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Ancient insect vision tuned for flight amongst rocks and plants underpins natural flower colour diversity - rock, mineral, stick, bark, leaf, bird- and insect-flower petal reflectance spectra

Dorin, Alan1; Shrestha, Mani2; Garcia, Jair3; Burd, Martin4; Dyer, Adrian1

Published Feb 09, 2024 on Dryad. https://doi.org/10.5061/dryad.fn2z34v2c

Cite this dataset

Dorin, Alan et al. (2024). Ancient insect vision tuned for flight amongst rocks and plants underpins natural flower colour diversity - rock, mineral, stick, bark, leaf, bird- and insect-flower petal reflectance spectra [Dataset]. Dryad. https://doi.org/10.5061/dryad.fn2z34v2c

Abstract

Understanding the origins of flower colour signalling to pollinators is fundamental to evolutionary biology and ecology. Flower colour evolves under pressure from visual systems of pollinators, like birds and insects, to establish global signatures among flowers with similar pollinators. However, an understanding of the ancient origins of this relationship remains elusive. Here, we employ computer simulations to generate artificial flower backgrounds assembled from real material sample spectra of rocks, leaves, and dead plant materials, against which to test flowers’ visibility to birds and bees. Our results indicate how flower colours differ from their backgrounds in strength, and the distributions of salient reflectance features when perceived by these key pollinators, to reveal the possible origins of their colours. Since Hymenopteran visual perception evolved before flowers, the terrestrial chromatic context for its evolution to facilitate flight and orientation consisted of rocks, leaves, sticks, and bark. Flowers exploited these pre-evolved visual capacities of their visitors, and in response evolved chromatic features to signal to bees, and differently to birds, against a backdrop of other natural materials. Consequently, it appears that today’s flower colours may be an evolutionary response to the vision of diurnal pollinators navigating their world millennia prior to the first flowers.

README: Ancient insect vision tuned for flight amongst rocks and plants underpins natural flower colour diversity - rock, mineral, stick, bark, leaf, bird- and insect-flower petal reflectance spectra

https://doi.org/10.5061/dryad.fn2z34v2c

The dataset contains spectral reflectance data collected from:

  • Australian background materials, i.e. non-floral surfaces, likely to appear behind flowers when viewed by pollinating insects and birds : rocks, minerals, sand, shells, dry leaves, dry bark, wood, dry seeds, green leaves.
  • Australian flowers (petal surfaces): insect- and bird-pollinated flowers.

The data was used to test theories of flower colour evolution targeting visual systems of insect and bird pollinators. It supports the hypothesis that flowers have evolved colours to allow their specific pollinators to detect them against natural backgrounds that form the visual context for pollinator foraging.

Reflectance curves were measured for background material and floral samples from 300-700 nm using a spectrophotometer with quartz optics and a PX-2 pulsed xenon light source (USB2000+, Ocean Optics Inc., Dunedin, FL, USA) attached to a computer running SPECTRA SUITE software. Reflectance profiles were measured relative to a Lambertian PTF WS-1 reflectance standard (Ocean Optics, USA).

Description of the data and file structure

Spectral reflectance data are collected in sets:

  1. Backgrounds

    1. Bark, dry leaves, sticks (96 samples)
    2. Green leaves (65 samples)
    3. Rocks and Minerals (346 samples)

  2. Insect-only pollinated flower petals (153 samples)

  3. Bird-only pollinated flower petals (68 samples)

Although file names all have a numerical prefix, these are not indicative of any relationship between samples – they are simply the order in which the samples were measured over several years of data collection. Many file prefixes are missing as they refer to samples that are not relevant to the present dataset. File labels "insect-only" and "bird-only" refer to the fact that, based on the literature, these species have a clearly dominant pollinator (either insect or bird).

Backgrounds spectral reflectance data are stored in CSV files generated by Open Access software Spectral-MP** when fed with the raw spectral reflectance data. These data are formatted as follows (refer to Spectral-MP publication and software manual for more detail):

  • column 1 = wavelength
  • column 2 = spectral reflectance (0-100%), mean value of 3 raw spectrophotometer readings of a material taken in the same area of the surface on all materials except green leaves where samples were taken at leaf base, middle and tip.
  • column 3 = spectral reflectance (0-100%) smoothed values of column 2 with smoothing applied by Spectral-MP with input parameters: Threshold 20%; Range 50 nm; Smoothing window 21 points (i.e. +/- 10 points either side of central point); Lookahead 5 points; Interval 300-700 nm.
  • column 4 = spectral reflectance (0-100%) sections of curve (if any) identified by Spectral-MP as being monotonically increasing or decreasing (parameters as for column 3)
  • column 5 = spectral reflectance (0-100%) marker points (if any) identified by Spectral-MP at 20% threshold (parameters as for column 3).
  • Notes: Image.PNG image files in the directories are produced by SpectralMP and show the plotted spectral reflectance graph for each material with (Threshold=20%) marker points (if any). Material name for each sample appears in the file name, e.g., 1223_EucalyptusDryBark_Bark_1.csv. Files Histogram_H/V.png and histogram.csv are produced automatically by the SpectralMP software and depict histograms (_H/V.png indicates horizontal/vertical formatting, .csv = data file) of the marker points for the encapsulating folder placed in 10 nm wide bins.

Insect and Bird-pollinated flower petal spectral reflectance data are stored in CSV files formatted as follows:

  • column 1 = wavelength
  • column 2 = spectral reflectance (0-100%)
  • Notes: Files _FlowerData FileList 2023 Bird Pollinated Only.csv and _FlowerData FileList 2023 Insect Pollinated Only.csv contain the species lists for the spectral data files which are simply numbered file names, e.g., 112.csv

Code/Software

** Spectral-MP software is detailed/linked in: Dorin, A., Shrestha, M., Herrmann, M., Burd, M. & Dyer, A. G. Automated calculation of spectral-reflectance marker-points to enable analysis of plant colour-signalling to pollinators. MethodsX 7, 1-9, https://doi.org/10.1016/j.mex.2020.100827 (2020)

Methods

Material samples, data collection

Background materials data (non-floral surfaces): rocks, minerals, sand, shells, dry leaves, dry bark, wood, dry seeds, and green leaves.

  • Background surface data samples were collected across a 2400 km range from the tropical north (16.9°, 145.7°) to the temperate southern tip (39.1°, 146.2°) of mainland Australia.
  • N = 507 total natural background surface data samples were collected: n = 65 green leaves; n = 96 dry leaves, bark, wood etc. samples; n = 346 rocks/mineral samples.

Flower data (petal surfaces): insect- and bird-pollinated flowers.

  • Flower data has previously been described and analysed 9,29 and is made available here.

Spectral reflectance measurement

Reflectance curves were measured for background material and floral samples from 300-700 nm (see below – Marker point calculations) using a spectrophotometer with quartz optics and a PX-2 pulsed xenon light source (USB2000+, Ocean Optics Inc., Dunedin, FL, USA) attached to a computer running SPECTRA SUITE software. Reflectance profiles were measured relative to a Lambertian PTF WS-1 reflectance standard (Ocean Optics, USA). Multiple readings, usually three, were taken from within a square region of each surface (see associated article, Fig. 1B for examples). Where sample surfaces were conspicuously heterogeneous to human visual systems several sections were sampled individually and used in this study. In the case of fresh green leaves specifically, one measurement was taken near the base, one in the middle, and one near the tip of each. These three spectra were then used to calculate an average reflectance spectrum for the leaf.

To assist us in making accurate spectrophotometer readings, we built a black, curved-wall sample enclosure and covered this with a black cardboard lid. The lid was perforated with a tiny hole through which a fibre-optic light was channelled which prevented ambient light from hitting the sample during measurement. Room lighting was turned off. The optical fibre was held in an aluminium block that also helped eliminate stray illumination. The fibre was held approximately 6 mm above each sample, illuminating a circular patch 3-4 mm in diameter. Sample data points recorded between 300 and 700 nm in wavelength that represent reflectance spectra for three background surfaces are illustrated (see associated article, Fig. 1B).

Marker point calculations

Marker points are locations on surface spectral reflectance curves centrally located within sudden changes in spectral reflectance (see associated article, Fig. 1B) 14, SuppRef-1. The severity of the jump is measured as a threshold over which it occurs from its base reflectance to its peak.  For this study, marker points were identified as the midpoint of any change in reflectance of at least a pre-specified percentage threshold value, occurring within a wavelength range of < 50 nm. We calculated thresholds for each background sample at 5% reflectance jump and for each flower sample at 20% reflectance jump, in order to compare the properties of different materials. The 20% threshold for flower spectra was taken from the literature as being suited to such evolutionarily enhanced signals16. The 5% threshold for natural backgrounds that do not constitute evolutionarily enhanced reflectance curves was determined empirically to provide a similar mean number of marker points per sample as the 20% threshold had done for the flowers (see associated article, Supp Table 1).

Marker point calculations were performed using the Open Source Spectral-MP softwareSuppRef-1 with parameters: Threshold 5% (backgrounds), 20% (flowers); Range 50 nm; Smoothing window 21 points; Lookahead 5 points; Interval 300-700 nm. The study interval of 300-700 nm was selected to ensure we analysed regions in which the spectrophotometer readings were reliable, noting that the extremities of these regions are outside the range of sensitivity of avian and hymenopteran pollinator vision (see associated article, Fig. 1B).

References

(Citation numbering refers to original article bibliographic data, reproduced here without change for clarity)

9. Shrestha, M., Dyer, A. G., Boyd-Gerny, S., Wong, B. B. M. & Burd, M. Shades of red: bird pollinated flowers target the specific colour discrimination abilities of avian vision. New Phytologist 198, 301–310 (2013).

14. Chittka, L. & Menzel, R. The evolutionary adaptation of flower colors and the insect pollinators' color vision systems. Journal of Comparative Physiology A 171, 171-181 (1992).

16. Dyer, A. G. et al. Parallel evolution of angiosperm colour signals: common evolutionary pressures linked to hymenopteran vision. Proc. Royal Soc. London B 279, 3605-3615 (2012).

29. Burd, M., Stayton, C. T., Shrestha, M. & Dyer, A. G. Distinctive convergence in Australian floral colours seen through the eyes of Australian birds. Proc. R. Soc. B 281 (2014).

SuppRef-1. Dorin, A., Shrestha, M., Herrmann, M., Burd, M. & Dyer, A. G. Automated calculation of spectral-reflectance marker-points to enable analysis of plant colour-signalling to pollinators. MethodsX 7, 1-9, https://doi.org/10.1016/j.mex.2020.100827 (2020).

Funding

Australian Research Council, Award: DP130100015, Discovery Project

Australian Research Council, Award: DP160100161, Discovery Project

Federal Ministry of Education and Research, Award: 031B0516C