Unravelling the mystery of red flowers in the Mediterranean Basin: How to be conspicuous in a place dominated by hymenopteran pollinators
León-Osper, Melissa; Narbona, Eduardo (2022), Unravelling the mystery of red flowers in the Mediterranean Basin: How to be conspicuous in a place dominated by hymenopteran pollinators, Dryad, Dataset, https://doi.org/10.5061/dryad.4mw6m90d9
Red-flowered species have traditionally been related to ornithophily, and the 'bee avoidance' hypothesis, i.e. red flower coloration is a way to reduce visits from hymenopterans, has been proposed to explain this association. In the Mediterranean Basin, ornithophily is almost absent, and hymenopterans are the most common group of pollinators. The fact that hymenopterans are virtually red-blind raises the question of how red-flowered species are pollinated in this region. Are these flowers pollinated by other groups of red-sensitive insects such as lepidopterans and coleopterans, or do they have visual cues that make them attractive to hymenopterans? We examined the reflectance spectra of 51 red-flowered species from the Mediterranean Basin and modelled these spectra in the visual system of hymenopterans, dipterans, coleopterans, and lepidopterans to obtain colour and conspicuousness. According to their reflectance curves, species were classified as pure red and UV-red flowers, and the presence of more than one flower colour (patterned flowers) was studied. We evaluated the match between flower reflectance spectra and the maximum discrimination abilities of hymenopteran and lepidopteran visual system. All these metrics were analysed in a phylogenetically explicit framework, and a literature review of potential pollinators was performed. The vast majority of red-flowered species in the Mediterranean Basin are potentially pollinated by hymenopterans, and only three species are exclusively visited by coleopterans. We found that 90% of these species showed at least one colour signal strategy that helps to enhance conspicuousness to hymenopterans: to produce UV-red flower type spectra and/or patterned flowers. The UV-red colour showed a significant phylogenetic signal, but the presence of patterned flowers did not. Even though the red-flowered species of the Mediterranean Basin did not optimally match the colour vision of hymenopterans or lepidopterans, the presence of patterned and UV-red colours suggests an improvement in detection and discrimination by hymenopterans. The bee-avoidance hypothesis seems to be ruled out for the red-flowered species of the Mediterranean Basin. Our results suggest that red-flowered species are mostly pollinated by hymenopterans and show different flower colour signal strategies that can be interpreted as signs of adaptation to these pollinators.
We sampled 51 red-flowered species from the Mediterranean Basin and recorded their reflectance spectra in the UV and visible light spectrum with a spectrophotometer. Reflectance data was processed using PAVO package (Maia et al., 2019) in R Studio. We also assesed the presence of UV or visible colour patterns in flowers and measure its reflectance spectra.
The data set includes values for main colour (red) and pattern of the sampled species for the pollinators visual models studied namely hymenopterans, dipterans, coleopterans and lepidopterans. Data encompass chromatic contrast values, spectral purity and location of marker points using the online tool 'Spectral-MP' developed by Dorin et al. (2020).
- Dorin, A., Shrestha, M., Herrmann, M., Burd, M. & Dyer, A. G. (2020). Automated calculation of spectral-reflectance marker-points to enable analysis of plant colour-signaling to pollinators. MethodsX, 7, 100827. http://dx.doi.org/10.1016/j.mex.2020.100827
- Maia, R., Gruson, H., Endler, J. A. & White, T. E. (2019). PAVO 2: new tools for the spectral and spatial analysis of colour in R. Methods in Ecology and Evolution, 10(7), 1097-1107. https://doi.org/10.1111/2041-210X.13174
Data set is provided as a ".xlsx" file.
Consejería de Economía, Conocimiento, Empresas y Universidad, Junta de Andalucía, Award: PREDOC_00336
Agencia Estatal de Investigación, Award: PID2020-116222GB-100
Ministerio de Economía y Competitividad, Award: CGL2015-63827