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Supplementary material
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Methods
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Floral arrays
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Flowers were arranged in a 5 × 4 grid spaced 7 cm apart at the base (5 cm apart at the
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top), and consisted of 3D-printed 5 cm diameter discs (Makerbot, NY, USA) placed on
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inverted plastic tubes (8 cm in height), with a coloured circle (the ‘corolla’, printed on
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laminated waterproof paper: National Geographic Co., USA). The centre of the corolla
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contained a ‘nectar well’ (diameter: 4mm) and an ‘anther’ (a 25 mm chenille stem:
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Creatology, China). Flowers were always oriented in the same direction, such that the
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nectar wells faced bees as they entered the arena.
To scent ‘unrewarding’ anthers used in the experiment, we stored artificial anthers
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overnight in a sealed container of pollen, separated from the pollen by mesh. Treating
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anthers in this way likely does not make them indistinguishable from rewarding anthers
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by scent alone, but previous experiments [1] suggest that such treatment is necessary for
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bees to land on anthers lacking pollen and thus facilitates learning which flowers contain
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pollen rewards based on the associated floral visual cue.
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Behaviour recorded
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From the videos we recorded each flower visit made by a bee, including: 1) the colour of
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the flower (blue or yellow); 2) whether the bee attempted to collect nectar or pollen; and
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3) whether they were successful at gaining the reward or not (‘rewarded’ or
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‘unrewarded’).
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Nectar collection was identified as the bee landing on the ‘corolla’ of the flower
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and probing the nectar well. We defined nectar visits as ‘rewarding’ when the bee drank
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the nectar reward (probing the well for >2 seconds; inspection of wells and preliminary
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observations indicated that bees generally empty the well on their visits, taking 10-30
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seconds to do so) and as ‘unrewarding’ when she probed a well containing water (bees
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generally left immediately after doing this). If a bee visited a flower and probed for nectar
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where she had already emptied the well of its reward (but where there was probably some
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residue), we excluded this from analysis of training, because it is not clear whether bees
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experience such visits as rewarding or unrewarding, and because they are a different type
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of error to visiting the CS-. Across all bees’ visits to collect nectar, less than 1% were re-
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visits to previously emptied nectar wells.
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Pollen collection was easily identified as the bee flying directly to the anther and
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‘scrabbling’ [2,3] at the pollen with her legs in a stereotyped manner, as in [1] (see
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supplementary video). In packing the pollen onto their corbiculae, bees were also seen
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extending their proboscis and grooming with their front legs. In our assay, this usually
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occurred on the flower’s anther or in flight, but occasionally the bee would land to groom
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elsewhere (on a flower’s corolla or the arena wall). Because bees only collected and
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searched for pollen from the flowers’ anthers, we defined a ‘visit’ to a flower type as the
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bee touching the anther with its antennae or legs (either by landing or hovering in front of
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the top of the anther). If the anther contained pollen and the bee was seen to scrabble with
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its legs, the visit was recorded as ‘rewarded’. If the anther had no pollen on it and the bee
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touched it with its antennae or legs the visit was recorded as ‘unrewarded’. If the bee
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briefly touched the rewarding anther with her antennae or legs but did not scrabble to
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collect pollen from it then this visit was excluded from analyses, because it was not clear
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whether the bee had failed to detect the pollen or had detected its presence but decided
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not to collect it (i.e. whether this visit was perceived as reinforcing or inhibiting to the
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bee). Unlike when nectar-foraging, pollen-foraging bees did not empty anthers containing
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pollen on a single visit. Instead, a bee would generally collect pollen from all rewarding
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anthers, and then return to anthers they had already visited to collect more pollen; these
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visits were also scored as ‘rewarding’. Across all bees’ visits to collect pollen, 58% were
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rewarding, 28% were unrewarding and 14% were to rewarding flowers but without the
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bee collecting pollen.
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Nectar and pollen collection on the artificial flowers can be seen in the
supplementary video.
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Data analysis
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We carried out all LMMs in R version 2.15.1 (R Development Core Team 2014). LMMs
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were carried out using the lme() function in nlme package, specifying type III sums of
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squares and sums contrasts in cases where we included interactions [4]. For all models,
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maximal models were run initially, and then non-significant interaction terms were
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removed in a step-wise fashion. In cases of significant interactions, simplified models
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were re-run to determine the significance of the individual factors in these interactions.
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To do this, we divided the data into two groups by one of the two-level factors in the
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significant interaction, and ran two separate analyses in order to determine the
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significance of the remaining main effects. Results are reported for models with non-
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significant interaction terms removed.
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To assess whether bees learned to associate floral colour with nectar and pollen,
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we compared the proportion of correct flower visits made across trials and treatments. We
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fitted a linear mixed model (LMM) with the response variable ‘proportion of correct
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choices made’ and the explanatory variables: trial (a continuous variable between 1 and
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6); treatment (PYNB or PBNY); reward type (nectar or pollen) and the random factors
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‘bee’ and ‘colony’(‘Model 1’). As we had two significant interactions (LMM:
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treatment*reward type: F1, 208 = 5.642; p < 0.05; trial*reward type: F1, 208 = 15.355; p <
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0.001), we then ran two additional LMMs for each treatment group separately.
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To determine whether bees visited different flowers in the test phase between the
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two treatments and for the two different rewards, we initially ran a model with the
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response variable ‘number of visits in the first 10 visits’ and the same explanatory
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variables as ‘Model 1’ except excluding ‘trial’ and including ‘flower colour’ (blue,
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yellow, orange or purple). As this model showed that the colour of flower the bee visited
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differed both depending on whether they were searching for nectar or pollen and between
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the two treatment groups, via a 3-way interaction (treatment*reward*colour interaction:
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F3, 126 = 92.332; p < 0.0001), we proceeded to address the two treatment groups separately
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in two further models.
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These two models showed that within each treatment group, the colour of flower a
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bee visited differed when she was searching for nectar versus pollen (LMM of PBNY
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data: reward*flower colour interaction: F3, 63 = 36.739; p < 0.0001; LMM of PYNB data:
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F3, 63 = 58.198; p < 0.0001). To better understand these interactive effects and because we
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were interested in specifically which colours bees chose over others when searching for
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each reward type, we then carried out four individual models for each reward type within
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each treatment. All of these models showed that bees did not visit colours equally: PBNY,
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nectar: F3, 27 = 34.054; p < 0.0001; PBNY, pollen: F3, 27 = 11.869; p < 0.0001; PYNB,
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nectar: F3, 27 = 62.947; p < 0.0001; PYNB, pollen: F3, 27 = 16.964; p < 0.0001). We used
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pair-wise comparisons between flower colour factors to determine where these
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differences lay.
To determine whether short-term “reward specialists” (bees that collected only
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nectar or pollen from blue flowers) differed in their learning and test performance vs.
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bees that collected both nectar and pollen, we compared the proportion of correct visits
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for either nectar or pollen (for nectar- and pollen-“specialists”, respectively) to bees that
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had collected both rewards. We used LMMs as described above but included only
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explanatory variables ‘trial’ and ‘behaviour’ (specialist or short-term “generalist”) and the
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random factor ‘bee’.
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Colourimetry
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We measured the reflectance spectra of the four flower colours used in the experiment
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and irradiance at the array using a single beam UV-VIS spectrophotometer (Ocean
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Optics, Dunedin, FL, U.S.A.) (Figure S1). The spectrophotometer was connected by
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means of a USB cable to a computer running SpectraSuite software (Ocean Optics). We
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then plotted the reflectance spectra into bee colour space taking into account the
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photoreceptor spectral sensitivities of B. impatiens [5] and irradiance, using AVICOL v.6
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(AVICOL: A program to analyse spectrometric data; free program available from the
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author at dodogomez@yahoo.fr) (Figure S2). These analyses confirmed that for bees, the
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human-purple target was more similar to the human-blue target, and the human-orange
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target was more similar to the human-yellow target (for chromatic contrasts see Table
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S1).
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Figure S1: Reflectance spectra of the four colours used in the experiment. Colours refer
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to human visual perception.
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Table S1: Chromatic contrasts of the four colour stimuli used relative to each other. All
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data are in hexagon units, and are calculated as described elsewhere [6].
Comparison
Chromatic contrast
yellow-orange
0.102
yellow-blue
0.234
yellow-purple
0.286
orange-blue
0.334
orange-purple
0.389
blue-purple
0.078
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Results
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Comparison between foragers that collected one vs. two reward types
In the test phase, PBNY-trained bees that had collected both rewards during
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training made significantly more errors during the test phase than bees that foraged for
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pollen alone, as they visited yellow and orange flowers more frequently for pollen (Mann
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Whitney U-Tests: orange: n=10,5, U=0, p < 0.005; yellow: n=10,5, U=0, p < 0.005).
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PYNB-trained bees that either collected only nectar or both rewards did not differ in their
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test performance, making the same number of attempts to collect nectar from yellow and
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orange flowers (Mann Whitney U-Tests: orange: n=10,8, U=22.50, p = 0.102; yellow:
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n=10,8, U=29.50, p = 0.312).
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References
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Muth, F., Papaj, D. R. & Leonard, A. In revision at Animal Behaviour Bees
remember flowers for more than one reason: Pollen mediates associative learning.
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2.
Buchmann, S. L. 1983 Buzz pollination in angiosperms. In Handbook of
Experimental Pollination Biology (eds C. E. Jones & R. J. Little), pp. 73–113. Van
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3.
Thorp, R. 2000 The collection of pollen by bees. Plant Syst. Evol. 222, 211–233.
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Pinheiro, J., Bates, D., DebRoy, S., & Sarkar, D. (2014). nlme: linear and nonlinear
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