skip to main content
Language:
Search Limited to: Search Limited to: Resource type Show Results with: Show Results with: Index

Interannual bumble bee abundance is driven by indirect climate effects on floral resource phenology

Ogilvie, Jane E. ; Griffin, Sean R. ; Gezon, Zachariah J. ; Inouye, Brian D. ; Underwood, Nora ; Inouye, David W. ; Irwin, Rebecca E.

Ecology Letters, December 2017, Vol.20(12), pp.1507-1515 [Peer Reviewed Journal]

Full text available

View all versions
Citations Cited by
  • Title:
    Interannual bumble bee abundance is driven by indirect climate effects on floral resource phenology
  • Author: Ogilvie, Jane E. ; Griffin, Sean R. ; Gezon, Zachariah J. ; Inouye, Brian D. ; Underwood, Nora ; Inouye, David W. ; Irwin, Rebecca E.
  • Description: Climate change can influence consumer populations both directly, by affecting survival and reproduction, and indirectly, by altering resources. However, little is known about the relative importance of direct and indirect effects, particularly for species important to ecosystem functioning, like pollinators. We used structural equation modelling to test the importance of direct and indirect (via floral resources) climate effects on the interannual abundance of three subalpine bumble bee species. In addition, we used long‐term data to examine how climate and floral resources have changed over time. Over 8 years, bee abundances were driven primarily by the indirect effects of climate on the temporal distribution of floral resources. Over 43 years, aspects of floral phenology changed in ways that indicate species‐specific effects on bees. Our study suggests that climate‐driven alterations in floral resource phenology can play a critical role in governing bee population responses to global change.
  • Is Part Of: Ecology Letters, December 2017, Vol.20(12), pp.1507-1515
  • Identifier: ISSN: 1461-023X ; E-ISSN: 1461-0248 ; DOI: 10.1111/ele.12854
  • Subjects: Bumble Bee ; Bombus ; Climate Change ; Floral Resources ; Phenology ; Pollinator ; Precipitation ; Snowmelt ; Structural Equation model

Searching Remote Databases, Please Wait