Application of ITS2 Metabarcoding to Determine the Provenance of Pollen Collected by Honey Bees in an Agroecosystem

Premise of the study: Melissopalynology, the identification of bee-collected pollen, provides insight into the flowers exploited by foraging bees. Information provided by melissopalynology could guide floral enrichment efforts aimed at supporting pollinators, but it has rarely been used because trad...

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Published inApplications in plant sciences Vol. 3; no. 1
Main Authors Richardson, Rodney T, Lin, Chia-Hua, Sponsler, Douglas B, Quijia, Juan O, Goodell, Karen, Johnson, Reed M
Format Journal Article
LanguageEnglish
Published United States Botanical Society of America 01.01.2015
John Wiley & Sons, Inc
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Summary:Premise of the study: Melissopalynology, the identification of bee-collected pollen, provides insight into the flowers exploited by foraging bees. Information provided by melissopalynology could guide floral enrichment efforts aimed at supporting pollinators, but it has rarely been used because traditional methods of pollen identification are laborious and require expert knowledge. We approach melissopalynology in a novel way, employing a molecular method to study the pollen foraging of honey bees (Apis mellifera) in a landscape dominated by field crops, and compare these results to those obtained by microscopic melissopalynology. Methods: Pollen was collected from honey bee colonies in Madison County, Ohio, USA, during a two-week period in mid-spring and identified using microscopic methods and ITS2 metabarcoding. Results: Metabarcoding identified 19 plant families and exhibited sensitivity for identifying the taxa present in large and diverse pollen samples relative to microscopy, which identified eight families. The bulk of pollen collected by honey bees was from trees (Sapindaceae, Oleaceae, and Rosaceae), although dandelion (Taraxacum officinale) and mustard (Brassicaceae) pollen were also abundant. Discussion: For quantitative analysis of pollen, using both metabarcoding and microscopic identification is superior to either individual method. For qualitative analysis, ITS2 metabarcoding is superior, providing heightened sensitivity and genus-level resolution.
Bibliography:http://dx.doi.org/10.3732%2Fapps.1400066
The authors thank J. Wenger, E. E. Wilson, C. S. Sidhu, J. Wallace, B. Klips, A. D. Wolfe, and anonymous reviewers for discussion; N. Douridas for site access; G. Cobb for help with sample processing; M. E. Hernandez‐Gonzalez and the Ohio Agricultural Research and Development Center Molecular and Cellular Imaging Center staff for technical support; and the Ohio Supercomputing Center for computing time. This study was funded by the Pollinator Partnership's Corn Dust Research Consortium grant to R.M.J. and an Ohio State University–Newark Scholarly Activity Grant to K.G.
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The authors thank J. Wenger, E. E. Wilson, C. S. Sidhu, J. Wallace, B. Klips, A. D. Wolfe, and anonymous reviewers for discussion; N. Douridas for site access; G. Cobb for help with sample processing; M. E. Hernandez-Gonzalez and the Ohio Agricultural Research and Development Center Molecular and Cellular Imaging Center staff for technical support; and the Ohio Supercomputing Center for computing time. This study was funded by the Pollinator Partnership’s Corn Dust Research Consortium grant to R.M.J. and an Ohio State University–Newark Scholarly Activity Grant to K.G.
ISSN:2168-0450
2168-0450
DOI:10.3732/apps.1400066