adult traits). With our approach, experimental manipulation of early growth conditions takes a different value for each cross-fostered individual (rather than the classical two-level fixed effect treatment), and the strength of this treatment is estimated from the growth phenotype by statistically accounting for heritable variation in early growth. Importantly, this analysis captures the entire environmental component of early growth, which represents about 87% of the total phenotypic variation in growth (see Methods), instead of focusing on only one aspect of the environment (e.g. brood size).
We measure both presumably naturally and presumably sexually selected traits in both sexes, so that the condition dependence of sexually selected traits can be compared to that of nonsexually selected traits, or to homologous, but presumably not sexually selected traits in the opposite sex (Cotton et al., 2004). To identify any life-history trade-offs, we also look at reproductive success and longevity.
In this way, we obtain a relatively complete picture of the potential for traits to honestly indicate quality by reflecting past condition in the zebra finch. Although we might expect most traits to exhibit some degree of condition dependence, the developmental stress hypothesis predicts that sexually selected traits (e.g. song, beak colour, plumage ornaments) should show heightened condition dependence in comparison with naturally selected traits. Further, if compensation occurs and is costly, we would expect effects on attractiveness, reproductive success and/or longevity. We expect the strongest effects on traits that develop during the actual period of stress (e.g. tarsus length), whereas we expect weaker effects on traits that develop after the period of stress has ended. In contrast to the environmental correlations, the predictions regarding the genetic correlation between early growth and adult traits are unclear. If growing to a large size reflects ‘good genes’, genes for a high mass at day 8 may be generally ‘good genes’. Alternatively, a high mass at day 8 may reflect a fast growth strategy (e.g. to avoid nest predation by minimizing the time spent in the nest). In this case, we may rather expect trade-offs between early growth and the development of adult traits. Our aim here is therefore to conduct an initial exploration of the genetic correlations between mass at day 8 and adult traits.