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Area of Science:

  • Ecology
  • Bioacoustics
  • Pollination Biology

Background:

  • Wild and managed bee populations are declining due to multiple factors, impacting crucial pollination services.
  • Effective bee population management requires widespread, intensive monitoring, which is often cost-prohibitive.
  • Passive acoustic monitoring offers a potential low-cost, non-invasive alternative for tracking bee activity.

Purpose of the Study:

  • To evaluate an inexpensive, passive acoustic survey technique for monitoring bumble bee behavior and pollination services.
  • To determine the relationship between bumble bee flight buzz characteristics and pollinator functional traits.
  • To assess the efficacy of acoustic data in predicting bumble bee activity and pollination success.

Main Methods:

  • Flight cage experiments and literature review to correlate flight buzz frequency with pollinator traits.
  • Development of a Computational Auditory Scene Analysis algorithm to quantify buzzes from acoustic data.
  • Comparison of acoustic estimates with visual observations of bumble bee activity.
  • Pollinator exclusion experiments to link buzz density to seed set in alpine plants.

Main Results:

  • Bumble bee flight buzz frequency correlated with body size and tongue length, traits influencing pollination.
  • Acoustic buzz density strongly correlated with visual estimates of bumble bee density (r = 0.97).
  • Buzz density significantly predicted seed set in two alpine forb species when bees had access.

Conclusions:

  • Acoustic signatures of bumble bee flight can be reliably deciphered to monitor bee activity.
  • Passive acoustic monitoring effectively predicts pollination services for bumble bee-pollinated plants.
  • This technique can assist scientists and farmers in early detection and response to bee population declines.