Data from: An affordable apparatus for fine‐controlled emulation of buzzing frequencies of bees for the testing hypothesis in buzz interactions
Cite this dataset
Rodrigues, Ernani V. et al. (2019). Data from: An affordable apparatus for fine‐controlled emulation of buzzing frequencies of bees for the testing hypothesis in buzz interactions [Dataset]. Dryad. https://doi.org/10.5061/dryad.5147g9s
1. The buzzing foraging behavior of female bees for pollen harvesting called the attention of early pollination biologists. Flower-types that demand this buzzing behavior comprise about 20.000 species of different and phylogenetically unrelated plant taxa, suggesting that it had independently evolved many times among the flowering plants. Between the late 70’s and early 80’s, theoretical papers had modeled the energetics of buzz-pollination, but, up to this moment, no hypothesis was experimentally tested concerning the theoretical basis of the energetics of buzz-pollination. 2. We present a cost-eﬀective and simple apparatus, including a digital and highly accurate frequency generator, and a device for the transference of buzz-frequency energy to the receptive floral unity. The receptive floral unities may comprise the entire or partial androecium, or the tubular corolla, or, in some cases, the whole flower. 3. This apparatus can be easily used both laboratory and field conditions of research, since natural air currents are avoided, and the response of pollen liberation can be quantitatively measured by pollen grain counts that can be captured by adhesion in slide poured with an isosmotic lactate-glycerin media. 4. The maximum displacement of the hardwire beam/claw system was 0.1170 ± 0.0006mm @ 150Hz; 0.021 ± 0.003 mm @ 250 Hz; 0.010 ± 0.001 mm @350 Hz; 0.0058 ± 0.0001 mm @ 450 Hz and 0.0082 ± 0.0005 mm @ 55 0Hz. 5. Hypothesis contrasting frequency emission and pollen liberation measured as pollen-grain counts may be tested in a species flower-type by simple linear regression, if pollen counts are normally distributed, or ordinal logistic regression, with non-normal counts. The comparison among different flower-type requirements can be tested through appropriate statistical methods for both normally and non-normally distributed pollen grain counts.