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

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Abstract

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 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).

Code availability

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

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Acknowledgements

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.

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.

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 (2019) doi:10.1038/s41559-019-1003-2

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