DOI: 10.5061/dryad.j0zpc86tc
title: Data and code from: Evaluating eDNA metabarcoding techniques for pollinator community assessment in a field and controlled experiment

description: 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.
description: # Data and code from: Evaluating eDNA metabarcoding techniques for
 pollinator community assessment in a field and controlled experiment
 Dataset DOI: [10.5061/dryad.j0zpc86tc](10.5061/dryad.j0zpc86tc) ##
 Description of the data and file structure This study explored the use of
 environmental DNA (eDNA) metabarcoding techniques to assess
 plant-pollinator interactions. We conducted two experiments: 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 (called Pollinator Biodiversity Field Survey).
 For the second experiment, we sampled in a controlled environment at the
 Lewis Ginter Botanical Garden butterfly exhibit, tested two primers and
 used Oxford Nanopore Technology for DNA sequencing (called Butterfly
 Exhibit Survey). ### Files and variables #### File:
 ButterflyExhibitData_071425.xlsx **Description:** The output of
 sequencing, clustering, and matching OTUs to taxa for the Butterfly
 Exhibit Survey. There are two tabs, one tab for each primer used (Hebert
 and Folmer, see text). ##### Variables * sample is the name of each sample
 * sample type is where the sample came from [fruit, flower (swab or whole
 flower), bark] * flower is species of flower sampled * abundance is read
 number * cluster ID is cluster OTU * pident is percent identity of cluster
 sequence to blastn taxon * length is length of sequence matched * mismatch
 is number of SNP mismatches * gapopen is number of gaps in alignment *
 bitscore is alignment score * Acc is Accession number OTU matched to *
 Kingdom, Phylum, Class, Order, Family, Genus, Species are identifiers of
 OTU * Taxon is the final Taxa assigned after accounting for rules of
 assignment (length and percent identity, see text) #### File:
 Manuscript_code.R **Description:** The R code used for statistical
 analysis and plot creation. #### File: PollBiodiversityData_071425.xlsx
 **Description:** The output of sequencing, clustering, and matching OTUs
 to taxa for the Pollinator Biodiversity Field Survey. There are four tabs.
 The first 'VisualPA' is the presence/absence data for visual
 observations of pollinator interactions (includes site name, plant name
 and taxon to lowest id). The tab called 'eDNA_Liatris_all'
 include all OTUs that matched given the length and percent identity
 threshold noted in the text, filtered to Eukaryotes for the samples
 swabbed on plant *Liatris spicata*. The tab called
 'eDNA_Pycnanthemum_all' include all OTUs that matched given the
 length and percent identity threshold noted in the text, filtered to
 Eukaryotes. The tab called 'eDNA_arthropoda' combines OTUs from
 both plant species, filtered to length, percent identity, and to Phylum
 Arthropoda. ##### Variables * Sample is described by L/P for which plant,
 Site #, Flower # * Site is what site sample was swabbed * Flower is flower
 swabbed * DNA_Sequence is the OTU cluster * Abundance/Reads is the read
 number of that OTU cluster * pident is percent identity of OTU matched to
 taxa * length is read length * mismatch is number of SNP mismatches *
 gapopen is number of gaps in alignment * evalue is match probability due
 to random chance * bitscore is the alignment score * Acc is Accession
 number OTU matched to * Kingdom, Phylum, Class, Order, Family, Genus,
 Species are identifiers of OTU * Taxon is the final Taxa assigned after
 accounting for rules of assignment (length and percent identity, see text)
 ## Code/software RStudio and R were used to write code for statistical
 analysis. See code, packages, etc. in file called 'Manuscript
 code'.