UMD Theses and Dissertations

Permanent URI for this collectionhttp://hdl.handle.net/1903/3

New submissions to the thesis/dissertation collections are added automatically as they are received from the Graduate School. Currently, the Graduate School deposits all theses and dissertations from a given semester after the official graduation date. This means that there may be up to a 4 month delay in the appearance of a given thesis/dissertation in DRUM.

More information is available at Theses and Dissertations at University of Maryland Libraries.

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Author: search.filters.author.Avalos, GraceSubject: search.filters.subject.eDNA

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    REFINING METAGENETIC ENVIRONMENTAL DNA TECHNIQUES FOR SENSITIVE BEE COMMUNITY MONITORING
    (2023) Avalos, Grace; Richardson, Rodney T; Marine-Estuarine-Environmental Sciences; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    Molecular taxonomic detection is now widespread across the sciences, because of advances in direct PCR, improved marker selection, and increases in sequencing throughput. Facilitated by these advances in sequencing, methodological sensitivity of sample identification has improved substantially. Metagenetic techniques to infer what species are present in a sample by sequencing unknown samples and comparing them to known references has the potential to advance our understanding of biodiversity. Metagenetic analysis of environmental DNA (eDNA) represents a novel, non-lethal method for characterizing floral-associated arthropod communities. Diverse arthropod assemblages interact with flowers, and floral surfaces have been shown to harbor arthropod DNA. We performed metagenetic sequencing on eDNA isolated from flower samples and honey bee-collected pollen samples using multiple markers and compared the frequency and taxonomic breadth of eDNA detections across these genetic markers and substrate types. Understanding which markers and substrates are most effective for eDNA characterization of floral-associated arthropod communities will guide future research and enable low-risk detection of threatened or endangered arthropods.