Evaluating eDNA Metabarcoding Techniques for Pollinator Community Assessment in a Field and Controlled Experiment

Abstract

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.