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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Bibliographic Details
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
Subjects
agroecosystems
Apis mellifera
Application
APPLICATION ARTICLE
bee foraging landscape
Bees
Brassicaceae
expert opinion
field crops
Flowers
Flowers & plants
foraging
Fraxinus
Habitats
honey bee colonies
honey bees
Identification
internal transcribed spacers
landscapes
Microscopy
Nutrition research
Ohio
Oleaceae
palynology
Plant sciences
Pollen
pollen analysis
pollinator ecology
Pollinators
provenance
qualitative analysis
quantitative analysis
Rosaceae
Sapindaceae
spring
Taraxacum officinale
Taxonomy
trees
Ohio
United States > US
Apis mellifera
palynology
bee foraging landscape
pollinator ecology
pollen analysis
Fraxinus
Online AccessGet full text

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Abstract 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.
AbstractList 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.
• 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 midspring 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.
• 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 midspring 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.
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. • Pollen was collected from honey bee colonies in Madison County, Ohio, USA, during a two-week period in midspring and identified using microscopic methods and ITS2 metabarcoding. • 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. • 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.
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. •PREMISE OF THE STUDYMelissopalynology, 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. •Pollen was collected from honey bee colonies in Madison County, Ohio, USA, during a two-week period in midspring and identified using microscopic methods and ITS2 metabarcoding. •METHODSPollen was collected from honey bee colonies in Madison County, Ohio, USA, during a two-week period in midspring and identified using microscopic methods and ITS2 metabarcoding. •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. •RESULTSMetabarcoding 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. •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.DISCUSSIONFor 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.
• 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 midspring 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.
Author Johnson, Reed M
Sponsler, Douglas B
Richardson, Rodney T
Quijia, Juan O
Goodell, Karen
Lin, Chia-Hua
Author_xml – sequence: 1
  givenname: Rodney T
  surname: Richardson
  fullname: Richardson, Rodney T
  organization: Department of Entomology, The Ohio State University–Ohio Agricultural Research and Development Center, 1680 Madison Ave., Wooster, Ohio 44691 USA
– sequence: 2
  givenname: Chia-Hua
  surname: Lin
  fullname: Lin, Chia-Hua
  organization: Department of Entomology, The Ohio State University–Ohio Agricultural Research and Development Center, 1680 Madison Ave., Wooster, Ohio 44691 USA
– sequence: 3
  givenname: Douglas B
  surname: Sponsler
  fullname: Sponsler, Douglas B
  organization: Department of Entomology, The Ohio State University–Ohio Agricultural Research and Development Center, 1680 Madison Ave., Wooster, Ohio 44691 USA
– sequence: 4
  givenname: Juan O
  surname: Quijia
  fullname: Quijia, Juan O
  organization: Department of Entomology, The Ohio State University–Ohio Agricultural Research and Development Center, 1680 Madison Ave., Wooster, Ohio 44691 USA
– sequence: 5
  givenname: Karen
  surname: Goodell
  fullname: Goodell, Karen
  organization: Department of Evolution, Ecology and Organismal Biology, The Ohio State University, 1179 University Dr., Newark, Ohio 43023 USA
– sequence: 6
  givenname: Reed M
  surname: Johnson
  fullname: Johnson, Reed M
  organization: Department of Entomology, The Ohio State University–Ohio Agricultural Research and Development Center, 1680 Madison Ave., Wooster, Ohio 44691 USA
BackLink https://www.ncbi.nlm.nih.gov/pubmed/25606352$$D View this record in MEDLINE/PubMed
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2015 Richardson et al. Published by the Botanical Society of America 2015
Copyright_xml – notice: 2015 The Author(s)
– notice: 2015. This work is published under http://creativecommons.org/licenses/by-nc/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
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Issue 1
Keywords Apis mellifera
palynology
bee foraging landscape
pollinator ecology
pollen analysis
Fraxinus
Language English
License Attribution-NonCommercial
http://creativecommons.org/licenses/by-nc/4.0
This work is licensed under a Creative Commons Attribution License (CC-BY-NC-SA).
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Notes 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.
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Snippet Premise of the study: Melissopalynology, the identification of bee-collected pollen, provides insight into the flowers exploited by foraging bees. Information...
• Premise of the study: Melissopalynology, the identification of bee‐collected pollen, provides insight into the flowers exploited by foraging bees....
• Premise of the study: Melissopalynology, the identification of bee‐collected pollen, provides insight into the flowers exploited by foraging bees....
Melissopalynology, the identification of bee-collected pollen, provides insight into the flowers exploited by foraging bees. Information provided by...
• Premise of the study: Melissopalynology, the identification of bee-collected pollen, provides insight into the flowers exploited by foraging bees....
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SubjectTerms agroecosystems
Apis mellifera
Application
APPLICATION ARTICLE
bee foraging landscape
Bees
Brassicaceae
expert opinion
field crops
Flowers
Flowers & plants
foraging
Fraxinus
Habitats
honey bee colonies
honey bees
Identification
internal transcribed spacers
landscapes
Microscopy
Nutrition research
Ohio
Oleaceae
palynology
Plant sciences
Pollen
pollen analysis
pollinator ecology
Pollinators
provenance
qualitative analysis
quantitative analysis
Rosaceae
Sapindaceae
spring
Taraxacum officinale
Taxonomy
trees
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Title Application of ITS2 Metabarcoding to Determine the Provenance of Pollen Collected by Honey Bees in an Agroecosystem
URI http://www.bioone.org/doi/abs/10.3732/apps.1400066
https://onlinelibrary.wiley.com/doi/abs/10.3732%2Fapps.1400066
https://www.ncbi.nlm.nih.gov/pubmed/25606352
https://www.proquest.com/docview/2290242124
https://www.proquest.com/docview/1652392659
https://www.proquest.com/docview/1753434493
https://pubmed.ncbi.nlm.nih.gov/PMC4298230
Volume 3
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