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Bayesian mimicry in the non-rewarding saprophytic orchid Danxiaorchis yangii

Citation

yang, boyun (2022), Bayesian mimicry in the non-rewarding saprophytic orchid Danxiaorchis yangii, Dryad, Dataset, https://doi.org/10.5061/dryad.8w9ghx3jk

Abstract

Bayesian mimicry, a type of deceptive pollination, is a complicated strategy used by non-rewarding plants to attract pollinators, but some hypotheses concerning this phenomenon have not been systematically verified. In order to show in detail a case of Bayesian mimicry on saprophytic orchid Danxiaorchis yangii in this study, we compared floral characteristics of Danxiaorchis yangii and Lysimachia alfredi as well as the pollination behavior of the insect Dufourea sp. towards the two species. Lysimachia alfredi can provide a reward to Dufourea sp., whereas Danxiaorchis yangii cannot. The flowering phenology and geographical distribution of these two plants are highly overlapping. Statistical analysis of quadrat and L. alfredi transplanting test data revealed that the fruit set rate of Danxiaorchis yangii was significantly positively correlated with the number of nearby L. alfredi individuals. In a glass cylinder experiment, Danxiaorchis yangii and L. alfredi attracted Dufourea sp. through visual signals, but the insect could not distinguish between flowers of the two plants before landing on flowers. We observed that the ultraviolet reflection spectra of Danxiaorchis yangii and L. alfredi are highly similar. In addition, we found that the hexagonal color models of the two plants are consistent with the bee’s visual characteristics, thus indicating that the visual signals of the flowers of the two plants are greatly similar. All of these results provide evidence that Danxiaorchis yangii simulates the visual signals of L. alfredi through Batesian mimicry, thereby deceivingly attracting Dufourea sp.

Funding

National Natural Science Foundation of China, Award: 31260485&31360491

National Science & Technology Fundamental Resources Investigation Program of China, Award: 2018FY100406