Colour vision and background adaptation in a passerine bird, the zebra finch (
            <i>Taeniopygia guttata</i>
            )

Lind, Olle

doi:10.1098/rsos.160383

Cited by 41 publications

(52 citation statements)

References 39 publications

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“…Further complicating matters, ambient illumination almost certainly affects discrimination thresholds but these effects have never been behaviourally tested [56]. Discrimination thresholds may be higher when the patch being evaluated matches the background [57], which would be the case in our achromatic contrast calculations below a depth of approximately 10 m.…”

Section: Discussionmentioning

confidence: 99%

Red fluorescence of the triplefinTripterygion delaisiis increasingly visible against background light with increasing depth

et al. 2017

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The light environment in water bodies changes with depth due to the absorption of short and long wavelengths. Below 10 m depth, red wavelengths are almost completely absent rendering any red-reflecting animal dark and achromatic. However, fluorescence may produce red coloration even when red light is not available for reflection. A large number of marine taxa including over 270 fish species are known to produce red fluorescence, yet it is unclear under which natural light environment fluorescence contributes perceptively to their colours. To address this question we: (i) characterized the visual system of Tripterygion delaisi, which possesses fluorescent irides, (ii) separated the colour of the irides into its reflectance and fluorescence components and (iii) combined these data with field measurements of the ambient light environment to calculate depth-dependent perceptual chromatic and achromatic contrasts using visual modelling. We found that triplefins have cones with at least three different spectral sensitivities, including differences between the two members of the double cones, giving them the potential for trichromatic colour vision. We also show that fluorescence contributes increasingly to the radiance of the irides with increasing depth. Our results support the potential functionality of red fluorescence, including communicative roles such as species and sex identity, and non-communicative roles such as camouflage.

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Section: Discussionmentioning

confidence: 99%

Red fluorescence of the triplefinTripterygion delaisiis increasingly visible against background light with increasing depth

et al. 2017

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“…For zebra finches, for instance, the same pair of similar red objects have a discriminability threshold of ca. 1 JND when the background is red, but much higher when the background is green (Lind, ). Furthermore, the relationship between ΔS values and probability of discriminability varies between species and it is not necessarily linear, in particular for ΔS values that greatly surpass threshold values (Garcia, Spaethe, & Dyer, ).…”

Section: Guidelines and Limitationsmentioning

confidence: 99%

Section: Third Simulation: Achromatic Stimulus and Chromatic Backgrmentioning

confidence: 99%

Color vision models: Some simulations, a general n‐dimensional model, and the colourvision R package

Gawryszewski

2018

Ecology and Evolution

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The development of color vision models has allowed the appraisal of color vision independent of the human experience. These models are now widely used in ecology and evolution studies. However, in common scenarios of color measurement, color vision models may generate spurious results. Here I present a guide to color vision modeling (Chittka (1992, Journal of Comparative Physiology A, 170, 545) color hexagon, Endler & Mielke (2005, Journal Of The Linnean Society, 86, 405) model, and the linear and log‐linear receptor noise limited models (Vorobyev & Osorio 1998, Proceedings of the Royal Society B, 265, 351; Vorobyev et al. 1998, Journal of Comparative Physiology A, 183, 621)) using a series of simulations, present a unified framework that extends and generalize current models, and provide an R package to facilitate the use of color vision models. When the specific requirements of each model are met, between‐model results are qualitatively and quantitatively similar. However, under many common scenarios of color measurements, models may generate spurious values. For instance, models that log‐transform data and use relative photoreceptor outputs are prone to generate spurious outputs when the stimulus photon catch is smaller than the background photon catch; and models may generate unrealistic predictions when the background is chromatic (e.g. leaf reflectance) and the stimulus is an achromatic low reflectance spectrum. Nonetheless, despite differences, all three models are founded on a similar set of assumptions. Based on that, I provide a new formulation that accommodates and extends models to any number of photoreceptor types, offers flexibility to build user‐defined models, and allows users to easily adjust chromaticity diagram sizes to account for changes when using different number of photoreceptors.

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“…For zebra 453 finches, for instance, the same pair of similar red object have a discriminability threshold of ca. 1 454 JND when the background is red, but much higher when the background is green (Lind 2016). 455…”

mentioning

confidence: 98%

Colour vision models: a practical guide, some simulations, and colourvision R package

Gawryszewski

2017

Preprint

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17• Human colour vision differs from the vision of other animals. The most obvious 18 differences are the number and type of photoreceptors in the retina. E.g., while humans are 19 insensitive to ultraviolet (UV) light, most non-mammal vertebrates and insects have a colour 20 vision that spans into the UV. The development of colour vision models allowed appraisals of 21 colour vision independent of the human experience. These models are now widespread in 22 ecology and evolution fields. Here I present a guide to colour vision modelling, run a series of 23 simulations, and provide a R package -colourvision -to facilitate the use of colour vision 24 models. 25• I present the mathematical steps for calculation of the most commonly used colour vision (1998) linear and log-linear receptor noise limited models (RNL). These models are then tested 28 using identical simulated and real data. These comprise of reflectance spectra generated by a 29 logistic function against an achromatic background, achromatic reflectance against an 30 27, 2017; achromatic background, achromatic reflectance against a chromatic background, and real flower 31 reflectance data against a natural background reflectance. 32ND 4.0 International license peer-reviewed) is the author/funder. It is made available under a The copyright holder for this preprint (which was not . http://dx.doi.org/10.1101/103754 doi: bioRxiv preprint first posted online Jan.• When the specific requirements of each model are met, between model results are, 33 overall, qualitatively and quantitatively similar. However, under many common scenarios of 34 colour measurements, models may generate spurious values and/or considerably different 35 predictions. Models that log-transform data and use relative photoreceptor outputs are prone to 36 generate unrealistic results when the stimulus photon catch is smaller than the background 37 photon catch. Moreover, models may generate unrealistic results when the background is 38 chromatic (e.g. leaf reflectance) and the stimulus is an achromatic low reflectance spectrum. 39• Colour vision models are a valuable tool in several ecology and evolution subfields.

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Colour vision and background adaptation in a passerine bird, the zebra finch ( Taeniopygia guttata )

Cited by 41 publications

References 39 publications

Red fluorescence of the triplefinTripterygion delaisiis increasingly visible against background light with increasing depth

Red fluorescence of the triplefinTripterygion delaisiis increasingly visible against background light with increasing depth

Color vision models: Some simulations, a general n‐dimensional model, and the colourvision R package

Colour vision models: a practical guide, some simulations, and colourvision R package

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