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BeeDNA : Microfluidic environmental DNA metabarcoding as a tool for connecting plant and pollinator communities
Author(s) -
Harper Lynsey R.,
Niemiller Matthew L.,
Benito Joseph B.,
Paddock Lauren E.,
Knittle E.,
MolanoFlores Brenda,
Davis Mark A.
Publication year - 2023
Publication title -
environmental dna
Language(s) - English
Resource type - Journals
ISSN - 2637-4943
DOI - 10.1002/edn3.370
Subject(s) - pollinator , environmental dna , biodiversity , biology , metagenomics , ecology , ecosystem services , pollination , ecosystem , pollen , biochemistry , gene
Abstract Pollinators are declining globally, and this loss can reduce plant reproduction, erode critical ecosystem services and resilience, and drive economic losses. Monitoring pollinator biodiversity trends is essential for adaptive conservation and management, but conventional surveys are often costly, time‐consuming, and requires considerable taxonomic expertise. Environmental DNA (eDNA) metabarcoding surveys are booming due to their rapidity, nondestructiveness, and cost efficiency. Microfluidic technology allows multiple primer sets from different markers to be used in eDNA metabarcoding for more comprehensive inventories, minimizing associated primer bias. We evaluated microfluidic eDNA metabarcoding for pollinator community monitoring in both controlled greenhouse and natural field settings. Using a variety of sampling, preservation, and extraction methods, we assessed pollinator communities with a number of markers using microfluidic metabarcoding. In greenhouse experiments, microfluidic eDNA metabarcoding detected the target bumblebee in two of four focal flower species as well as greenhouse insects in all focal flower species. In the field, numerous common regional arthropods, including some directly observed, were detected. Pollinator detection was maximized using whole flower heads preserved in ATL buffer and extracted with a modified Qiagen® DNeasy protocol for amplification with COI primers. eDNA surveillance could enhance pollinator assessment by detecting protected and endangered species and being more applicable to remote, inaccessible locations, whilst reducing survey time, effort, and expense. Microfluidic eDNA metabarcoding requires optimization to address remaining efficacy concerns, but this approach shows potential in revealing complex networks underpinning critical ecosystem functions and services, enabling more accurate assessments of ecosystem resilience.

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