Supplementary material from "Sensory bias and signal detection tradeoffs maintain intersexual floral mimicry"
Posted on 2020-04-21 - 08:57
Mimicry is common in interspecies interactions, yet conditions maintaining Batesian mimicry have been primarily tested in predator–prey interactions. In pollination mutualisms, floral mimetic signals thought to dupe animals into pollinating unrewarding flowers are widespread (greater than 32 plant families). Yet whether animals learn to both correctly identify floral models and reject floral mimics and whether these responses are frequency-dependent is not well understood. We tested how learning affected the effectiveness and frequency-dependence of imperfect Batesian mimicry among flowers using the generalist bumblebee, Bombus impatiens, visiting Begonia odorata, a plant species exhibiting intersexual floral mimicry. Unrewarding female flowers are mimics of pollen-rewarding male flowers (models), though mimicry to the human eye is imperfect. Flower-naive bees exhibited a perceptual bias for mimics over models, but rapidly learned to avoid mimics. Surprisingly, altering the frequency of models and mimics only marginally shaped responses by naive bees and by bees experienced with the distribution and frequency of models and mimics. Our results provide evidence both of exploitation by the plant of signal detection tradeoffs in bees and of resistance by the bees, via learning, to this exploitation. Critically, we provide experimental evidence that imperfect Batesian mimicry can be adaptive and, in contrast with expectations of signal detection theory, functions largely independently of the model and mimic frequency.This article is part of the theme issue ‘Signal detection theory in recognition systems: from evolving models to experimental tests’.
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Russell, Avery L.; Kikuchi, David W.; Giebink, Noah W.; Papaj, Daniel R. (2020). Supplementary material from "Sensory bias and signal detection tradeoffs maintain intersexual floral mimicry". The Royal Society. Collection. https://doi.org/10.6084/m9.figshare.c.4946076.v1
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Avery L. Russell
David W. Kikuchi
Noah W. Giebink
Daniel R. Papaj