Data and code from: Evaluating eDNA metabarcoding techniques for pollinator community assessment in a field and controlled experiment

Pollinators play a critical role in ensuring the stability of food
systems, yet their populations are in decline. To better understand and
promote pollinator biodiversity, this study explored the use of
environmental DNA (eDNA) metabarcoding techniques to assess
plant–pollinator interactions. We conducted two experiments to optimize
eDNA metabarcoding strategies for detecting pollinators on flowering
plants. In the first experiment, we compared visual observations and eDNA
detection via Illumina sequencing to characterize pollinator visitation on
two native plant species in public and private green spaces across the
Richmond, Virginia metropolitan area. Our findings revealed notable
differences between the two methods, with visual surveys more sensitive to
Hymenoptera and eDNA more sensitive to plant pests and other organisms. We
devised a second experiment in a controlled environment at the Lewis
Ginter Botanical Garden butterfly exhibit. Here, we tested different
sampling strategies, primer pairs, and DNA sequencing platform (using
Oxford Nanopore Technology). Despite detecting two butterfly species
present in the exhibit, the eDNA metabarcoding showed limited sensitivity
to the expected Lepidoptera. Our results indicate that while eDNA
metabarcoding can detect a broader range of eukaryotic organisms, it may
not be as effective for monitoring specific pollinator taxa like
Hymenoptera and Lepidoptera. Factors such as sample type, primer bias,
sequencing platform, and bioinformatics pipeline may impact detection
outcomes. This study underscores the need for combining traditional
monitoring techniques with eDNA metabarcoding to gain a comprehensive
understanding of plant–pollinator interactions and improve pollinator
conservation efforts.