D3482: Assessing pollinator forage by genetic metabarcoding: Past insights and future applications

Tuesday, November 12, 2024

9:00 AM – 5:00 PM MST

Location: Phoenix Convention Center, Exhibit Hall 6, PCC

Presenting Author(s)

SC

Scott Cornman

U.S. Geological Survey
Fort Collins, Colorado

Co-Author(s)

CO

Clint Otto

Research Ecologist
U.S. Geological Survey
Jamestown, North Dakota
DI

Deborah Iwanowicz

United States Geological Survey
Kearneysville, West Virginia
MS

Michael Simanonok

United States Geological Survey
Jamestown, North Dakota
AS

Autumn Smart

Research Assistant Professor
University of Nebraska
Lincoln, Nebraska
TS

Tamara Smith

United States Fish and Wildlife Service
Minneapolis, Minnesota
Elaine Evans (she/they)

Extension Professor
University of Minnesota
Saint Paul, Minnesota

Pollen forage availability, diversity, and quality are important determinants of insect-pollinator distributions. In support of diverse stakeholders, we have been applying genetic methods to characterize pollen mixtures taken from bees, apiaries, and nests to better understand the ecology of managed and wild species, including the endangered rusty patched bumble bee (Bombus affinis). These ‘metabarcode’ methods compare favorably with morphological taxonomy, have high throughput, and are readily archived for public reuse and reanalysis. Quantitative models and experiments can utilize pollen composition data to identify landscape characteristics, plant communities, and management practices that support pollinator health. Here we present an overview of past and ongoing pollen metabarcoding data, emphasizing methods development and a broadening of their application to understudied taxa.