Molecular sequencing and morphological identification reveal similar patterns in native bee communities across public and private grasslands of eastern North Dakota

Autoři: Brian Darby aff001;  Russ Bryant aff002;  Abby Keller aff001;  Madison Jochim aff001;  Josephine Moe aff001;  Zoe Schreiner aff001;  Carrie Pratt aff001;  Ned H. Euliss, Jr. aff002;  Mia Park aff001;  Rebecca Simmons aff001;  Clint Otto aff002
Působiště autorů: Department of Biology, University of North Dakota, Grand Forks, North Dakota, United States of America aff001;  U.S. Geological Survey, Northern Prairie Wildlife Research Center, Jamestown, North Dakota, United States of America aff002;  Humboldt State University, College of Natural Resources and Sciences, Arcata, North Dakota, United States of America aff003;  Department of Biological Sciences, North Dakota State University, Fargo, North Dakota, United States of America aff004
Vyšlo v časopise: PLoS ONE 15(1)
Kategorie: Research Article
doi: 10.1371/journal.pone.0227918


Bees play a key role in the functioning of human-modified and natural ecosystems by pollinating agricultural crops and wild plant communities. Global pollinator conservation efforts need large-scale and long-term monitoring to detect changes in species’ demographic patterns and shifts in bee community structure. The objective of this project was to test a molecular sequencing pipeline that would utilize a commonly used locus, produce accurate and precise identifications consistent with morphological identifications, and generate data that are both qualitative and quantitative. We applied this amplicon sequencing pipeline to native bee communities sampled across Conservation Reserve Program (CRP) lands and native grasslands in eastern North Dakota. We found the 28S LSU locus to be more capable of discriminating between species than the 18S SSU rRNA locus, and in some cases even resolved instances of cryptic species or morphologically ambiguous species complexes. Overall, we found the amplicon sequencing method to be a qualitatively accurate representation of the sampled bee community richness and species identity, especially when a well-curated database of known 28S LSU sequences is available. Both morphological identification and molecular sequencing revealed similar patterns in native bee community structure across CRP lands and native prairie. Additionally, a genetic algorithm approach to compute taxon-specific correction factors using a small subset of the most concordant samples demonstrated that a high level of quantitative accuracy could be possible if the specimens are fresh and processed soon after collection. Here we provide a first step to a molecular pipeline for identifying insect pollinator communities. This tool should prove useful for future national monitoring efforts as use of molecular tools becomes more affordable and as numbers of 28S LSU sequences for pollinator species increase in publicly-available databases.

Klíčová slova:

Bees – Genetic algorithms – Grasslands – Polymerase chain reaction – Ribosomal RNA – Sequence databases – Species diversity – Taxonomy


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