, Volume 176, Issue 4, pp 1033–1045 | Cite as

High-altitude multi-taskers: bumble bee food plant use broadens along an altitudinal productivity gradient

  • Nicole E. Miller-StruttmannEmail author
  • Candace Galen
Plant-microbe-animal interactions - Original research


We use an extensive historical data set on bumble bee host choice collected almost 50 years ago by L. W. Macior (Melanderia 15:1–59, 1974) to examine how resource partitioning by bumble bees varies over a 2,700-m altitudinal gradient at four hierarchical scales: individual, colony, species and community. Bumble bee behavior, resource overlap between castes, and plant-bumble bee networks change with altitude in accordance with tightening temporal constraints on flowering and colony growth in alpine habitats. Individual bees were more likely to collect pollen from multiple sources at high altitude. Between-caste foraging niche overlap increased with altitude. Similarly, alpine forager networks were more highly nested than either subalpine or montane networks due to increased asymmetric specialization. However, interspecific resource partitioning showed a more complex spatial pattern with low niche overlap at intermediate altitude (subalpine) compared to montane (disturbed) and alpine (unproductive) sites. Results suggest that spatial variation in interspecific resource partitioning is driven by a shift in the behavior of long-tongued bumble bees. Long-tongued bumble bees specialized in the subalpine but generalized in montane and alpine zones. Our reanalysis of Macior’s data shows that bumble bee behavior varies substantially with altitude influencing plant-bumble bee interaction networks. Results imply that pollination services to alpine host plants will change dramatically as subalpine species with unique foraging strategies move upward under global warming.


Alpine bumble bees Niche partitioning Generalization Productivity Bombus 



We acknowledge L. Walter Macior for his meticulous contributions to the understanding of Rocky Mountain bumble bees and their food plants. We thank R. Holdo for advice on implementing the network analyses in R Statistical Software. Anonymous reviewers were especially helpful in improving the manuscript. This research was supported with funding from NSF grant 1045322.

Supplementary material

442_2014_3066_MOESM1_ESM.pdf (1.3 mb)
Supplementary material 1 (PDF 1295 kb)


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© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  1. 1.Division of Biological SciencesUniversity of MissouriColumbiaUSA

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