SUPPLEMENTARY METHODS

Field methods at Mornington Wildlife Sanctuary, Western Australia

Methods were similar to those at other sites. However, nests were not inspected, and therefore cuckoos were not detected, until nestlings reached banding age (~ 6 days old). Two cuckoo nestlings were found after the appearance of pin feathers – reflectance measurements were made on the patches of bare skin between the feather tracts. Spectral reflectance was quantified in the field using an AvaSpec-2048 spectrophotometer, connected to a Xenon-pulsed-lamp (Avalight-XE) and a bifurcated fibre optic probe. The probe, with a matte black plastic cylinder at the tip to standardise measuring distance and exclude ambient light, was placed perpendicular to the surface, hence illumination and recording angles were both 90o (coincident normal). Reflectance was computed relative to a WS-2 white standard using the program Avasoft 6.2.1 (all Avantes, The Netherlands). This data is presented in Fig. 1, but was not used in the visual modelling analyses due to the incompatible methodology used in the spectrophotometric measurements.

Visual modelling

We first calculated the predicted photon catches for the four single cones (used in colour vision in birds) [1] and the double cones (used in luminance vision) [2] using the visual sensitivity of a blue tit Cyanistes caeruleus [3]. Visual sensitivity data is not available for the host species in this study, although research indicates that higher passerines vary little in their spectral sensitivity, even across distantly related species occupying different light environments [1,4]. However, we also repeated all the photon catch modelling using the spectral sensitivity of the zebra finch Taeniopygia guttata[5], which is not only distantly related to the blue tit, but is also found in a different light environment. Furthermore, because some passerines have an ultraviolet cone type shifted towards longer wavelengths (a ‘violet’ system) [1], we repeated the modelling with this kind of system using spectral sensitivity data of the peafowl Pavo cristatus [6]. Because we had irradiance spectra only for yellow-rumped thornbill nests, we also repeated the photon catch modelling with four different irradiance spectra types (yellow-rumped thornbill nests, blue sky, forest shade, and a standard daylight D65 spectrum). There was little difference between the blue tit and zebra finch visual systems on the photon catches (mean difference and standard deviation: ultraviolet sensitive = 0.05 +/- 0.04; shortwave sensitive = 0.02 +/- 0.02; mediumwave sensitive = 0.01 +/- 0.01; longwave sensitive < 0.01 +/- 0.01). There was also minimal effect of irradiance spectra (< 0.01 change in photon catch values for all cone types between all four light spectra types). Therefore, we conducted the discrimination modelling using photon catches based on the blue tit and peafowl visual systems and a D65 irradiance spectrum. The output from analyses based on the peafowl visual system are presented above (Table S1).

The ‘standard’ Vorobyev-Osorio [7] discrimination model used by most studies assumes that receptor noise is proportional to signal intensity, and the contrast between two signals is constant and independent of light intensity (Weber’s law) [8]. However, this is only true at high light levels, and the nests of the host species in this study are quite dark [9]. In dark conditions, noise also arises due to variations in photon catches (see [8] for further information). Therefore, we model discrimination contrasts incorporating both high light level noise (using a Weber fraction of 0.05 for the most abundant cone type) and low light level photon noise (see [9] for further details).For chromatic comparisons we use the photon catches of the single cones, with retinal cone proportions of the blue tit (longwave = 1.00, mediumwave = 0.99, shortwave = 0.71, and ultraviolet sensitive = 0.37)[5]. For the luminance comparisons, we use the double cones (as [10]). (See [7,9] and references therein for the full equations).

Supplementary References

1Cuthill I. C. 2006 Color perception. In: Bird Coloration, Vol. 1: Mechanisms and Measurements (eds. Hill G. E. & McGraw K. J.). Cambridge, Massachusetts: Harvard University Press.

2Osorio D. & Vorobyev M. 2005 Photoreceptor spectral sensitivities in terrestrial animals: adaptations for luminance and colour vision. Proc. R. Soc. B272, 1745-1752.

3Hart N. S., Partridge J. C., Cuthill I. C. & Bennett A. T. D. 2000b Visual pigments, oil droplets, ocular media and cone photoreceptor distribution in two species of passerine: the blue tit (Parus caeruleus L.) and the blackbird (Turdus merula L.). J. Comp. Physiol. A, 186, 375-387.

4Ödeen A. & Håstad O. 2003 Complex distribution of avian color vision systems revealed by sequencing the SWS1 opsin from total DNA. Mol. Biol. Evol.20, 855-861.

5Hart N. S., Partridge J. C., Bennett A. T. D. & Cuthill I. C. 2000a Visual pigments, cone oil droplets and ocular media in four species of estrildid finch. J. Comp. Physiol. A186, 681-694.

6Hart N. S. 2002 Vision in the peafowl (Aves: Pavo cristatus). J. Exp. Biol.205, 3925-3935.

7Vorobyev M. & Osorio D. 1998 Receptor noise as a determinant of colour thresholds. Proc. R. Soc. B265, 351-358.

8Osorio D., Smith A. C., Vorobyev M. & Buchanan-Smith H. M. 2004 Detection of fruit and the selection of primate visual pigments for color vision. Am. Nat. 164, 696-708.

9Langmore N. E., Stevens M., Maurer G. & Kilner R. M. 2009 Are dark cuckoo eggs cryptic in host nests? Anim. Behav.78, 461-468.

10Siddiqi A., Cronin T. W., Loew E. R., Vorobyev M. & Summers K. 2004 Interspecific and intraspecific views of color signals in the strawberry poison frog Dendrobates pumilio. J. Exp. Biol.207, 2471-2485.

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