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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The BirdLife International species distribution data can be requested at http://datazone.birdlife.org/species/requestdis. The Digital Chart of the World basemap can be accessed at https://worldmap.harvard.edu/data/geonode:Digital_Chart_of_the_World. The Natural Earth Data maps can be found at www.naturalearthdata.com/. The Worldclim v.2 temperature data are available at http://worldclim.org/version2. The National Center for Atmospheric Research UV data can be found at www2.acom.ucar.edu/modeling/tuv-download. The Atlas of the Biosphere humidity data can be found at https://nelson.wisc.edu/sage/data-and-models/maps.php. The ISEA global grid data can be found at https://cran.r-project.org/web/packages/dggridR/vignettes/dggridR.html for the R codes or www.arcgis.com/home/item.html?id=38e3e0453e4040c69ff5e9fde306c12c for the shapefiles. Data generated and/or analysed during this study are available from the figshare digital repository95 (https://doi.org/10.6084/m9.figshare.9745109).
The R script used for the statistical analysis is available upon request.
Clusella Trullas, S., van Wyk, J. H. & Spotila, J. R. Thermal melanism in ectotherms. J. Therm. Biol. 32, 235–245 (2007).
Pinkert, S. & Zeuss, D. Thermal biology: melanin-based energy harvesting across the tree of life. Curr. Biol. 28, R887–R889 (2018).
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).
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).
Abram, P. K. et al. An insect with selective control of egg coloration. Curr. Biol. 25, 2007–2011 (2015).
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).
Kilner, R. M. The evolution of egg colour and patterning in birds. Biol. Rev. Camb. Phil. Soc. 81, 383–406 (2006).
Webb, D. R. Thermal tolerance of avian embryos: a review. Condor 89, 874–898 (1987).
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).
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).
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).
Gómez, J. et al. A trade-off between overheating and camouflage on shorebird eggshell colouration. J. Avian Biol. 47, 346–353 (2016).
Westmoreland, D. Evidence of selection for egg crypsis in conspicuous nests. J. Field Ornithol. 79, 263–268 (2008).
Westmoreland, D. & Best, L. B. Incubation continuity and the advantage of cryptic egg coloration to mourning doves. Wilson Bull. 98, 297–300 (1986).
Verbeek, N. A. M. Differental predation on eggs in clutches of northwestern crows: the importance of egg color. Condor 92, 695–701 (1990).
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).
Yahner, R. H. & Mahan, C. G. Effects of egg type on depredation of artificial ground nests. Wilson Bull. 108, 129–136 (1996).
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).
Westmoreland, D., Schmitz, M. & Burns, K. E. Egg color as an adaptation for thermoregulation. J. Field Ornithol. 78, 176–183 (2007).
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).
Troscianko, J., Wilson-Aggarwal, J., Stevens, M. & Spottiswoode, C. N. Camouflage predicts survival in ground-nesting birds. Sci. Rep. 6, 19966 (2016).
McKinnon, L. et al. Lower predation risk for migratory birds at higher latitudes. Science 237, 326–327 (2010).
Kubelka, V. et al. Global pattern of nest predation is disrupted by climate change in shorebirds. Science 362, 680–683 (2018).
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).
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).
Ishikawa, S. et al. Photodynamic antimicrobial activity of avian eggshell pigments. FEBS Lett. 584, 770–774 (2010).
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).
D’Alba, L. & Shawkey, M. D. Mechanisms of antimicrobial defense in avian eggs. J. Ornithol. 156, 399–408 (2015).
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).
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).
BirdLife International & NatureServe Bird Species Distribution Maps of the World version 5.0 (BirdLife International & NatureServe, 2015).
Gaston, K. J., Chown, S. L. & Evans, K. L. Ecogeographical rules: elements of a synthesis. J. Biogeogr. 35, 483–500 (2008).
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).
Beckmann, M. et al. glUV: a global UV-B radiation data set for macroecological studies. Methods Ecol. Evol. 5, 372–383 (2014).
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).
Maurer, G., Portugal, S. J. & Cassey, P. Review: an embryo’s eye view of avian eggshell pigmentation. J. Avian Biol. 42, 494–504 (2011).
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).
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).
Yang, C. et al. Keeping eggs warm: thermal and developmental advantages for parasitic cuckoos of laying unusually thick-shelled eggs. Naturwissenschaften 105, 10 (2018).
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).
Yang, C., Liang, W., Møller, A. P. in Avian Brood Parasitism: Behaviour, Ecology, Evolution and Coevolution (ed. Soler, M.) 345–361 (Springer, 2017).
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).
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).
Wesołowski, T. & Maziarz, M. Dark tree cavities: a challenge for hole nesting birds? J. Avian Biol. 43, 454–460 (2012).
Endler, J. A. The color of light in forests and its implications. Ecol. Monogr. 63, 1–27 (1993).
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).
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).
von Haartman, L. Adaptation in hole-nesting birds. Evolution 11, 339–347 (1957).
Holyoak, D. The function of the pale egg colour of the jackdaw. Bull. Br. Ornithol. Club 89, 159 (1969).
Abercrombie, R. G. The colour of birds’ eggs. Naturalist 56, 105–108 (1931).
Needham, A. E. The Significance of Zoochromes Vol. 3 (Springer, 1974).
Caro, T. The adaptive significance of coloration in mammals. BioScience 55, 125–136 (2005).
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).
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).
Cassey, P. et al. Variability in avian eggshell colour: a comparative study of museum eggshells. PLoS ONE 5, e12054 (2010).
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).
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).
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).
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).
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).
Conway, C. J. & Martin, T. E. Evolution of passerine incubation behavior: influence of food, temperature, and nest predation. Evolution 54, 670–685 (2000).
Piersma, T. et al. High daily energy expenditure of incubating shorebirds on High Arctic tundra: a circumpolar study. Funct. Ecol. 17, 356–362 (2003).
D’Alba, L., Monaghan, P. & Nager, R. G. Thermal benefits of nest shelter for incubating female eiders. J. Therm. Biol. 34, 93–99 (2009).
Mallory, M. L., Gaston, A. J. & Gilchrist, H. G. Sources of breeding season mortality in Canadian arctic seabirds. Arctic 62, 333–341 (2009).
Martin, T. E. A new view of avian life-history evolution tested on an incubation paradox. Proc. Biol. Sci. 269, 309–316 (2002).
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).
Martin, T. E. Age-related mortality explains life history strategies of tropical and temperate songbirds. Science 349, 966–970 (2015).
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).
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).
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).
Skutch, A. F. Parent Birds and Their Young (Corrie Herring Hooks Series 2, Univ. Texas Press, 1976).
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).
Weidinger, K. Does egg colour affect predation rate on open passerine nests? Behav. Ecol. Sociobiol. 49, 456–464 (2001).
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).
Vleck, C. M., Vleck, D. & Hoyt, D. F. Patterns of metabolism and growth in avian embryos. Am. Zool. 20, 405–416 (1980).
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).
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).
Digital Chart of the World (Defense Mapping Agency, accessed 26 September 2019); https://worldmap.harvard.edu/data/geonode:Digital_Chart_of_the_World
Kelso, N. V. & Patterson, T. Introducing Natural Earth data: naturalearthdata.com. Geogr. Tech. 5, 82–89 (2010).
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).
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).
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).
Hackett, S. J. et al. A phylogenomic study of birds reveals their evolutionary history. Science 320, 1763–1768 (2008).
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).
Sukumaran, J. & Holder, M. T. DendroPy: a Python library for phylogenetic computing. Bioinformatics 26, 1569–1571 (2010).
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).
Anselin, L. & Bera, A. K. Spatial dependence in linear regression models with an introduction to spatial econometrics. Stat. Textb. Monogr. 155, 237–290 (1998).
Anselin, L. Spatial Econometrics: Methods and Models (Kluwer Academic Publishers, 1988).
Elhorst, J., J. P. Spatial Econometrics: from Cross-Sectional Data to Spatial Panels (Springer, 2014).
Millo, G. & Piras, G. splm: spatial panel data models in R. J. Stat. Softw. 47, 1–38 (2012).
Pagel, M. Inferring evolutionary processes from phylogenies. Zool. Scr. 26, 331–348 (1997).
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).
Burnham, K. P. & Anderson, D. R. Model Selection and Multimodel Inference: A Practical Information-Theoretic Approach 2nd edn (Springer, 2002).
Schindelin, J. et al. Fiji: an open-source platform for biological-image analysis. Nat. Methods 9, 676–682 (2012).
Wisocki, P. A. et al. Dataset from Wisocki et al. 2019 Nature Ecology and Evolution.zip. Figshare https://doi.org/10.6084/m9.figshare.9745109 (2019).
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 (www.hfsp.org/) Young Investigator grant (no. RGY0069/2007-C) and a Leverhulme Trust (www.leverhulme.ac.uk/) project grant (no. F/00 094/AX) to P.C. and M. E. Hauber.
The authors declare no competing interests.
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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.
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).
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.
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.
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.
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).
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.
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). https://doi.org/10.1038/s41559-019-1003-2
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