Photo by Ben Barnhart
More than two decades ago, a groundbreaking study showed bumble bees could become infected with Crithidia by foraging on plants that had already been visited by infected bees. Furthermore, the odds of becoming infected differed on two different plant species, and were mediated by floral architecture (Durrer and Schmid-Hempel 1994). Only recently have others begun to consider the role that flowers play in pathogen transmission among bees. We are examining how plant species vary in their ability to transmit Crithidia to bumble bees, the traits that influence transmission, and consequences for pathogen infection at the colony scale. We found that plant species vary fourfold in their likelihood of transmitting C. bombi (Adler et al 2018) and that this variation scales up to affect colony-level infection intensity (Adler et al 2020).
We are part of a collaborative project assessing trait-mediated pathogen transmission in bee pollinators funded by the EEID (Ecology and Evolution of Infectious Disease) panel by NIH, with lead PI Scott McArt (Cornell) and including collaborators Becky Irwin (NCSU), Steve Ellner and Chris Myers (Cornell), and Quinn McFrederick (UC Riverside). Our role, led by postdoctoral research Jenny Van Wyk, used manipulative field experiments to ask how bee traits, plant traits, and network traits affect disease transmission. We found that larger worker bees transmit twice as likely to transmit C. bombi even though smaller workers had 50% more intense infections, suggesting that the higher foraging rates, defecation and survival of larger bees influences transmission more than infection intensity (Van Wyk et al 2021). In a separate experiment we manipulated a range of plant and floral traits in tents, finding that a wide range of traits affects pathogen transmission (Van Wyk et al 2022).
In 2021, this collaborative group received a new EEID grant funded by the USDA to assess how temporal dynamics influence pathogen transmission in plant-pollinator networks across the season. The UMass portion began in 2024, and Simon Pinilla-Gallego just joined our lab as a postdoc on this project. Stay tuned for updates!
