The global distribution of avian eggshell colours suggest a thermoregulatory benefit of darker pigmentation


The survival of a bird’s developing embryo depends on the egg’s ability to stay within strict thermal limits. How eggshell colours help maintain thermal balance is a long-standing and contested question. Using data spanning a wide phylogenetic diversity of birds on a global spatial scale, we find evidence that eggshell pigmentation may have been shaped by thermoregulatory needs. Birds living in cold habitats, particularly those with nests exposed to incident solar radiation, have darker eggs. We show evidence that darker eggs heat more rapidly than lighter ones when exposed to solar radiation. This evidence suggests that egg pigmentation could play an important role in thermoregulation in cold climates, while a range of competing selective pressures further influence eggshell colours in warmer climates. These findings advance our understanding of thermoregulation in the distribution of natural colours.

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Fig. 1: Variation in avian eggshell brightness and colouration.
Fig. 2: An equal Earth projection of the global distribution of avian eggshell colour.
Fig. 3: Relationship between solar intensity and eggshell colour.
Fig. 4: Interspecific patterns.
Fig. 5: Differential heating by eggshell colour.

Data availability

The BirdLife International species distribution data can be requested at The Digital Chart of the World basemap can be accessed at The Natural Earth Data maps can be found at The Worldclim v.2 temperature data are available at The National Center for Atmospheric Research UV data can be found at The Atlas of the Biosphere humidity data can be found at The ISEA global grid data can be found at for the R codes or for the shapefiles. Data generated and/or analysed during this study are available from the figshare digital repository95 (

Code availability

The R script used for the statistical analysis is available upon request.


  1. 1.

    Clusella Trullas, S., van Wyk, J. H. & Spotila, J. R. Thermal melanism in ectotherms. J. Therm. Biol. 32, 235–245 (2007).

    Google Scholar 

  2. 2.

    Pinkert, S. & Zeuss, D. Thermal biology: melanin-based energy harvesting across the tree of life. Curr. Biol. 28, R887–R889 (2018).

    CAS  PubMed  Google Scholar 

  3. 3.

    Stuart-Fox, D., Newton, E. & Clusella-Trullas, S. Thermal consequences of colour and near-infrared reflectance. Phil. Trans. R. Soc. Lond. B 372, 20160345 (2017).

    Google Scholar 

  4. 4.

    Delhey, K., Dale, J., Valcu, M. & Kempenaers, B. Reconciling ecogeographical rules: rainfall and temperature predict global colour variation in the largest bird radiation. Ecol. Lett. 22, 726–736 (2019).

    PubMed  Google Scholar 

  5. 5.

    Abram, P. K. et al. An insect with selective control of egg coloration. Curr. Biol. 25, 2007–2011 (2015).

    CAS  PubMed  Google Scholar 

  6. 6.

    Torres-Campos, I., Abram, P. K., Guerra-Grenier, E., Boivin, G. & Brodeur, J. A scenario for the evolution of selective egg coloration: the roles of enemy-free space, camouflage, thermoregulation and pigment limitation. R. Soc. Open Sci. 3, 150711 (2016).

    PubMed  PubMed Central  Google Scholar 

  7. 7.

    Kilner, R. M. The evolution of egg colour and patterning in birds. Biol. Rev. Camb. Phil. Soc. 81, 383–406 (2006).

    CAS  Google Scholar 

  8. 8.

    Webb, D. R. Thermal tolerance of avian embryos: a review. Condor 89, 874–898 (1987).

    Google Scholar 

  9. 9.

    Boulton, R. L. & Cassey, P. How avian incubation behaviour influences egg surface temperatures: relationships with egg position, development and clutch size. J. Avian Biol. 43, 289–296 (2012).

    Google Scholar 

  10. 10.

    Hanley, D., Grim, T., Cassey, P. & Hauber, M. E. Not so colourful after all: eggshell pigments constrain avian eggshell colour space. Biol. Lett. 11, 20150087 (2015).

    PubMed  PubMed Central  Google Scholar 

  11. 11.

    Gorchein, A., Lim, C. K. & Cassey, P. Extraction and analysis of colourful eggshell pigments using HPLC and HPLC/electrospray ionization tandem mass spectrometry. Biomed. Chromatogr. 23, 602–606 (2009).

    CAS  PubMed  Google Scholar 

  12. 12.

    Gómez, J. et al. A trade-off between overheating and camouflage on shorebird eggshell colouration. J. Avian Biol. 47, 346–353 (2016).

    Google Scholar 

  13. 13.

    Westmoreland, D. Evidence of selection for egg crypsis in conspicuous nests. J. Field Ornithol. 79, 263–268 (2008).

    Google Scholar 

  14. 14.

    Westmoreland, D. & Best, L. B. Incubation continuity and the advantage of cryptic egg coloration to mourning doves. Wilson Bull. 98, 297–300 (1986).

    Google Scholar 

  15. 15.

    Verbeek, N. A. M. Differental predation on eggs in clutches of northwestern crows: the importance of egg color. Condor 92, 695–701 (1990).

    Google Scholar 

  16. 16.

    Castilla, A. A. M., Dhondt, A. A., Díaz-Uriarte, R. & Westmoreland, D. Predation in ground-nesting birds: an experimental study using natural egg-color variation. Avian Conserv. Ecol. 2, 2 (2007).

    Google Scholar 

  17. 17.

    Yahner, R. H. & Mahan, C. G. Effects of egg type on depredation of artificial ground nests. Wilson Bull. 108, 129–136 (1996).

    Google Scholar 

  18. 18.

    Lahti, D. C. & Ardia, D. R. Shedding light on bird egg color: pigment as parasol and the dark car effect. Am. Nat. 187, 547–563 (2016).

    PubMed  Google Scholar 

  19. 19.

    Westmoreland, D., Schmitz, M. & Burns, K. E. Egg color as an adaptation for thermoregulation. J. Field Ornithol. 78, 176–183 (2007).

    Google Scholar 

  20. 20.

    Ruxton, G. D. Comment on ‘Vegetation height and egg coloration differentially affect predation rate and overheating risk: an experimental test mimicking a ground-nesting bird’. Can. J. Zool. 90, 1359–1360 (2012).

    Google Scholar 

  21. 21.

    Troscianko, J., Wilson-Aggarwal, J., Stevens, M. & Spottiswoode, C. N. Camouflage predicts survival in ground-nesting birds. Sci. Rep. 6, 19966 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  22. 22.

    McKinnon, L. et al. Lower predation risk for migratory birds at higher latitudes. Science 237, 326–327 (2010).

    Google Scholar 

  23. 23.

    Kubelka, V. et al. Global pattern of nest predation is disrupted by climate change in shorebirds. Science 362, 680–683 (2018).

    CAS  PubMed  Google Scholar 

  24. 24.

    Remeš, V., Matysioková, B. & Cockburn, A. Long-term and large-scale analyses of nest predation patterns in Australian songbirds and a global comparison of nest predation rates. J. Avian Biol. 43, 435–444 (2012).

    Google Scholar 

  25. 25.

    Mayani-Parás, F., Kilner, R. M., Stoddard, M. C., Rodríguez, C. & Drummond, H. Behaviorally induced camouflage: a new mechanism of avian egg protection. Am. Nat. 186, E91–E97 (2015).

    PubMed  Google Scholar 

  26. 26.

    Ishikawa, S. et al. Photodynamic antimicrobial activity of avian eggshell pigments. FEBS Lett. 584, 770–774 (2010).

    CAS  PubMed  Google Scholar 

  27. 27.

    Ruiz-de-Castañeda, R., Vela, A. I., Lobato, E., Briones, V. & Moreno, J. Bacterial loads on eggshells of the pied flycatcher: environmental and maternal factors. Condor 113, 200–208 (2011).

    Google Scholar 

  28. 28.

    D’Alba, L. & Shawkey, M. D. Mechanisms of antimicrobial defense in avian eggs. J. Ornithol. 156, 399–408 (2015).

    Google Scholar 

  29. 29.

    M’Aldowie, A. M. Observations on the development and the decay of the pigment layer in birds’ eggs. J. Anat. Physiol. 20, 225–237 (1886).

    Google Scholar 

  30. 30.

    Inomata, K. et al. Sterically locked synthetic bilin derivatives and phytochrome Agp1 from Agrobacterium tumefaciens form photoinsensitive Pr- and Pfr-like adducts. J. Biol. Chem. 280, 24491–24497 (2005).

    CAS  PubMed  Google Scholar 

  31. 31.

    BirdLife International & NatureServe Bird Species Distribution Maps of the World version 5.0 (BirdLife International & NatureServe, 2015).

  32. 32.

    Gaston, K. J., Chown, S. L. & Evans, K. L. Ecogeographical rules: elements of a synthesis. J. Biogeogr. 35, 483–500 (2008).

    Google Scholar 

  33. 33.

    Losos, J. B. Uncertainty in the reconstruction of ancestral character states and limitations on the use of phylogenetic comparative methods. Anim. Behav. 58, 1319–1324 (1999).

    CAS  PubMed  Google Scholar 

  34. 34.

    Beckmann, M. et al. glUV: a global UV-B radiation data set for macroecological studies. Methods Ecol. Evol. 5, 372–383 (2014).

    Google Scholar 

  35. 35.

    Maurer, G. et al. First light for avian embryos: eggshell thickness and pigmentation mediate variation in development and UV exposure in wild bird eggs. Funct. Ecol. 29, 209–218 (2015).

    Google Scholar 

  36. 36.

    Maurer, G., Portugal, S. J. & Cassey, P. Review: an embryo’s eye view of avian eggshell pigmentation. J. Avian Biol. 42, 494–504 (2011).

    Google Scholar 

  37. 37.

    Moreno, J. & Osorno, J. L. Avian egg colour and sexual selection: does eggshell pigmentation reflect female condition and genetic quality? Ecol. Lett. 6, 803–806 (2003).

    Google Scholar 

  38. 38.

    Gosler, A. G., Connor, O. R. & Bonser, R. H. C. Protoporphyrin and eggshell strength: preliminary findings from a passerine bird. Avian Biol. Res. 4, 214–223 (2011).

    Google Scholar 

  39. 39.

    Yang, C. et al. Keeping eggs warm: thermal and developmental advantages for parasitic cuckoos of laying unusually thick-shelled eggs. Naturwissenschaften 105, 10 (2018).

    PubMed  Google Scholar 

  40. 40.

    Davies, N. B. & de Brooke, M. L. An experimental study of co-evolution between the cuckoo, Cuculus canorus, and its hosts. I. Host egg discrimination. J. Anim. Ecol. 58, 207–224 (1989).

    Google Scholar 

  41. 41.

    Yang, C., Liang, W., Møller, A. P. in Avian Brood Parasitism: Behaviour, Ecology, Evolution and Coevolution (ed. Soler, M.) 345–361 (Springer, 2017).

  42. 42.

    Yang, C. et al. Coevolution in action: disruptive selection on egg colour in an avian brood parasite and its host. PLoS ONE 5, e10816 (2010).

    PubMed  PubMed Central  Google Scholar 

  43. 43.

    Węgrzyn, E., Leniowski, K., Rykowska, I. & Wasiak, W. Is UV and blue-green egg colouration a signal in cavity-nesting birds? Ethol. Ecol. Evol. 23, 121–139 (2011).

    Google Scholar 

  44. 44.

    Wesołowski, T. & Maziarz, M. Dark tree cavities: a challenge for hole nesting birds? J. Avian Biol. 43, 454–460 (2012).

    Google Scholar 

  45. 45.

    Endler, J. A. The color of light in forests and its implications. Ecol. Monogr. 63, 1–27 (1993).

    Google Scholar 

  46. 46.

    Martin, T. E. et al. Enclosed nests may provide greater thermal than nest predation benefits compared with open nests across latitudes. Funct. Ecol. 31, 1231–1240 (2017).

    Google Scholar 

  47. 47.

    Godard, R. D., Wilson, C. M., Frick, J. W., Siegel, P. B. & Bowers, B. B. The effects of exposure and microbes on hatchability of eggs in open-cup and cavity nests. J. Avian Biol. 38, 709–716 (2007).

    Google Scholar 

  48. 48.

    von Haartman, L. Adaptation in hole-nesting birds. Evolution 11, 339–347 (1957).

    Google Scholar 

  49. 49.

    Holyoak, D. The function of the pale egg colour of the jackdaw. Bull. Br. Ornithol. Club 89, 159 (1969).

    Google Scholar 

  50. 50.

    Abercrombie, R. G. The colour of birds’ eggs. Naturalist 56, 105–108 (1931).

    Google Scholar 

  51. 51.

    Needham, A. E. The Significance of Zoochromes Vol. 3 (Springer, 1974).

  52. 52.

    Caro, T. The adaptive significance of coloration in mammals. BioScience 55, 125–136 (2005).

    Google Scholar 

  53. 53.

    Bakken, G. S., Vanderbilt, V. C., Buttermer, W. A. & Dawson, W. R. Avian eggs: thermoregulatory value of very high near-infrared reflectance. Science 200, 321–323 (1978).

    CAS  PubMed  PubMed Central  Google Scholar 

  54. 54.

    D’Alba, L. et al. What does the eggshell cuticle do? A functional comparison of avian eggshell cuticles. Physiol. Biochem. Zool. 90, 588–599 (2017).

    PubMed  Google Scholar 

  55. 55.

    Cassey, P. et al. Variability in avian eggshell colour: a comparative study of museum eggshells. PLoS ONE 5, e12054 (2010).

    PubMed  PubMed Central  Google Scholar 

  56. 56.

    Matysioková, B. & Remeš, V. Evolution of parental activity at the nest is shaped by the risk of nest predation and ambient temperature across bird species. Evolution 72, 2214–2224 (2018).

    PubMed  Google Scholar 

  57. 57.

    L’Herpiniere, K. L., O’Neill, L. G., Russell, A. F., Duursma, D. E. & Griffith, S. C. Unscrambling variation in avian eggshell colour and patterning in a continent-wide study. R. Soc. Open Sci. 6, 181269 (2019).

    PubMed  PubMed Central  Google Scholar 

  58. 58.

    Gómez, J. et al. Latitudinal variation in biophysical characteristics of avian eggshells to cope with differential effects of solar radiation. Ecol. Evol. 8, 8019–8029 (2018).

    PubMed  PubMed Central  Google Scholar 

  59. 59.

    Martin, T. E., Martin, P. R., Olson, C. R., Heidinger, B. J. & Fontaine, J. J. Parental care and clutch sizes in North and South American birds. Science 287, 1482–1485 (2000).

    CAS  PubMed  Google Scholar 

  60. 60.

    Martin, T. E., Scott, J. & Menge, C. Nest predation increases with parental activity: separating nest site and parental activity effects. Proc. Biol. Sci. 267, 2287–2293 (2000).

    CAS  PubMed  PubMed Central  Google Scholar 

  61. 61.

    Conway, C. J. & Martin, T. E. Evolution of passerine incubation behavior: influence of food, temperature, and nest predation. Evolution 54, 670–685 (2000).

    CAS  PubMed  Google Scholar 

  62. 62.

    Piersma, T. et al. High daily energy expenditure of incubating shorebirds on High Arctic tundra: a circumpolar study. Funct. Ecol. 17, 356–362 (2003).

    Google Scholar 

  63. 63.

    D’Alba, L., Monaghan, P. & Nager, R. G. Thermal benefits of nest shelter for incubating female eiders. J. Therm. Biol. 34, 93–99 (2009).

    Google Scholar 

  64. 64.

    Mallory, M. L., Gaston, A. J. & Gilchrist, H. G. Sources of breeding season mortality in Canadian arctic seabirds. Arctic 62, 333–341 (2009).

    Google Scholar 

  65. 65.

    Martin, T. E. A new view of avian life-history evolution tested on an incubation paradox. Proc. Biol. Sci. 269, 309–316 (2002).

    PubMed  PubMed Central  Google Scholar 

  66. 66.

    Ghalambor, C. K., Peluc, S. I. & Martin, T. E. Plasticity of parental care under the risk of predation: how much should parents reduce care? Biol. Lett. 9, 20130154 (2013).

    PubMed  PubMed Central  Google Scholar 

  67. 67.

    Martin, T. E. Age-related mortality explains life history strategies of tropical and temperate songbirds. Science 349, 966–970 (2015).

    CAS  PubMed  Google Scholar 

  68. 68.

    Gill, S. A. & Haggerty, T. M. A comparison of life-history and parental care in temperate and tropical wrens. J. Avian Biol. 43, 461–471 (2012).

    Google Scholar 

  69. 69.

    Martin, T. E. & Ghalambor, C. K. Males feeding females during incubation. I. Required by microclimate or constrained by nest predation? Am. Nat. 153, 131–139 (1999).

    PubMed  Google Scholar 

  70. 70.

    Roper, J. J. & Goldstein, R. R. A test of the Skutch hypothesis: does activity at nests increase nest predation risk? J. Avian Biol. 28, 111–116 (1997).

    Google Scholar 

  71. 71.

    Skutch, A. F. Parent Birds and Their Young (Corrie Herring Hooks Series 2, Univ. Texas Press, 1976).

  72. 72.

    Blanco, G. & Bertellotti, M. Differential predation by mammals and birds: implications for egg-colour polymorphism in a nomadic breeding seabird. Biol. J. Linn. Soc. Lond. 75, 137–146 (2002).

    Google Scholar 

  73. 73.

    Weidinger, K. Does egg colour affect predation rate on open passerine nests? Behav. Ecol. Sociobiol. 49, 456–464 (2001).

    Google Scholar 

  74. 74.

    Watt, W. B. Adaptive significance of pigment polymorphisms in Colias butterflies. I. Variation of melanin pigment in relation to thermoregulation. Evolution 22, 437–458 (1968).

    PubMed  Google Scholar 

  75. 75.

    Vleck, C. M., Vleck, D. & Hoyt, D. F. Patterns of metabolism and growth in avian embryos. Am. Zool. 20, 405–416 (1980).

    Google Scholar 

  76. 76.

    Hanley, D. & Grim, T. & Cassey, P. & Hauber, M. E. Not so colourful after all: eggshell pigments constrain avian eggshell colour space. Biol. Lett. 11, 20150087 (2015).

    PubMed  PubMed Central  Google Scholar 

  77. 77.

    Hanley, D., Cassey, P. & Doucet, S. M. Parents, predators, parasites, and the evolution of eggshell colour in open nesting birds. Evol. Ecol. 27, 593–617 (2013).

    Google Scholar 

  78. 78.

    Digital Chart of the World (Defense Mapping Agency, accessed 26 September 2019);

  79. 79.

    Kelso, N. V. & Patterson, T. Introducing Natural Earth data: Geogr. Tech. 5, 82–89 (2010).

    Google Scholar 

  80. 80.

    Fick, S. E. & Hijmans, R. J. WorldClim 2: new 1-km spatial resolution climate surfaces for global land areas. Int. J. Climatol. 37, 4302–4315 (2017).

    Google Scholar 

  81. 81.

    Lee-Taylor, J. & Madronich, S. Climatology of UV-A, UV-B, and Erythemal Radiation at the Earth’s Surface, 1979–2000 NCAR Technical Note TN-474-STR (NCAR, 2007).

  82. 82.

    Mitchell, T. D., Carter, T. R., Jones, P. D., Hulme, M. & New, M. A Comprehensive Set of High-Resolution Grids of Monthly Climate for Europe and the Globe: the Observed Record (1901–2000) and 16 Scenarios (2001–2100) Working Paper 55 (Tyndall Centre for Climate Change Research, 2004).

  83. 83.

    Hackett, S. J. et al. A phylogenomic study of birds reveals their evolutionary history. Science 320, 1763–1768 (2008).

    CAS  PubMed  Google Scholar 

  84. 84.

    Jetz, W., Thomas, G. H., Joy, J. B., Hartmann, K. & Mooers, A. O. The global diversity of birds in space and time. Nature 491, 444–448 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  85. 85.

    Sukumaran, J. & Holder, M. T. DendroPy: a Python library for phylogenetic computing. Bioinformatics 26, 1569–1571 (2010).

    CAS  PubMed  Google Scholar 

  86. 86.

    Pagel, M. Detecting correlated evolution on phylogenies: a general method for comparative analysis of discrete characters. Proc. R. Soc. Lond. B 255, 37–45 (1994).

    Google Scholar 

  87. 87.

    Anselin, L. & Bera, A. K. Spatial dependence in linear regression models with an introduction to spatial econometrics. Stat. Textb. Monogr. 155, 237–290 (1998).

    Google Scholar 

  88. 88.

    Anselin, L. Spatial Econometrics: Methods and Models (Kluwer Academic Publishers, 1988).

  89. 89.

    Elhorst, J., J. P. Spatial Econometrics: from Cross-Sectional Data to Spatial Panels (Springer, 2014).

  90. 90.

    Millo, G. & Piras, G. splm: spatial panel data models in R. J. Stat. Softw. 47, 1–38 (2012).

    Google Scholar 

  91. 91.

    Pagel, M. Inferring evolutionary processes from phylogenies. Zool. Scr. 26, 331–348 (1997).

    Google Scholar 

  92. 92.

    Freckleton, R. P., Harvey, P. H. & Pagel, M. Phylogenetic analysis and comparative data: a test and review of evidence. Am. Nat. 160, 712–726 (2002).

    CAS  PubMed  Google Scholar 

  93. 93.

    Burnham, K. P. & Anderson, D. R. Model Selection and Multimodel Inference: A Practical Information-Theoretic Approach 2nd edn (Springer, 2002).

  94. 94.

    Schindelin, J. et al. Fiji: an open-source platform for biological-image analysis. Nat. Methods 9, 676–682 (2012).

    CAS  Google Scholar 

  95. 95.

    Wisocki, P. A. et al. Dataset from Wisocki et al. 2019 Nature Ecology and Figshare (2019).

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We thank Long Island University for space and support for this project. We also thank K. Mendola, J. L. Cuthbert and K. Dalto for their assistance, and S. Tettelbach, M. C. Stoddard, S. Madronich, R. Bivand, C Brückner and T. E. Lewis for helpful comments. We thank M. E. Hauber for his assistance with securing funding to collect the eggshell spectra. Collection of the original dataset was partially funded by a Human Frontier Science Program ( Young Investigator grant (no. RGY0069/2007-C) and a Leverhulme Trust ( project grant (no. F/00 094/AX) to P.C. and M. E. Hauber.

Author information




D.H. developed the concept. D.H. and P.C. collected the data. D.H. and I.R.R. conducted the colour analyses. P.A.W., P.K., M.L.B. and D.H. developed and implemented the ecogeographical models. P.A.W. and D.H. conducted the fieldwork. P.A.W. and D.H. prepared the initial draft and all authors edited the paper.

Corresponding author

Correspondence to Daniel Hanley.

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The authors declare no competing interests.

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Extended data

Extended Data Fig. 1 Global variation in environmental variables.

Global variation in the environmental variables across all locales examined in this study (n= 6,692). The first two principal components explained 91% of the variance, where b, temperature and c, UVB radiance loaded positively on PC1 with d, precipitation and e, humidity loading less strongly (loadings: temperature= 0.65, UVB = 0.65, humidity = −0.22, precipitation = −0.32). By contrast, f, temperature and g, UVB radiance loaded less strongly on PC2 while, h, precipitation and i, humidity loaded negatively (loadings: temperature= −0.04, UVB = 0.13, humidity = −0.73, precipitation = −0.67). Here we illustrate a, the discordance and congruence among within PC scores representing environmental variation using a colour scheme (see key). Locales that are relatively cold and humid are shown in darker blue, locales that are relative hot and humid are shown in red, locales that are cold and dry are relatively light blue, and places that are hot and dry (arid) are shown in yellow. We use this colour scheme in Fig. 3 as well as Extended Data Figs. 2 and 6 to aid interpretation.

Extended Data Fig. 2 Variation in eggshell appearance by nest types.

The fitted values from linear models (solid lines) predicting a, brightness and b, colour by solar intensity (PC1), along with their 95% confidence intervals (dashed lines). From top to bottom the fitted lines represent cavity, cup, and ground nesting birds. The colours of dots represent environmental conditions at each locale (n= 6,992; see Extended Data Fig. 1 for definition of colour scheme).

Extended Data Fig. 3 Parameter estimates from phylogenetic generalized least squares analyses.

Models predicting brightness and colour, by solar intensity (PC1), aridity (PC2), nest type, and interactions between nest type and aridity. When interactions were non-significant (for example, interactions with solar intensity) they were removed and the models rerun without the interaction (see Methods). We report Pagel’s lambda (λML) and AICc for each analysis. We report, standardized beta (β), standard error (s.e.m.), a t-value, and significance for each parameter. The effects of all parameters are made with reference to the eggs of ground nesting birds. See Methods for further details.

Extended Data Fig. 4 Influence of avian groups on PGLS analysis.

For models predicting a, brightness and b, colour we explored the influence of individual species by performing a jack-knife procedure, running the each analysis repeatedly, each time removing a different species. We plot the scaled log likelihood values of those analyses by their taxonomic order, and constructed a ‘conservative’ models removing all species from orders that may drive the detected patterns (that is, ≤2 s.d. from the mean). The full models explained the data better than the conservative models for both a, brightness (ΔAICc = 7.65, evidence ratio = 45.74) and b, colour (ΔAICc = 6.75, evidence ratio = 29.23). For both models the direction and significance for all parameters was the same; therefore, the full models are presented in the Main text. See Methods for further details.

Extended Data Fig. 5 Heating and cooling rates of eggs.

To complement the patterns reported in the main paper, we added mean ( ± s.e.m.) differential heating for duck (square) and quail (small dots) eggs alongside chicken eggs (circles), in a randomized order for each trial. Although neither duck (inter-quartile range = 0.19 s.d.) nor quail (inter-quartile range = 0.48 s.d.) has the variation in eggshell ground brightness corresponding with the chicken (inter-quartile range = 2.22 s.d.) they should fall roughly along the same line as chicken eggs with respect to their rate of heating and cooling, relative to white chicken eggs (see Methods). These represent trials where eggs were a-b, exposed to direct solar radiation while at incubation temperature and where eggs were c-d, exposed to direct solar radiation while maintained at ambient temperature (see Methods). Here we plot the rates of cooling for these additional species alongside the data plotted in Fig. 5. Including these data within the same model produced nearly identical parameter estimates, significances, and predicted rates of heating and cooling. In addition, we plot the b,d, standardized residuals by their fitted values highlighting residuals above or below 2 s.d. The majority of these data fit within these bounds suggesting that despite limit variation in brightness the rate of heating and cooling of these eggs roughly corresponds with those measured for the chicken.

Extended Data Fig. 6 Comparison between environmental and predation.

A plot of eggshell a, brightness and colour c, versus solar intensity and b,d, historic total nest predation rate using publicly available data from a previously published source23. We show the relationship between brightness and a, solar intensity (PC1) and b, predation pressure where data were available such that all locales had a spatial neighbour (n = 6,326). All variables were centred and scaled to aid interpretation. Additionally, we present the relationship between colour and c, solar intensity (PC1) and predation pressure. If predation pressure was driving eggshell phenotypes we would expect the darkest brownest eggshells where predation was highest; however, the opposite pattern is present and significant for predation (brightness: β = 0.32, CI = 0.19 to 0.46, p < 0.0001; colour: β = 0.21, CI = 0.08 to 0.34, p = 0.002). Please note these predation data apply to shorebirds, and future research should determine if clinal variation in predation applies to all birds. Environmental variables fit data on eggshell brightness (∆AICc = 74.8; evidence ratio > 1,000) and colour (∆AICc = 111.9; evidence ratio > 1,000) provided a better fit for the data than predation. The colours of the plotted points relate to their relative values of PC1 and PC2 (see Extended Data Fig. 1 for details).

Extended Data Fig. 7 Relationship between colour and brightness and their avian perceived equivalent scores.

The relationship between a, eggshell brightness (mean brightness) and egg species’ calculated perceived luminance. In addition, present the relationship between b, eggshell colour (representing blue-green chroma) and each species’ egg colour coordinate within the tetrahedral colour space. All eggs vary from blue-green to brown within this avian perceptual colour space and here we compare variation across the x-axis (corresponding with this axis of variation) within that space and our estimate of colour. These avian visual models corresponding with either the average ultraviolet sensitive receiver (black dots) or the average violet sensitive receiver (grey dots). For the average ultraviolet-sensitive receiver, we used photoreceptor sensitivity estimates for the average ultraviolet-sensitive receiver under idealized illumination, and using the blue-tit Cyanistes caeruleus double cone catch to estimate luminance. For the average violet-sensitive receiver, we used photoreceptor sensitivity estimates for the average violet sensitive receiver and double cone catch estimates for the chicken Gallus gallus to estimate luminance, under idealized conditions. Avian eggshell brightness was highly correlated with avian perceived eggshell luminance (UVS: β = 0.98, CI = 0.98 to 0.99, p < 0.0001, λML = 0.82; VS: β = 0.98, CI = 0.971 to 0.99, p < 0.0001; λML = 0.83) and eggshell colours were also were highly correlated with avian perceived variation in colour (UVS: β = −0.77, CI = −0.80 to −0.73, p < 0.0001, λML = 0.84: VS: β = −0.85, CI = −0.88 to −0.82, p < 0.0001, λML = 0.83).

Extended Data Fig. 8 Sampling bias.

To consider the possibility that our findings are impacted by an overabundance of some nest types in certain places (for example, only ground nesting birds above a certain latitude) or poor sampling overall, we report the relative proportion of birds of a given nest type across space and run an analysis. First, a, across 5-degree latitudinal bins, we report the b, percentage of birds with each nest type (ground = black, cup = red, dome = dark blue, cavity = light blue, mound = yellow). Values falling above 95% are areas where our ability to infer is limited, in our case we sampled relatively few samples in Antarctica. Therefore, to determine whether our sampled species richness (richness) in each locale was poor relative to total avian richness (that is, species in BirdLife International) within that same locale, we examined c, the relationship between richness and total avian richness. Sampling effort d, plateaued as a function of specimen availability (that is, limit of samples), but was c, predicted by total species richness (F2,33 = 74.67, R2 = 0.82, p < 0.0001). We had relatively c-e, higher sampling effort in the northern temperate region (~30 to 60°N) and relatively lower sampling effort in the southern sub-tropical region (approximately −15 to −40°S). This is illustrated in a plot of c, of predicted richness and sampled richness as well as d, the relationship between total and sampled avian richness. In both plots points are coloured by their latitude (a gradation of colours from South Pole as red to the North Pole as yellow). Although the Northern Hemisphere was well sampled, the e, residuals from this model were all less than one standard deviation, indicating that no region was sampled so much, or so little, to be considered an outlier.

Extended Data Fig. 9 Internal and external relationship.

Eggshell external surface temperatures were related to their internal temperatures. Dark brown (filled dots, n = 12) and white (open dots, n = 12) eggs were left under natural ambient light conditions (26-30 °C; see Methods for details).

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Wisocki, P.A., Kennelly, P., Rojas Rivera, I. et al. The global distribution of avian eggshell colours suggest a thermoregulatory benefit of darker pigmentation. Nat Ecol Evol 4, 148–155 (2020).

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