Volume 130, Issue 4 e2024JC021643
Research Article

Marine eDNA Production and Loss Mechanisms

Elizabeth Brasseale

Corresponding Author

Elizabeth Brasseale

School of Marine and Environmental Affairs, University of Washington, Seattle, WA, USA

Correspondence to:

E. Brasseale,

[email protected]

Contribution: Conceptualization, Methodology, Software, Validation, Formal analysis, ​Investigation, Writing - original draft, Writing - review & editing, Visualization

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Nicolaus Adams

Nicolaus Adams

Conservation Biology Division, Northwest Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, Seattle, WA, USA

Contribution: Methodology, Resources, Data curation, Writing - review & editing

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Elizabeth Andruszkiewicz Allan

Elizabeth Andruszkiewicz Allan

School of Marine and Environmental Affairs, University of Washington, Seattle, WA, USA

Contribution: Conceptualization, Methodology, Validation, Formal analysis, ​Investigation, Resources, Data curation, Writing - original draft, Writing - review & editing, Supervision, Project administration, Funding acquisition

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Eiren K. Jacobson

Eiren K. Jacobson

School of Mathematics and Statistics, University of St Andrews, St Andrews, Scotland

Contribution: Methodology, Software, Validation, Writing - review & editing

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Ryan P. Kelly

Ryan P. Kelly

School of Marine and Environmental Affairs, University of Washington, Seattle, WA, USA

Contribution: Conceptualization, Methodology, Software, Validation, Formal analysis, ​Investigation, Resources, Writing - original draft, Writing - review & editing, Supervision, Project administration, Funding acquisition

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Owen R. Liu

Owen R. Liu

School of Marine and Environmental Affairs, University of Washington, Seattle, WA, USA

Conservation Biology Division, Northwest Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, Seattle, WA, USA

Contribution: Software, Validation, Writing - review & editing

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Stephanie Moore

Stephanie Moore

Conservation Biology Division, Northwest Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, Seattle, WA, USA

Contribution: Methodology, Resources, Writing - review & editing

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Megan Shaffer

Megan Shaffer

School of Marine and Environmental Affairs, University of Washington, Seattle, WA, USA

Conservation Biology Division, Northwest Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, Seattle, WA, USA

Contribution: Conceptualization, Methodology, Resources, Data curation, Writing - original draft, Writing - review & editing

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Jilian Xiong

Jilian Xiong

School of Oceanography, University of Washington, Seattle, WA, USA

Contribution: Conceptualization, Methodology, Software, Validation, Formal analysis, Resources, Writing - original draft, Writing - review & editing

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Kim Parsons

Kim Parsons

Conservation Biology Division, Northwest Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, Seattle, WA, USA

Contribution: Conceptualization, Methodology, Resources, Data curation, Writing - review & editing, Supervision, Project administration, Funding acquisition

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First published: 24 April 2025

Abstract

Environmental DNA (eDNA) analysis is a technique for detecting organisms based on genetic material in environments such as air, water, or soil. Observed eDNA concentrations vary in space and time due to biological and environmental processes. Here, we investigate variability in eDNA production and loss by sampling water adjacent to a managed population of non-native cetaceans on a near-hourly timescale for 48 hr. We used diverse sampling approaches and modeling methods to describe time variability in observed eDNA concentrations and then compare the magnitude of production and loss mechanisms. We parsed production and loss in a conceptual box model and compared biological and physical loss rates using a decay experiment and a physical transport-and-diffusion tracer model. We then evaluated eDNA concentrations along a transect away from the animal enclosure in light of model parameter estimates. We conclude that eDNA production is best conceptualized using a time-varying mixed-state model, and biological losses are small relative to physical losses in the marine environment. Because physical loss is unsteady and nonlinear, tracer models are especially helpful tools to estimate it accurately.

Key Points

  • Atlantic bottlenose dolphin eDNA was sampled at near-hourly frequency, and concentrations varying by over three orders of magnitude

  • A model of background eDNA production with episodic larger eDNA production events best explained near-hourly variability

  • Little genetic material persisted hour to hour, and most eDNA loss was attributable to physical rather than biological processes

Plain Language Summary

Environmental DNA (eDNA) is the genetic material of animals, bacteria, or plants that can be found in air, soil, or water samples. Using eDNA for marine ecology is complicated, however, because animals may shed DNA at irregular rates and once shed, eDNA is moved by ocean currents and broken apart by microbes. To better understand the fate of eDNA, we sampled water repeatedly near an enclosure of non-native dolphins in Hood Canal, Washington to see how much eDNA concentrations changed hourly over 2 days. We compared models built on different explanations for dolphin eDNA variability. Observations were best explained by a model where dolphins shed DNA at steady background rate but could occasionally shed large amounts of eDNA (presumably through defecation). In that model, over half of eDNA was lost each hour. To distinguish biological and physical loss rates, we estimated degradation in the lab and ocean current transport and diffusion using an ocean model. The diffusion rate from the ocean model matched observed eDNA better than biological decay rates, which were much lower. By better understanding how eDNA is produced and where it goes in the ocean, we can better interpret our eDNA measurements to learn about marine ecosystems.

Data Availability Statement

The ESP, dolphin occupancy, and tide data and R NIMBLE model codes used for Part 1 are archived and available at https://zenodo.org/doi/10.5281/zenodo.12735445.