Many bird species have colourful, intricately patterned plumage. This ornamentation is generally believed to exist to attract partners. In the 1970s, however, scientists proposed an alternative idea, called the ‘status signalling hypothesis’. This suggests that some birds have plumage ornaments that indicate the fighting abilities or dominance status of their bearers, much like the military badges worn by humans. These badges of status might evolve because fights, which commonly determine who gets valuable resources such as food, are a risky business. Individuals would greatly benefit from being able to predict the fighting abilities of any potential competitor and so avoid fights that they will probably lose.

Male house sparrows have a black patch on their throat, known as the bib, that has been considered to be a textbook demonstration of the status signalling hypothesis. However, most of the studies that support this idea studied small numbers of birds and used inconsistent methods. Furthermore, some recent studies have failed to replicate previous findings.

Sánchez-Tójar et al. collected data from several house sparrow populations across the world and systematically scrutinized the published literature to find all of the studies that tested the status signalling hypothesis in house sparrows. This revealed only weak evidence that the bib of male house sparrows signals the fighting abilities of its bearer. Instead, the published literature is a biased subsample; failures to replicate the hypothesis likely remain unpublished.

Currently, failures to replicate previous findings are generally deemed uninteresting, and so are not often published. By demonstrating the need to replicate findings robustly to avoid biasing conclusions, Sánchez-Tójar et al. thus join the call for a change in incentives and scientific culture.

Plumage ornamentation is a striking example of colour and pattern diversity in the animal kingdom and has attracted considerable research (Hill, 2002). Most studies have focused on sexual selection as the key mechanism to explain this diversity in ornamentation (Andersson, 1994; Dale et al., 2015). The status signalling hypothesis explains within-species variation in ornaments by suggesting that these ornaments signal individual dominance status or fighting ability (Rohwer, 1975). Aggressive contests are costly in terms of energy use, and risk of injuries and predation (Jakobsson et al., 1995; Kelly and Godin, 2001; Neat et al., 1998; Prenter et al., 2006; Sneddon et al., 1998). These costs could be reduced if individuals can predict the outcome of such contests beforehand using so-called ‘badges of status’ – that is, two potential competitors could decide whether to avoid or engage in aggressive interactions based on the message provided by their opponent’s signals (Rohwer, 1975).

Patches of ornamentation have been suggested to function as badges of status in a wide range of taxa, including insects (Tibbetts and Dale, 2004), reptiles (Whiting et al., 2003) and birds (Senar, 2006). The status signalling hypothesis was originally proposed to explain variation in the size of mountain sheep horns (Beninde, 1937; Geist, 1966), but the hypothesis has become increasingly important in the study of variability in plumage ornamentation in birds (Rohwer, 1975; Senar, 2006). Among the many bird species studied (Santos et al., 2011), the house sparrow (Passer domesticus) has become the classic textbook example of status signalling (Andersson, 1994; Searcy and Nowicki, 2005; Senar, 2006; Davies et al., 2012). The house sparrow is a sexually dimorphic passerine, in which the main difference between the sexes is a prominent black patch on the male’s throat and chest (hereafter ‘bib’). Many studies have suggested that bib size serves as a badge of status, but most studies are based on limited sample sizes, and have used inconsistent methodologies for measuring bib and dominance status (Nakagawa and Cuthill, 2007; Santos et al., 2011).

Meta-analysis is a powerful tool to quantitatively test the overall (across-study) effect size (i.e. the ‘meta-analytic mean’) for a specific hypothesis. Meta-analyses are therefore able to provide more robust conclusions than single studies and are increasingly used in evolutionary ecology (Gurevitch et al., 2018; Nakagawa and Poulin, 2012a; Nakagawa and Santos, 2012b; Senior et al., 2016). Traditional meta-analyses combine summary data across different studies, where design and methodology are study-specific (e.g. effect sizes among studies are typically adjusted for different fixed effects). These differences among studies are expected to increase heterogeneity, and therefore, the uncertainty of the meta-analytic mean (Mengersen et al., 2013). Meta-analysis of primary or raw data is a specific type of meta-analysis where studies are analysed in a consistent manner (Mengersen et al., 2013). This type of meta-analysis allows methodology to be standardized so that comparable effect sizes can be obtained across studies and is, therefore, considered the gold standard in disciplines such as medicine (Simmonds et al., 2005). Unfortunately, meta-analysis of primary data is still rarely used in evolutionary ecology (but see Barrowman et al., 2003; Richards and Bass, 2005; Krasnov et al., 2009), perhaps due to the difficulty of obtaining the primary data of previously published studies until recently (Culina et al., 2018; Schmid et al., 2003).

An important feature of any meta-analysis is to identify the existence of bias in the literature (Nakagawa and Santos, 2012b; Jennions et al., 2013). For example, publication bias occurs whenever particular effect sizes (e.g. larger ones) are more likely found in the literature than others (e.g. smaller ones). This tends to be the case when statistical significance and/or direction of effect sizes determines whether results were submitted or accepted for publication (Jennions et al., 2013). Thus, publication bias can strongly affect the estimation of the meta-analytic mean, and distort the interpretation of the hypothesis (Rothstein et al., 2005). Several methods have been developed to identify this and other biases (Nakagawa and Santos, 2012b; Jennions et al., 2013); however, such methods are imperfect and dependent on the number of effect sizes available, and therefore should be considered as types of sensitivity analysis (Nakagawa et al., 2017; Nakagawa and Santos, 2012b).

Here, we meta-analytically assessed the textbook example of the status signalling hypothesis in the house sparrow. Specifically, we combined summary and primary data from published and unpublished studies to test the prediction that dominance rank is positively associated with bib size across studies. We found that the meta-analytic mean was small, uncertain and overlapped zero. Hence, our results challenge the status signalling function of the male house sparrow’s bib. Also, we identified several biases in the published literature. Finally, we discuss potential biological explanations for our results, and provide advice for future studies testing the status signalling hypothesis.

Overall, we obtained the primary data for seven of 13 (54%) published studies, and we provided data for six additional unpublished studies (Table 1—Appendix 1).

Meta-analytic mean

Our meta-analyses revealed a small overall effect size with large 95% credible intervals that overlapped zero (Table 2; Figure 1). Additionally, the overall heterogeneity (I²_overall) was moderate (53%; Table 2). Thus, our results suggested that generally, bib size is at best a weak and unreliable signal of dominance status in male house sparrows.

Figure 1

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Table 2

Meta-analysis	K	Meta-analytic mean [95% CrI]	I2population ID [95% CrI] (%)	I2study ID [95% CrI] (%)	I2overall [95% CrI] (%)	Egger’s regression [95% CrI]
meta 1	85	0.23 [−0.01,0.45]	16 [0,48]	21 [0,51]	53 [33,73]	−0.13 [−0.59,0.27]
meta 2	87	0.20 [−0.01,0.40]	15 [0,46]	20 [0,49]	53 [34,74]	−0.12 [−0.55,0.28]

1. k = number of estimates; CrI = credible intervals; I² = heterogeneity.

Detection of publication bias

There was no clear asymmetry in the funnel plots (Figure 2). Also, Egger’s regression tests did not show evidence of funnel plot asymmetry in any of the meta-analyses (Table 2). However, published effect sizes were larger than unpublished ones, and the latter were not different from zero (Table 4; Figure 3). Additionally, we found that the overall effect size decreased over time and approached zero (Table 4; Figure 4).

Figure 2

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Figure 3

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Figure 4

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Table 4

Meta-regression	Estimates	Mean [95% CrI]
time-lag bias	intercept	0.26 [0.03,0.57]
(k = 53)	year of publication	−0.21 [-0.41,–0.01]
	R2marginal=	29 [0,66]
published vs.	intercept	−0.09 [-0.37,0.18]
unpublished (k = 85)	publisheda	0.50 [0.19,0.81]
	R2marginal=	38 [0,68]

1. k = number of estimates; CrI = credible intervals; R²_marginal = percentage of variance explained by the moderators; ^a relative to unpublished. Year of publication was z-transformed.

The male house sparrow’s bib is not the strong across-study predictor of dominance status once believed. In contrast to the medium-to-large effect found in the previous meta-analysis (Nakagawa et al., 2007), our updated meta-analytic mean was small, uncertain and overlapped zero. Thus, the male house sparrow’s bib should not be unambiguously considered or called a badge of status. Furthermore, we found evidence for the existence of bias in the published literature that further undermines the validity of the available support for the status signalling hypothesis. First, the meta-analytic mean of unpublished studies was essentially zero, compared to the medium effect size detected in published studies. Second, we found that the effect size estimated in published studies has been decreasing over time, and recently published effects were on average no longer distinguishable from zero. Our findings call for reconsidering this textbook example in evolutionary and behavioural ecology, and should stimulate renewed attention to hypotheses explaining within-species variation in ornamentation.

The status signalling hypothesis (Rohwer, 1975) has been extensively tested to try and explain within-species trait variation (e.g. reptiles: Whiting et al., 2003; insects: Tibbetts and Dale, 2004; humans: Dixson and Vasey, 2012), particularly plumage variation (Santos et al., 2011). Soon after the first empirical tests on birds, the black bib of male house sparrows became a textbook example of the status signalling hypothesis (Andersson, 1994; Searcy and Nowicki, 2005; Senar, 2006; Davies et al., 2012), an idea that was later confirmed meta-analytically (Nakagawa et al., 2007). However, Nakagawa et al., 2007 meta-analytic mean was over-estimated because only nine low-powered studies were available (more in Button et al., 2013). Here, we updated that meta-analysis with newly published and unpublished data. Our results showed that the overall effect size is much smaller and much more uncertain than previously thought. The status signalling hypothesis is thus no longer a compelling explanation for the evolution of bib size across populations of house sparrows.

Similar contradicting conclusions have been reported for other model species. An exhaustive review and meta-analysis on plumage coloration of blue tits (Cyanistes caeruleus) revealed that, after dozens of publications studying the function of plumage ornamentation in this species, the only robust conclusion is that females’ plumage differs from that of males (Parker, 2013). Another example is the long-believed effect of leg bands of particular colours on the perceived attractiveness of male zebra finches (Taeniopygia guttata), which has been also experimentally and meta-analytically refuted (Seguin and Forstmeier, 2012; Wang et al., 2018). Finally, the existence of a badge of status in a non-bird model species, the paper wasp (Polistes dominulus; Tibbetts and Dale, 2004) has also been challenged multiple times (e.g. Cervo et al., 2008; Green and Field, 2011; Green et al., 2013), generating doubts about its generality. Our findings corroborate studies showing that abundant replication is needed before any strong or general conclusion can be drawn (Aarts et al., 2015), and highlight the existence of important impediments (e.g. publication bias) to scientific progress in evolutionary ecology (Forstmeier et al., 2017; Fraser et al., 2018).

Indeed, our results showed that the published literature on status signalling in house sparrows is likely a biased subsample. The main evidence for this is that the mean effect size of unpublished studies was essentially zero and clearly different from the mean effect size based on published studies, which was of medium size. Furthermore, this moderator (i.e. unpublished vs. published) explained a large percentage of the model’s variance. In some of our own unpublished datasets, the relationship between dominance rank and bib size was never formally tested (D.F. Westneat and V. Bókony, personal communication, February, 2018), that is, our unpublished datasets are not all examples of the ‘file drawer problem’ (sensu Rosenthal, 1979). Egger’s regression tests failed to detect any funnel plot asymmetry, even in the meta-analyses based on published effect sizes only (Appendix 2—table 1). However, because unpublished data indeed existed (i.e. those obtained for this study), the detection failure was likely the consequence of the limited number of effect sizes available (i.e. low power) and the moderate level of heterogeneity found in this study (Moreno et al., 2009; Sterne and Egger, 2005).

An additional type of publication bias is time-lag bias, where early studies report larger effect sizes than later studies (Trikalinos and Ioannidis, 2005). We detected evidence for such bias because the correlation between dominance rank and bib size in published studies has decreased over time and approached zero. Year of publication explained a large percentage of the model's variance, and accounting for year of publication resulted in a strong reduction of the mean effect size across published studies (Table 4 vs. Appendix 2—table 1). Time-lag bias has been detected in other ecological studies (Poulin, 2000); Jennions and Moller, 2002b), including a meta-analysis on status signalling across bird species (Santos et al., 2011). In the latter study, a positive overall (across-species) effect size persisted regardless of the time-lag bias, and no strong evidence for other types of biases was found (Santos et al., 2011). However, Santos et al., 2011 did not attempt to analyse unpublished data, so additional evidence is needed to determine the effect that unpublished data may have on the overall validity of the status signalling hypothesis across bird species. If effect sizes based on unpublished data for other species were of similar magnitude to those obtained for house sparrows, the validity of the status signalling hypothesis across species would need reconsideration. The existence of publication bias in ecology has long been recognized (Cassey et al., 2004; Jennions and Moller, 2002b; Palmer, 2000). Publication bias leads to false conclusions if not accounted for (Rothstein et al., 2005), and is, thus, a serious impediment to scientific progress.

In addition to estimating the overall effect size for a hypothesis, meta-analyses are also used to assess heterogeneity among estimates (Higgins and Thompson, 2002; Higgins et al., 2003). Understanding the sources of heterogeneity is an important step towards the correct interpretation of a meta-analytic mean, and can be done using meta-regressions (Nakagawa and Santos, 2012b). Here, we found that the percentage of variance that was not attributable to sampling error (i.e. heterogeneity) was moderate. This value is below the average calculated across ecological and evolutionary meta-analyses (Senior et al., 2016), and indicates that we accounted for large differences among estimates. Our meta-regressions based on biological moderators explained 20–23% of the variance (Table 3). However, none of the biological moderators that we tested strongly influenced the overall effect size, possibly because of limited sample sizes.

The badge of status idea is more complex than typically portrayed (reviewed by Diep and Westneat, 2013). Badges of status are expected to be particularly important in large and unstable groups of individuals where individual recognition would otherwise be difficult (Rohwer, 1975). While the evolution of badges of status in New and Old World sparrows has been related to sociality (i.e. flocking) during the non-breeding season (Tibbetts and Safran, 2009), additional factors need to be involved if the signal is to function in reducing aggression but retaining honesty (Diep and Westneat, 2013). Our results, however, did not show any evidence for a season-dependent effect as the moderator ‘season’ (breeding vs. non-breeding) was not a strong predictor in our models. Badges of status are expected to function both within and between sexes (Rohwer, 1975; Senar, 2006). Indeed, we found little evidence that the status signalling function of bib size differed between male-only and mixed-sex flocks. Interestingly, when competing for resources, possessing a badge of status would be beneficial for both males and females. However, male but not female house sparrows have a bib. This sexual dimorphism suggests that the bib’s function is likely more important when competing for resources other than essential, a priori non-sex-specific resources such as food, water, sand baths and roosting sites. Møller, 1988 and Pape Moller, 1989 reported that female house sparrows preferentially choose males with large bibs (but see Kimball, 1996), and bib size has been positively correlated with sexual behaviour (Veiga, 1996; Møller, 1990), which suggests that the bib may play a role in mate choice. Furthermore, the original status signalling hypothesis posits that the main benefit of using badges of status would be to avoid fights, which should be particularly important when interacting with unfamiliar individuals (Rohwer, 1975; Senar, 2006). Although we did not have data to test whether unfamiliarity among contestants is an important pre-requisite for the status signalling hypothesis, we found no change in mean effect size when only obviously aggressive interactions were studied. In practice, testing whether the bib is important in mediating aggression among unfamiliar individuals is difficult because the certainty of the estimates of individual dominance increases over time as more contests are recorded, but so does familiarity among contestants.

There are some additional explanations for the small and uncertain effect detected by our meta-analyses. First, different populations might be under different selective pressures regarding status signalling. Indeed, the population-specific heterogeneity (I²_{population ID}) estimated in our meta-analyses was 15–16%, suggesting that population-dependent effects might exist. Second, although none of the moderators had a strong influence on the overall effect size, the study-specific heterogeneity estimated in our meta-analyses (I²_{study ID} = 20–21%) suggests that the uncertainty observed could still be explained by the status signal being context-dependent. However, context-dependence is often invoked post hoc to explain variation among studies, but strong evidence for it is lacking in most cases. Last, most studies testing the status signalling hypothesis in house sparrows are observational (Table 1), and the only two experimental studies conducted so far were inconclusive (Diep, 2012; Gonzalez et al., 2002). Thus, it cannot be ruled out that the weak correlation observed between dominance status and bib size is driven by a third, unknown variable. In this respect, it has been proposed that the association between melanin-based coloration (such as the bib; e.g. Galván et al., 2015; Galván and Alonso-Alvarez, 2017) and aggression is due to pleiotropic effects of the genes involved in regulating the synthesis of melanin (reviewed by Ducrest et al., 2008). Furthermore, bib size has been shown to correlate with testosterone, a hormone often involved in aggressive behaviour (Gonzalez et al., 2001) but this relationship has not been consistently observed (Laucht et al., 2010). Future studies should shift the focus towards understanding the function of bib size in wild populations and increase considerably the number of birds studied per group. The latter is essential because the statistical power of published tests of the status signalling hypothesis in house sparrows is alarmingly low (power = 8.5% for r = 0.20, Appendix 3) and lower than the average in behavioural ecology (Jennions, 2003).

Our analyses have several potential limitations. First, although the number of studies included in this meta-analysis is more than double that of the previous meta-analysis (Nakagawa et al., 2007), it is still limited. Also, it is likely (see above) that additional unpublished data are stored in ‘file drawers’ (sensu Rosenthal, 1979). Second, most tests included in this study were still low-powered in terms of group size (median = 6 individuals/estimate, range = 4–41), and the sample size is inflated because some of the published studies pooled individuals from different groups (Figure 4). Third, although our results showed little evidence of an effect of sampling effort on the overall effect size, the quality of the data on dominance and bib size may still be a potential factor explaining differences among studies. Fourth, experiments will normally yield larger effect sizes than observational studies because effects of confounding factors can be reduced (Palmer, 2000). Nonetheless, our systematic review only identified two studies where the status signalling hypothesis was tested experimentally in house sparrows (Gonzalez et al., 2002; Diep, 2012), preventing us from estimating the meta-analytic mean for experimental studies. Note, however, that the results of those experiments were inconclusive, and potentially affected by regression to the mean (Forstmeier et al., 2017).

In conclusion, our results challenge an established textbook example of the status signalling hypothesis, which aims to explain within-species variation in ornament size. In house sparrows, we find no evidence that bib size consistently acts as a badge of status across studies and populations, and thus, bib size can no longer be considered a textbook example of the status signalling hypothesis. Furthermore, our analyses highlight the existence of publication biases in the literature, further undermining the validity of past conclusions. Bias against the publication of small (‘non-significant’) effects hinders scientific progress. We thus join the call for a change in incentives and scientific culture in ecology and evolution (Forstmeier et al., 2017; Ihle et al., 2017; Nakagawa and Parker, 2015; Parker et al., 2016).

All data generated or analysed during this study are openly available at the Open Science Framework. We direct the reader to this project in the main text and the reference list. Link: https://osf.io/cwkxb/ DOI: 10.17605/OSF.IO/CWKXB

1. 1. Alfredo Sánchez-Tójar
   2. Shinichi Nakagawa
   3. Moisès Sánchez-Fortún
   4. Dominic A Martin
   5. Sukanya Ramani
   6. Antje Girndt
   7. Veronika Bókony
   8. Bart Kempenaers
   9. András Liker
   10. David F Westneat
   11. Terry Burke
   12. Julia Schroeder

   (2018) Open Science Framework

   Supporting information for "Meta-analysis challenges a textbook example of status signalling and demonstrates publication bias".

   https://doi.org/10.17605/OSF.IO/CWKXB

1. 1. Aarts AA
   2. Anderson JE
   3. Attridge CJ
   4. Open Science Collaboration

   (2015) Estimating the reproducibility of psychological science

   Science 349:aac4716.

   https://doi.org/10.1126/science.aac4716

   • PubMed
   • Google Scholar
2. 1. Andersson S
   2. Åhlund M

   (1991) Hunger affects dominance among strangers in house sparrows

   Animal Behaviour 41:895–897.

   https://doi.org/10.1016/S0003-3472(05)80356-2

   • Google Scholar
3. Book

   1. Andersson M

   (1994)

   Sexual Selection

   New Jersey: Princeton University Press.

   • Google Scholar
4. 1. Barrowman NJ
   2. Myers RA
   3. Hilborn R
   4. Kehler DG
   5. Field CA

   (2003) The variability among populations of coho salmon in the maximum reproductive rate and depensation

   Ecological Applications 13:784–793.

   https://doi.org/10.1890/1051-0761(2003)013[0784:TVAPOC]2.0.CO;2

   • Google Scholar
5. Book

   1. Beninde J

   (1937)

   Naturgeschichte Des Rothirshes. Monographie Wildsiiugetiere IV

   Leipzig: P. Schöps.

   • Google Scholar
6. 1. Bókony V
   2. Lendvai ÁZ
   3. Liker A

   (2006) Multiple cues in status signalling: the role of wingbars in aggressive interactions of male house sparrows

   Ethology 112:947–954.

   https://doi.org/10.1111/j.1439-0310.2006.01246.x

   • Google Scholar
7. 1. Bókony V
   2. Kulcsár A
   3. Liker A

   (2010) Does urbanization select for weak competitors in house sparrows?

   Oikos 119:437–444.

   https://doi.org/10.1111/j.1600-0706.2009.17848.x

   • Google Scholar
8. 1. Bókony V
   2. Seress G
   3. Nagy S
   4. Lendvai ÁZ
   5. Liker A

   (2012) Multiple indices of body condition reveal no negative effect of urbanization in adult house sparrows

   Landscape and Urban Planning 104:75–84.

   https://doi.org/10.1016/j.landurbplan.2011.10.006

   • Google Scholar
9. 1. Booksmythe I
   2. Mautz B
   3. Davis J
   4. Nakagawa S
   5. Jennions MD

   (2017) Facultative adjustment of the offspring sex ratio and male attractiveness: a systematic review and meta-analysis

   Biological Reviews 92:108–134.

   https://doi.org/10.1111/brv.12220

   • PubMed
   • Google Scholar
10. 1. Buchanan KL
    2. Evans MR
    3. Roberts ML
    4. Rowe L
    5. Goldsmith AR

    (2010) Does testosterone determine dominance in the house sparrow Passer domesticus? an experimental test

    Journal of Avian Biology 41:445–451.

    https://doi.org/10.1111/j.1600-048X.2010.04929.x

    • Google Scholar
11. 1. Button KS
    2. Ioannidis JP
    3. Mokrysz C
    4. Nosek BA
    5. Flint J
    6. Robinson ES
    7. Munafò MR

    (2013) Power failure: why small sample size undermines the reliability of neuroscience

    Nature Reviews Neuroscience 14:365–376.

    https://doi.org/10.1038/nrn3475

    • PubMed
    • Google Scholar
12. 1. Cassey P
    2. Ewen JG
    3. Blackburn TM
    4. Moller AP

    (2004) A survey of publication bias within evolutionary ecology

    Proceedings of the Royal Society B: Biological Sciences 271:S451–S454.

    https://doi.org/10.1098/rsbl.2004.0218

    • Google Scholar
13. 1. Cervo R
    2. Dapporto L
    3. Beani L
    4. Strassmann JE
    5. Turillazzi S

    (2008) On status badges and quality signals in the paper wasp Polistes dominulus: body size, facial colour patterns and hierarchical rank

    Proceedings of the Royal Society B: Biological Sciences 275:1189–1196.

    https://doi.org/10.1098/rspb.2007.1779

    • Google Scholar
14. Book

    1. Cohen J

    (1988)

    Statistical Power Analysis for the Behavioral Sciences (Second edition)

    New Jersey: Taylor & Francis Inc.

    • Google Scholar
15. 1. Culina A
    2. Crowther TW
    3. Ramakers JJC
    4. Gienapp P
    5. Visser ME

    (2018) How to do meta-analysis of open datasets

    Nature Ecology & Evolution 2:1053–1056.

    https://doi.org/10.1038/s41559-018-0579-2

    • PubMed
    • Google Scholar
16. 1. Curley JP

    (2016) compete: Analyzing Social Hierarchies

    compete: Analyzing Social Hierarchies, https://cran.r-project.org/web/packages/compete/index.html.

    https://cran.r-project.org/web/packages/compete/index.html

    • Google Scholar
17. 1. Dale J
    2. Dey CJ
    3. Delhey K
    4. Kempenaers B
    5. Valcu M

    (2015) The effects of life history and sexual selection on male and female plumage colouration

    Nature 527:367–370.

    https://doi.org/10.1038/nature15509

    • PubMed
    • Google Scholar
18. Book

    1. Davies NB
    2. Krebs JR
    3. West SA

    (2012)

    An Introduction to Behavioural Ecology

    Oxford: Wiley-Blackwell.

    • Google Scholar
19. Book

    1. Diep SK

    (2012)

    The Role of Social Interactions on the Development and Honesty of a Signal of Status

    University of Kentucky.

    • Google Scholar
20. 1. Diep SK
    2. Westneat DF

    (2013) The integration of function and ontogeny in the evolution of status signals

    Behaviour pp. 1–30.

    https://doi.org/10.1163/1568539X-00003066

    • Google Scholar
21. 1. Dixson BJ
    2. Vasey PL

    (2012) Beards augment perceptions of men's age, social status, and aggressiveness, but not attractiveness

    Behavioral Ecology 23:481–490.

    https://doi.org/10.1093/beheco/arr214

    • Google Scholar
22. 1. Dolnik OV
    2. Hoi H

    (2010) Honest signalling, dominance hierarchies and body condition in house sparrows Passer domesticus (Aves: Passeriformes) during acute coccidiosis

    Biological Journal of the Linnean Society 99:718–726.

    https://doi.org/10.1111/j.1095-8312.2010.01370.x

    • Google Scholar
23. 1. Ducrest AL
    2. Keller L
    3. Roulin A

    (2008) Pleiotropy in the melanocortin system, coloration and behavioural syndromes

    Trends in Ecology & Evolution 23:502–510.

    https://doi.org/10.1016/j.tree.2008.06.001

    • PubMed
    • Google Scholar
24. 1. Duval S
    2. Tweedie R

    (2000a) A nonparametric “Trim and Fill” Method of Accounting for Publication Bias in Meta-Analysis

    Journal of the American Statistical Association 95:89–98.

    https://doi.org/10.1080/01621459.2000.10473905

    • Google Scholar
25. 1. Duval S
    2. Tweedie R

    (2000b) Trim and fill: a simple funnel-plot-based method of testing and adjusting for publication Bias in meta-analysis

    Biometrics 56:455–463.

    https://doi.org/10.1111/j.0006-341X.2000.00455.x

    • PubMed
    • Google Scholar
26. 1. Farine DR
    2. Sánchez-Tójar A

    (2017) aniDom: Inferring Dominance Hierarchies and Estimating Uncertainty

    aniDom: Inferring Dominance Hierarchies and Estimating Uncertainty, https://cran.r-project.org/package=aniDom.

    https://cran.r-project.org/package=aniDom

    • Google Scholar
27. 1. Forstmeier W
    2. Wagenmakers EJ
    3. Parker TH

    (2017) Detecting and avoiding likely false-positive findings - a practical guide

    Biological Reviews 92:1941–1968.

    https://doi.org/10.1111/brv.12315

    • PubMed
    • Google Scholar
28. 1. Fraser H
    2. Parker T
    3. Nakagawa S
    4. Barnett A
    5. Fidler F

    (2018) Questionable research practices in ecology and evolution

    PLOS One 13:e0200303.

    https://doi.org/10.1371/journal.pone.0200303

    • PubMed
    • Google Scholar
29. 1. Galván I
    2. Wakamatsu K
    3. Camarero PR
    4. Mateo R
    5. Alonso-Alvarez C

    (2015) Low-quality birds do not display high-quality signals: the cysteine-pheomelanin mechanism of honesty

    Evolution 69:26–38.

    https://doi.org/10.1111/evo.12549

    • Google Scholar
30. 1. Galván I
    2. Alonso-Alvarez C

    (2017) Individual quality via sensitivity to cysteine availability in a melanin-based honest signaling system

    The Journal of Experimental Biology 220:2825–2833.

    https://doi.org/10.1242/jeb.160333

    • PubMed
    • Google Scholar
31. 1. Geist V

    (1966) The evolutionary significance of mountain sheep horns

    Evolution 20:558–566.

    https://doi.org/10.2307/2406590

    • Google Scholar
32. 1. Gonzalez G
    2. Sorci G
    3. Smith LC
    4. de Lope F

    (2001) Testosterone and sexual signalling in male house sparrows (Passer domesticus)

    Behavioral Ecology and Sociobiology 50:557–562.

    https://doi.org/10.1007/s002650100399

    • Google Scholar
33. 1. Gonzalez G
    2. Sorci G
    3. Smith LC
    4. de Lope F

    (2002) Social control and physiological cost of cheating in status signalling male house sparrows (Passer domesticus)

    Ethology 108:289–302.

    https://doi.org/10.1046/j.1439-0310.2002.00779.x

    • Google Scholar
34. 1. Green JP
    2. Field J

    (2011) Interpopulation variation in status signalling in the paper wasp Polistes dominulus

    Animal Behaviour 81:205–209.

    https://doi.org/10.1016/j.anbehav.2010.10.002

    • Google Scholar
35. 1. Green JP
    2. Leadbeater E
    3. Carruthers JM
    4. Rosser NS
    5. Lucas ER
    6. Field J

    (2013) Clypeal patterning in the paper wasp Polistes dominulus: no evidence of adaptive value in the wild

    Behavioral Ecology 24:623–633.

    https://doi.org/10.1093/beheco/ars226

    • Google Scholar
36. 1. Gurevitch J
    2. Koricheva J
    3. Nakagawa S
    4. Stewart G

    (2018) Meta-analysis and the science of research synthesis

    Nature 555:175–182.

    https://doi.org/10.1038/nature25753

    • PubMed
    • Google Scholar
37. 1. Hadfield JD

    (2010) MCMC methods for Multi-Response generalized linear mixed models: themcmcglmmrpackage

    Journal of Statistical Software 33:.

    https://doi.org/10.18637/jss.v033.i02

    • Google Scholar
38. 1. Hadfield JD
    2. Nakagawa S

    (2010) General quantitative genetic methods for comparative biology: phylogenies, taxonomies and multi-trait models for continuous and categorical characters

    Journal of Evolutionary Biology 23:494–508.

    https://doi.org/10.1111/j.1420-9101.2009.01915.x

    • PubMed
    • Google Scholar
39. 1. Hein WK
    2. Westneat DF
    3. Poston JP

    (2003) Sex of opponent influences response to a potential status signal in house sparrows

    Animal Behaviour 65:1211–1221.

    https://doi.org/10.1006/anbe.2003.2132

    • Google Scholar
40. 1. Higgins JP
    2. Thompson SG

    (2002) Quantifying heterogeneity in a meta-analysis

    Statistics in Medicine 21:1539–1558.

    https://doi.org/10.1002/sim.1186

    • PubMed
    • Google Scholar
41. 1. Higgins JP
    2. Thompson SG
    3. Deeks JJ
    4. Altman DG

    (2003) Measuring inconsistency in meta-analyses

    Bmj 327:557–560.

    https://doi.org/10.1136/bmj.327.7414.557

    • PubMed
    • Google Scholar
42. Book

    1. Hill GE

    (2002) A Red Bird in a Brown Bag: The Function and Evolution of Colorful Plumage in the House Finch

    New York: Oxford University Press.

    https://doi.org/10.1093/acprof:oso/9780195148480.001.0001

    • Google Scholar
43. 1. Ihle M
    2. Winney IS
    3. Krystalli A
    4. Croucher M

    (2017) Striving for transparent and credible research: practical guidelines for behavioral ecologists

    Behavioral Ecology 28:348–354.

    https://doi.org/10.1093/beheco/arx003

    • PubMed
    • Google Scholar
44. 1. Jakobsson S
    2. Brick O
    3. Kullberg C

    (1995) Escalated fighting behaviour incurs increased predation risk

    Animal Behaviour 49:235–239.

    https://doi.org/10.1016/0003-3472(95)80172-3

    • Google Scholar
45. 1. Jennions MD
    2. Møller AP

    (2002a) Publication Bias in ecology and evolution: an empirical assessment using the 'trim and fill' method

    Biological Reviews of the Cambridge Philosophical Society 77:211–222.

    https://doi.org/10.1017/S1464793101005875

    • PubMed
    • Google Scholar
46. 1. Jennions MD
    2. Moller AP

    (2002b) Relationships fade with time: a meta-analysis of temporal trends in publication in ecology and evolution

    Proceedings of the Royal Society B: Biological Sciences 269:43–48.

    https://doi.org/10.1098/rspb.2001.1832

    • Google Scholar
47. 1. Jennions MD

    (2003) A survey of the statistical power of research in behavioral ecology and animal behavior

    Behavioral Ecology 14:438–445.

    https://doi.org/10.1093/beheco/14.3.438

    • Google Scholar
48. Book

    1. Jennions MD
    2. Lortie C
    3. Rosenberg M
    4. Rothstein H

    (2013) Publication and related biases

    In: Koricheva J, Gurevitch J, Mengersen K, editors. Handbook of Meta-Analysis in Ecology & Evolution. Princenton: Princeton University Press. pp. 207–236.

    https://doi.org/10.1515/9781400846184-016

    • Google Scholar
49. 1. Kelly C
    2. Godin J-G

    (2001) Predation risk reduces male-male sexual competition in the trinidadian guppy (Poecilia reticulata)

    Behavioral Ecology and Sociobiology 51:95–100.

    https://doi.org/10.1007/s002650100410

    • Google Scholar
50. 1. Kimball RT

    (1996) Female choice for male morphological traits in house sparrows, Passer domesticus

    Ethology 102:639–648.

    https://doi.org/10.1111/j.1439-0310.1996.tb01155.x

    • Google Scholar
51. Book

    1. Koricheva J
    2. Jennions MD
    3. Lau J

    (2013) Temporal trends in effect sizes: causes, detection, and implications

    In: Koricheva J, Gurevitch J, Mengersen K, editors. Handbook of Meta-Analysis in Ecology & Evolution. Princenton: Princeton University Press. pp. 237–254.

    https://doi.org/10.1515/9781400846184-017

    • Google Scholar
52. 1. Krasnov BR
    2. Vinarski MV
    3. Korallo-Vinarskaya NP
    4. Mouillot D
    5. Poulin R

    (2009) Inferring associations among parasitic gamasid mites from census data

    Oecologia 160:175–185.

    https://doi.org/10.1007/s00442-009-1278-0

    • PubMed
    • Google Scholar
53. Book

    1. Lajeunesse MJ

    (2013) Recovering Missing or Partial Data from Studies: A Survey of Conversions and Imputations for Meta-analysis

    In: Koricheva J, Gurevitch J, Mengersen K, editors. Handbook of Meta-Analysis in Ecology & Evolution. Princenton: Princeton University Press. pp. 195–206.

    https://doi.org/10.1515/9781400846184-015

    • Google Scholar
54. 1. Laucht S
    2. Kempenaers B
    3. Dale J

    (2010) Bill color, not badge size, indicates testosterone-related information in house sparrows

    Behavioral Ecology and Sociobiology 64:1461–1471.

    https://doi.org/10.1007/s00265-010-0961-9

    • PubMed
    • Google Scholar
55. 1. Lendvai AZ
    2. Barta Z
    3. Liker A
    4. Bokony V

    (2004) The effect of energy reserves on social foraging: hungry sparrows scrounge more

    Proceedings of the Royal Society B: Biological Sciences 271:2467–2472.

    https://doi.org/10.1098/rspb.2004.2887

    • Google Scholar
56. 1. Liker A
    2. Barta Z

    (2001) Male badge size predicts dominance against females in house sparrows1

    The Condor 103:151–157.

    https://doi.org/10.1650/0010-5422(2001)103[0151:MBSPDA]2.0.CO;2

    • Google Scholar
57. 1. Lindström KM
    2. Hasselquist D
    3. Wikelski M

    (2005) House sparrows (Passer domesticus) adjust their social status position to their physiological costs

    Hormones and Behavior 48:311–320.

    https://doi.org/10.1016/j.yhbeh.2005.04.002

    • PubMed
    • Google Scholar
58. 1. McDonald DB
    2. Shizuka D

    (2013) Comparative transitive and temporal orderliness in dominance networks

    Behavioral Ecology 24:511–520.

    https://doi.org/10.1093/beheco/ars192

    • Google Scholar
59. Book

    1. Mengersen K
    2. Gurevitch J
    3. Schmid CH

    (2013) Meta-analysis of primary data

    In: Koricheva J, Mengersen K, Gurevit J, editors. Handbook of Meta-Analysis in Ecology & Evolution. Princenton: Princeton University Press. pp. 300–312.

    https://doi.org/10.1515/9781400846184-020

    • Google Scholar
60. 1. Moher D
    2. Liberati A
    3. Tetzlaff J
    4. Altman DG
    5. PRISMA Group

    (2009) Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement

    PLOS Medicine 6:e1000097.

    https://doi.org/10.1371/journal.pmed.1000097

    • PubMed
    • Google Scholar
61. 1. Møller AP

    (1987) Variation in badge size in male house sparrows Passer domesticus: evidence for status signalling

    Animal Behaviour 35:1637–1644.

    https://doi.org/10.1016/S0003-3472(87)80056-8

    • Google Scholar
62. 1. Møller AP

    (1988)

    Badge size in the house sparrow Passer domesticus - Effects of intra- and intersexual selection

    Behavioral Ecology and Sociobiology 22:373–378.

    • Google Scholar
63. 1. Møller A

    (1990) Sexual behavior is related to badge size in the house sparrow Passer domesticus

    Behavioral Ecology and Sociobiology 27:23–29.

    https://doi.org/10.1007/BF00183309

    • Google Scholar
64. 1. Moreno SG
    2. Sutton AJ
    3. Ades AE
    4. Stanley TD
    5. Abrams KR
    6. Peters JL
    7. Cooper NJ

    (2009) Assessment of regression-based methods to adjust for publication Bias through a comprehensive simulation study

    BMC Medical Research Methodology 9:2.

    https://doi.org/10.1186/1471-2288-9-2

    • PubMed
    • Google Scholar
65. 1. Morrison EB
    2. Kinnard TB
    3. STEWART IANRK
    4. Poston JP
    5. HATCH MI
    6. Westneat DF

    (2008) The links between plumage variation and nest site occupancy in male house sparrows

    The Condor 110:345–353.

    https://doi.org/10.1525/cond.2008.8470

    • Google Scholar
66. 1. Nakagawa S
    2. Cuthill IC

    (2007) Effect size, confidence interval and statistical significance: a practical guide for biologists

    Biological Reviews 82:591–605.

    https://doi.org/10.1111/j.1469-185X.2007.00027.x

    • PubMed
    • Google Scholar
67. 1. Nakagawa S
    2. Ockendon N
    3. Gillespie DOS
    4. Hatchwell BJ
    5. Burke T

    (2007) Assessing the function of house sparrows' bib size using a flexible meta-analysis method

    Behavioral Ecology 18:831–840.

    https://doi.org/10.1093/beheco/arm050

    • Google Scholar
68. 1. Nakagawa S
    2. Poulin R

    (2012a) Meta-analytic insights into evolutionary ecology: an introduction and synthesis

    Evolutionary Ecology 26:1085–1099.

    https://doi.org/10.1007/s10682-012-9593-z

    • Google Scholar
69. 1. Nakagawa S
    2. Santos ESA

    (2012b) Methodological issues and advances in biological meta-analysis

    Evolutionary Ecology 26:1253–1274.

    https://doi.org/10.1007/s10682-012-9555-5

    • Google Scholar
70. 1. Nakagawa S
    2. Schielzeth H

    (2013) A general and simple method for obtaining R ² from generalized linear mixed-effects models

    Methods in Ecology and Evolution 4:133–142.

    https://doi.org/10.1111/j.2041-210x.2012.00261.x

    • Google Scholar
71. 1. Nakagawa S
    2. Noble DW
    3. Senior AM
    4. Lagisz M

    (2017) Meta-evaluation of meta-analysis: ten appraisal questions for biologists

    BMC Biology 15:18.

    https://doi.org/10.1186/s12915-017-0357-7

    • PubMed
    • Google Scholar
72. 1. Nakagawa S
    2. Parker TH

    (2015) Replicating research in ecology and evolution: feasibility, incentives, and the cost-benefit conundrum

    BMC Biology 13:88.

    https://doi.org/10.1186/s12915-015-0196-3

    • PubMed
    • Google Scholar
73. 1. Neat FC
    2. Taylor AC
    3. Huntingford FA

    (1998) Proximate costs of fighting in male cichlid fish: the role of injuries and energy metabolism

    Animal Behaviour 55:875–882.

    https://doi.org/10.1006/anbe.1997.0668

    • PubMed
    • Google Scholar
74. 1. Palmer AR

    (2000) Quasi-Replication and the contract of error: lessons from sex ratios, heritabilities and fluctuating asymmetry

    Annual Review of Ecology and Systematics 31:441–480.

    https://doi.org/10.1146/annurev.ecolsys.31.1.441

    • Google Scholar
75. 1. Pape Moller A

    (1989) Natural and sexual selection on a plumage signal of status and on morphology in house sparrows, Passer domesticus

    Journal of Evolutionary Biology 2:125–140.

    https://doi.org/10.1046/j.1420-9101.1989.2020125.x

    • Google Scholar
76. 1. Parker TH

    (2013) What do we really know about the signalling role of plumage colour in blue tits? A case study of impediments to progress in evolutionary biology

    Biological Reviews 88:511–536.

    https://doi.org/10.1111/brv.12013

    • PubMed
    • Google Scholar
77. 1. Parker TH
    2. Forstmeier W
    3. Koricheva J
    4. Fidler F
    5. Hadfield JD
    6. Chee YE
    7. Kelly CD
    8. Gurevitch J
    9. Nakagawa S

    (2016) Transparency in ecology and evolution: real problems, real solutions

    Trends in Ecology & Evolution 31:711–719.

    https://doi.org/10.1016/j.tree.2016.07.002

    • PubMed
    • Google Scholar
78. 1. Poulin R

    (2000) Manipulation of host behaviour by parasites: a weakening paradigm?

    Proceedings of the Royal Society B: Biological Sciences 267:787–792.

    https://doi.org/10.1098/rspb.2000.1072

    • PubMed
    • Google Scholar
79. 1. Prenter J
    2. Elwood RW
    3. Taylor PW

    (2006) Self-assessment by males during energetically costly contests over precopula females in amphipods

    Animal Behaviour 72:861–868.

    https://doi.org/10.1016/j.anbehav.2006.01.023

    • Google Scholar
80. Software

    1. R Core Team

    (2017)

    R: A language and environment for statistical computing

    R Foundation for Statistical Computing, Vienna.
81. 1. Richards TA
    2. Bass D

    (2005) Molecular screening of free-living microbial eukaryotes: diversity and distribution using a meta-analysis

    Current Opinion in Microbiology 8:240–252.

    https://doi.org/10.1016/j.mib.2005.04.010

    • PubMed
    • Google Scholar
82. 1. Ritchison G

    (1985)

    Plumage variability and social status in captive male house sparrows

    Kentucky Warbler 61:39–42.

    • Google Scholar
83. 1. Riters LV
    2. Teague DP
    3. Schroeder MB

    (2004) Social status interacts with badge size and neuroendocrine physiology to influence sexual behavior in male house sparrows (Passer domesticus)

    Brain, Behavior and Evolution 63:141–150.

    https://doi.org/10.1159/000076240

    • PubMed
    • Google Scholar
84. 1. Rohwer S

    (1975) The social significance of avian winter plumage variability

    Evolution 29:593.

    https://doi.org/10.2307/2407071

    • Google Scholar
85. 1. Rojas Mora A
    2. Meniri M
    3. Glauser G
    4. Vallat A
    5. Helfenstein F

    (2016) Badge size reflects sperm oxidative status within social groups in the house sparrow Passer domesticus

    Frontiers in Ecology and Evolution 4:67.

    https://doi.org/10.3389/fevo.2016.00067

    • Google Scholar
86. 1. Rosenthal R

    (1979) The file drawer problem and tolerance for null results

    Psychological Bulletin 86:638–641.

    https://doi.org/10.1037/0033-2909.86.3.638

    • Google Scholar
87. Book

    1. Rothstein H
    2. Sutton A
    3. Borenstein M

    (2005) Publication Bias in Meta-Analysis: Prevention, Assessment and Adjustments

    Chichester: Wiley.

    https://doi.org/10.1002/0470870168

    • Google Scholar
88. 1. Sánchez-Tójar A
    2. Nakagawa S
    3. Sánchez-Fortún M
    4. Martin DA
    5. Ramani S
    6. Girndt A
    7. Bókony V
    8. Kempenaers B
    9. Liker A
    10. Westneat DF
    11. Burke T
    12. Schroeder J

    (2018)

    Supporting information for " Meta-analysis challenges a textbook example of status signalling and demonstrates publication bias"

    Supporting information for " Meta-analysis challenges a textbook example of status signalling and demonstrates publication bias".

    • Google Scholar
89. 1. Sánchez-Tójar A
    2. Schroeder J
    3. Farine DR

    (2018b) A practical guide for inferring reliable dominance hierarchies and estimating their uncertainty

    Journal of Animal Ecology 87:594–608.

    https://doi.org/10.1111/1365-2656.12776

    • PubMed
    • Google Scholar
90. 1. Santos ESA
    2. Scheck D
    3. Nakagawa S

    (2011) Dominance and plumage traits: meta-analysis and metaregression analysis

    Animal Behaviour 82:3–19.

    https://doi.org/10.1016/j.anbehav.2011.03.022

    • Google Scholar
91. 1. Schielzeth H

    (2010) Simple means to improve the interpretability of regression coefficients

    Methods in Ecology and Evolution 1:103–113.

    https://doi.org/10.1111/j.2041-210X.2010.00012.x

    • Google Scholar
92. 1. Schmid CH
    2. Landa M
    3. Jafar TH
    4. Giatras I
    5. Karim T
    6. Reddy M
    7. Stark PC
    8. Levey AS
    9. Angiotensin-Converting Enzyme Inhibition in Progressive Renal Disease (AIPRD) Study Group

    (2003) Constructing a database of individual clinical trials for longitudinal analysis

    Controlled Clinical Trials 24:324–340.

    https://doi.org/10.1016/S0197-2456(02)00319-7

    • PubMed
    • Google Scholar
93. Book

    1. Searcy WA
    2. Nowicki S

    (2005)

    The evolution of animal communication. Reliability and deception in signaling systems

    New Jersey: Princeton University Press.

    • Google Scholar
94. 1. Seguin A
    2. Forstmeier W

    (2012) No band color effects on male courtship rate or body mass in the zebra finch: four experiments and a meta-analysis

    PLOS ONE 7:e37785.

    https://doi.org/10.1371/journal.pone.0037785

    • PubMed
    • Google Scholar
95. Book

    1. Senar JC

    (2006)

    Color displays as intrasexual signals of aggression and dominance

    In: Hill G. E, McGraw K. J, editors. Bird Coloration: Function and Evolution. London: Harvard University Press. pp. 87–136.

    • Google Scholar
96. 1. Senior AM
    2. Grueber CE
    3. Kamiya T
    4. Lagisz M
    5. O'Dwyer K
    6. Santos ES
    7. Nakagawa S

    (2016) Heterogeneity in ecological and evolutionary meta-analyses: its magnitude and implications

    Ecology 97:3293–3299.

    https://doi.org/10.1002/ecy.1591

    • PubMed
    • Google Scholar
97. 1. Simmonds MC
    2. Higginsa JPT
    3. Stewartb LA
    4. Tierneyb JF
    5. Clarke MJ
    6. Thompson SG

    (2005) Meta-analysis of individual patient data from randomized trials: a review of methods used in practice

    Clinical Trials: Journal of the Society for Clinical Trials 2:209–217.

    https://doi.org/10.1191/1740774505cn087oa

    • Google Scholar
98. 1. Sneddon LU
    2. Huntingford FA
    3. Taylor AC

    (1998) Impact of an ecological factor on the costs of resource acquisition: fighting and metabolic physiology of crabs

    Functional Ecology 12:808–815.

    https://doi.org/10.1046/j.1365-2435.1998.00249.x

    • Google Scholar
99. 1. Solberg EJ
    2. Ringsby TH

    (1997) Does male badge size signal status in small island populations of house sparrows, Passer domesticus?

    Ethology 103:177–186.

    https://doi.org/10.1111/j.1439-0310.1997.tb00114.x

    • Google Scholar
100. Book

     1. Sterne J
     2. Egger M

     (2005) Regression methods to detect publication and other bias in meta-analysis

     In: Rothstein H, Sutton A, Borenstein M, editors. Publication Bias in Meta-Analysis2. Chichester: John Wiley. pp. 99–110.

     https://doi.org/10.1002/0470870168.ch6

     • Google Scholar
101. 1. Tibbetts EA
     2. Dale J

     (2004) A socially enforced signal of quality in a paper wasp

     Nature 432:218–222.

     https://doi.org/10.1038/nature02949

     • PubMed
     • Google Scholar
102. 1. Tibbetts EA
     2. Safran RJ

     (2009) Co-evolution of plumage characteristics and winter sociality in new and old world sparrows

     Journal of Evolutionary Biology 22:2376–2386.

     https://doi.org/10.1111/j.1420-9101.2009.01861.x

     • PubMed
     • Google Scholar
103. 1. Tóth Z
     2. Bókony V
     3. Lendvai Ádám Z.
     4. Szabó K
     5. Pénzes Z
     6. Liker A

     (2009) Kinship and aggression: do house sparrows spare their relatives?

     Behavioral Ecology and Sociobiology 63:1189–1196.

     https://doi.org/10.1007/s00265-009-0768-8

     • Google Scholar
104. Book

     1. Trikalinos T
     2. Ioannidis JPA

     (2005) Assessing the evolution of effect sizes over time

     In: Rothstein H, Sutton A, Borenstein M, editors. Publication Bias in Meta-Analysis. Chichester: John Wiley. pp. 241–259.

     https://doi.org/10.1002/0470870168.ch13

     • Google Scholar
105. 1. Veiga JP

     (1993) Badge size, phenotypic quality, and reproductive success in the house sparrow: a study on honest advertisement

     Evolution 47:1161–1170.

     https://doi.org/10.1111/j.1558-5646.1993.tb02143.x

     • Google Scholar
106. 1. Veiga JP

     (1996) Mate replacement is costly to males in the multibrooded house sparrow: an experimental study

     The Auk 113:664–671.

     https://doi.org/10.2307/4088987

     • Google Scholar
107. 1. Wang D
     2. Forstmeier W
     3. Ihle M
     4. Khadraoui M
     5. Jerónimo S
     6. Martin K
     7. Kempenaers B

     (2018) Irreproducible text-book “knowledge”: The effects of color bands on zebra finch fitness

     Evolution 72:961–976.

     https://doi.org/10.1111/evo.13459

     • Google Scholar
108. Book

     1. Whiting MJ
     2. Nagy KA
     3. Bateman PW

     (2003)

     Evolution and maintenance of social status-signalling badges

     In: Fox S. F, McCoy K, Baird T. A, editors. Lizard Social Behavior. Baltimore: Johns Hopkins University Press. pp. 47–82.

     • Google Scholar

Author details

1. Alfredo Sánchez-Tójar

   1. Evolutionary Biology Group, Max Planck Institute for Ornithology, Seewiesen, Germany
   2. Department of Life Sciences, Imperial College London, Ascot, United Kingdom

   Present address

   Department of Evolutionary Biology, Bielefeld University, Bielefeld, Germany

   Contribution

   Conceptualization, Data curation, Software, Formal analysis, Validation, Investigation, Visualization, Methodology, Writing—original draft, Project administration, Writing—review and editing

   For correspondence

   alfredo.tojar@gmail.com

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-2886-0649

2. Shinichi Nakagawa

   School of Biological, Earth and Environmental Sciences, University of New South Wales, Sidney, Australia

   Contribution

   Conceptualization, Software, Supervision, Writing—review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-7765-5182

3. Moisès Sánchez-Fortún

   1. Evolutionary Biology Group, Max Planck Institute for Ornithology, Seewiesen, Germany
   2. Department of Animal and Plant Sciences, University of Sheffield, Sheffield, United Kingdom

   Present address

   Department de Biologia Evolutiva, Ecologia i Ciències Ambientals, University of Barcelona, Barcelona, Spain

   Contribution

   Investigation, Writing—review and editing

   Competing interests

   No competing interests declared

4. Dominic A Martin

   Department of Life Sciences, Imperial College London, Ascot, United Kingdom

   Present address

   Biodiversity, Macroecology and Biogeography, University of Goettingen, Goettingen, Germany

   Contribution

   Investigation, Writing—review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0001-7197-2278

5. Sukanya Ramani

   1. Evolutionary Biology Group, Max Planck Institute for Ornithology, Seewiesen, Germany
   2. Department of Animal Behaviour, Bielefeld University, Bielefeld, Germany

   Contribution

   Investigation, Writing—review and editing

   Competing interests

   No competing interests declared

6. Antje Girndt

   1. Evolutionary Biology Group, Max Planck Institute for Ornithology, Seewiesen, Germany
   2. Department of Life Sciences, Imperial College London, Ascot, United Kingdom

   Contribution

   Investigation, Writing—review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-9558-1201

7. Veronika Bókony

   Lendület Evolutionary Ecology Research Group, Plant Protection Institute, Centre for Agricultural Research, Hungarian Academy of Sciences, Budapest, Hungary

   Contribution

   Investigation, Writing—review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-2136-5346

8. Bart Kempenaers

   Department of Behavioural Ecology and Evolutionary Genetics, Max Planck Institute for Ornithology, Seewiesen, Germany

   Contribution

   Investigation, Writing—review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-7505-5458

9. András Liker

   MTA-PE Evolutionary Ecology Research Group, University of Pannonia, Veszprém, Hungary

   Contribution

   Investigation, Writing—review and editing

   Competing interests

   No competing interests declared

10. David F Westneat

    Department of Biology, University of Kentucky, Lexington, United States

    Contribution

    Investigation, Writing—review and editing

    Competing interests

    No competing interests declared

    "This ORCID iD identifies the author of this article:" 0000-0001-5163-8096

11. Terry Burke

    Department of Animal and Plant Sciences, University of Sheffield, Sheffield, United Kingdom

    Contribution

    Conceptualization, Supervision, Funding acquisition, Writing—review and editing

    Competing interests

    No competing interests declared

    "This ORCID iD identifies the author of this article:" 0000-0003-3848-1244

12. Julia Schroeder

    1. Evolutionary Biology Group, Max Planck Institute for Ornithology, Seewiesen, Germany
    2. Department of Life Sciences, Imperial College London, Ascot, United Kingdom

    Contribution

    Conceptualization, Supervision, Funding acquisition, Writing—review and editing

    Competing interests

    No competing interests declared

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