592 Naturwissenschaften 86, 592–594 (1999) Q Springer-Verlag 1999

Do “White” and “Green” Look the Same to a Bee?

M. Vorobyev (Y), N. Hempel de Ibarra, R. Brandt, M. GiurfaInstitut für Neurobiologie, Freie Universität Berlin, Königin-Luise-Strasse 28–30, D-14195 Berlin, Germanye-mail: Vorobyev6zedat.fu-berlin.de, Tel.: c49-30-8386441, Fax: c49-30-838-5455

Received: 22 March 1999 / Accepted in revised form: 2 July 1999

Abstract The hexagon model of color vision pre-dicts that white flowers which reflect ultraviolet lightresemble green foliage to a bee’s eye, whereas, ac-cording to other models of the bee color vision, UV-reflecting white is discriminable from foliage green.The hexagon model is widely used in ecologicallyand evolutionary oriented literature, and the pre-dicted similarity between white and green has beenrecently presented as a well established fact (Waserand Chittka 1998). We show that bees detect UV-reflecting white objects presented on a green back-ground, a finding that is in disagreement with thepredictions of the hexagon model.

The question of how flower colors look in the eyesof a potential pollinator is central for understandingthe evolution of flower colors and has practical con-sequences in horticulture. Flowers that are difficultto detect against their background are likely to at-tract only few pollinators and are therefore selectedagainst. According to the hexagon model of the beecolor space (Chittka 1992), UV-reflecting white andgreen of leaves occupy color loci that are very closeto each other, and thus they must look similar(Chittka et al. 1994). The alleged similarity betweenwhite and green has been widely advertised to eco-logists, and it has been suggested that UV-reflectingwhite flowers are scarce because pollinators fail todetect them (Kevan et al. 1996). Furthermore, Was-er and Chittka (1998) have recently suggested thatwhite mutants of the snapdragon Antirrhinum majusproduce less fruit than do the violet wild-type plantsbecause flower white is perceived to be similar toleaf green by insect pollinators.Since the reflectance spectra of green leaves differsubstantially from white in both shape and averagereflectance (Fig. 1a), it is difficult to imagine that in-sects such as bees – with well developed color vision– cannot discriminate between these two colors.

Honeybee color vision has been extensively studied(for review see Menzel and Backhaus 1991) and sev-eral models have been proposed to describe it (forreview see Vorobyev and Brandt 1997). All modelsassume that bees use only chromatic cues for colordiscrimination, whereas achromatic cues are ignored(for review see Vorobyev and Brandt 1997). Chro-matic vision, which is mediated by color opponentinteractions between the receptors, is by definitionsensitive to changes in the shape of the stimulus’spectrum but not to changes in intensity of the lightstimulus. Because bees possess three spectral typesof photoreceptors (Autrum and Zwell 1964; Menzeland Blakers 1976) the receptor signals may combine,forming two independent color opponent mecha-nisms. These mechanisms define a two-dimensionalcolor opponent space (Backhaus 1991). Detectabili-ty of a colored object against a differently coloredbackground is predicted by the distance, DS, be-tween the chromatic loci of the two colors in the an-imal’s color space; the larger the distance, the betterthe detectability is. The distance in turn increaseswith increasing of the signal-to-noise ratio (SNR) ofchromatic mechanisms, which is generally a functionof the intensity of the light stimulus.The models of the bee vision can be classified ac-cording to the postulated dependence of the SNRon the light intensity, which may remain invariant,decrease, or increase. For example, a color-trianglemodel (Wyscecki and Stiles 1982, pp. 120, 121; forapplication to honeybee vision see Neumeyer 1981)postulates that SNR – and thus detectability – is in-dependent of light intensity. By comparison, thephoton-noise-limited color opponent model (Voro-byev and Osorio 1998; Vorobyev et al. 1998) postu-lates that the SNR increases with increasing light in-tensity, thus making bright stimuli easy to detect. Fi-nally, the color-hexagon model (Chittka 1992) as-sumes that receptor signals saturate when the target

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Fig. 1. a) Reflectance spectra of a green leaf, of the green paper usedin the experiments, and of UV-reflecting white and gray. b) Predic-tions for detectability by a honeybee eye of UV reflecting grays ongreen paper background using three published models. The reflec-tance of gray varies from 0.01 (close to black) to 1 (ideal white). Thereflectance of the stimuli used in our study are labeled as “Gray” and“White.” Detectability of a color against a background is given by thedistance in the color space to the background, DS, To simplify thecomparison, DS is scaled to unity for the optimal gray reflectance aspredicted by the hexagon model. The models calculate DS from thereceptor quantum catches qS, qM, qL, where indexes S, M, L corre-spond, respectively, to short-, middle-, and long-wavelengths recep-tors. The quantum catches are scaled so that the quantum catch forthe background is equal to unity. The color triangle presentation isobtained in the unit plane, qScqMcqLp1 and DSp;(Dx)2c(Dy)2 ,where x and y denote two orthogonal directions in this plane (Neu-meyer 1981). The color hexagon assumes that receptor signals are

given by receptor excitations, which are calculated as Ei pqi

1cqi.

Coding is performed by two unspecified color opponent mechanisms:xpsin(607) (EL–ES) and ypEM–0.5(ELcES), andDSp;(Dx)2c(Dy)2 (Chittka 1992). The photon-noise-limited coloropponent model postulates that coding is performed by two unspeci-fied color opponent mechanisms, whose accuracy is limited by thenoise of receptor mechanisms (Vorobyev and Osorio 1998). The rela-

tive receptor noise is given by vipv0i " 1

qi. And the color distance is

calculated as

(DS)2 pv2

S(DfLPDfM)2cvM2 (DfLPDfS)2cv2

L(DfSPDfM)2

(vS vM)2c(vSvL)2c(vMvL)2 ,

where fipln(qi), (Vorobyev et al. 1998). According to electophysio-logical recording in single receptor cells vS

0p0.13, vM0 p0,06 and

vL0p0.12 (Peitsch 1992)

intensity exceeds that of the background (SNR de-creases with increasing light intensity), thus makingbright stimuli difficult to detect. According to thehexagon model the optimum detectability occurswhen the average stimulus reflectance is similar tothat of the background (Fig. 1b). Consequently agray object presented on a green background wouldbe easier to detect than a white object, while othermodels (Vorobyev and Brandt 1997) predict eitherthat white and gray objects are equally well de-tected, or that white objects are easier to detect thanare gray ones.To test the conflicting predictions of the variousmodels we trained honeybees Apis mellifera L. todetect UV-reflecting white or gray targets presentedon a green background. The intensity of gray waschosen so as to provide optimal detectability as pre-dicted by the hexagon model. Our white was pre-dicted to be indistinguishable from green. Back-grounds were made from a green cardboard (HKS-58N, Stuttgart-Feuerbach, Germany) whose spec-trum in the visible range of bees (300–630 nm) wassimilar to that of leaves (Fig. 1a). The targets –which reflect uniformly across the spectrum, includ-

ing the UV – were created using BaSO4 powder(white) or a mixture of BaSO4 and carbon powder(gray). The experimental procedure was similar tothat described elsewhere (Giurfa et al. 1996). Beeswere trained to enter a Y-maze illuminated by natu-ral daylight and collect there a 50% sucrose solu-tion. A circular white or gray stimulus (8 cm diam-eter) was placed on the green background in onearm of the Y-maze (20–25 cm from the entrance):the other arm presented the background alone. Asucrose reward was offered at the center of the disk,and the disk was presented alternately, in a pseudo-random order, in the right or the left arm. The first30 choices of individual bees were recorded. Aftertesting for homogeneity (x2 test), the choices of in-dividual bees were pooled and percentages ofchoices in favor of the arm with the disk were calcu-lated.Contrary to the predictions of the hexagon model,our experiments show clearly that bees detect whiteobjects on a green background (Fig. 2), whereasgray objects on the same background are detectedless easily. This may indicate either that SNR ofchromatic mechanisms increases with increasing

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Fig. 2. Results of detection experiments with individually markedfree-flying honeybees. Error bars 95% confidence intervals (Fisher’sexact test). N Number of individual bees; n total number of choices

light intensity, as postulated by the photon-noise-limited color opponent model (Vorobyev and Oso-rio 1998; Vorobyev et al. 1998), or that achromaticvision is also used for detection of colored stimuli(Giurfa and Vorobyev 1998), or both. In any case,our results imply that the hexagon model does notprovide adequate predictions for stimuli which dif-fer in intensity, one of the most basic properties ofvisual stimuli. Bees – as humans – do see white flow-ers on green backgrounds. A number of evolutiona-ry and ecological speculations (e.g., Chittka 1996,1997; Chittka and Waser 1997; Chittka et al. 1994;Kevan et al. 1996; Waser and Chittka 1998) havebeen based on the color hexagon model. Since thepredictions of the hexagon model are at odds withbehavioral data, these speculations should be re-vised.

Acknowledgements We thank R. Menzel for fruitful discussions andvaluable suggestions, M. Lehrer, E. Warrant, D. Osorio, J. Partridge,T. Cronin, and J. Marshall for helpful comments and corrections ofthe manuscript. M. Vorobyev and M. Giurfa were supported byDeutsche Forschungsgemeinschaft (AZ Me365/20-2), N. Hempel deIbarra by the Academy of Science of Berlin-Brandenburg. This re-search was carried out according to regulations for animal experi-ments as stipulated in German law.

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