Abstract Detail



Symbioses: Plant, Animal, and Microbe Interactions

Howard, Scarlett [1].

Flower shape and quantity as informative cues for honeybee foragers.

Flowers utilize a range of signals, cues, and traits to attract or deter potential floral visitors. While many of these aspects of plant-pollinator communication have been extensively studied, less is known about the whether flower shape and quantity of flowers attracts pollinators. Here we present data testing honeybee (Apis mellifera) preferences for bird- or insect-pollinated flowers, based on shape. We examined whether preferences are based on global or local flower traits such as flower elongation, size, brightness, or flower number. Honeybees were shown to prefer insect-pollinated flowers based on the holistic shape of the flower rather than local cues, even in the absence of olfactory signals, colour signals, and prior experience with the flowers. We also tested whether honeybees would choose flower patches based on the quantity of flowers available. Honeybees preferred patches with greater flower number, only when the comparison was with a single flower (e.g. 1 vs. 3, 1 vs. 4, 1 vs. 12, but not 2 vs. 4). Our results have implications for the evolution of plant-pollinator communication and suggest spatial achromatic flower properties are an important part of visual signalling for plant–pollinator interactions. There also appears to be an evolutionary benefit to choosing a foraging patch with a higher quantity of flowers when resources are scarce.


Related Links:
Honeybees prefer novel insect-pollinated flower shapes over bird-pollinated flower shapes
Spontaneous quantity discrimination of artificial flowers by foraging honeybees


1 - Deakin University, Faculty of Science, Engineering and Built Environment, 221 Burwood Hwy, Burwood, Victoria, 3125, Australia

Keywords:
pollinator
pollination
honeybee
plant-pollinator
flower
angiosperm.

Presentation Type: Oral Paper
Session: SYMB1, Symbioses: Plant, Animal, and Microbe Interactions I
Location: Virtual/Virtual
Date: Tuesday, July 28th, 2020
Time: 12:45 PM
Number: SYMB1002
Abstract ID:543
Candidate for Awards:None


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