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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Ecological Applicati...arrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
Ecological Applications
Article . 2023 . Peer-reviewed
License: Wiley Online Library User Agreement
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Quantifying impacts of an environmental intervention using environmental DNA

Authors: Elizabeth Andruszkiewicz Allan; Ryan P. Kelly; Erin R. D'Agnese; Maya N. Garber‐Yonts; Megan R. Shaffer; Zachary J. Gold; Andrew O. Shelton;

Quantifying impacts of an environmental intervention using environmental DNA

Abstract

AbstractEnvironmental laws around the world require some version of an environmental‐impact assessment surrounding construction projects and other discrete instances of human development. Information requirements for these assessments vary by jurisdiction, but nearly all require an analysis of the biological elements of ecosystems. Amplicon‐sequencing—also called metabarcoding—of environmental DNA (eDNA) has made it possible to sample and amplify the genetic material of many species present in those environments, providing a tractable, powerful, and increasingly common way of doing environmental‐impact analysis for development projects. Here, we analyze an 18‐month time series of water samples taken before, during, and after two culvert removals in a salmonid‐bearing freshwater stream. We also sampled multiple control streams to develop a robust background expectation against which to evaluate the impact of this discrete environmental intervention in the treatment stream. We generate calibrated, quantitative metabarcoding data from amplifying the 12s MiFish mtDNA locus and complementary species‐specific quantitative PCR data to yield multispecies estimates of absolute eDNA concentrations across time, creeks, and sampling stations. We then use a linear mixed effects model to reveal patterns of eDNA concentrations over time, and to estimate the effects of the culvert removal on salmonids in the treatment creek. We focus our analysis on four common salmonid species: cutthroat trout (Oncorhynchus clarkii), coho salmon (Oncorhynchus kisutch), rainbow trout (Oncorhynchus mykiss), and sockeye salmon (Oncorhynchus nerka). We find that one culvert in the treatment creek seemed to have no impact while the second culvert had a large impact on fish passage. The construction itself seemed to have only transient effects on salmonid species during the two construction events. In the context of billions of dollars of court‐mandated road culvert replacements taking place in Washington State, USA, our results suggest that culvert replacement can be conducted with only minimal impact of construction to key species of management concern. Furthermore, eDNA methods can be an effective and efficient approach for monitoring hundreds of culverts to prioritize culverts that are required to be replaced. More broadly, we demonstrate a rigorous, quantitative method for environmental‐impact reporting using eDNA that is widely applicable in environments worldwide.

Related Organizations
Keywords

Rivers, Salmon, Oncorhynchus mykiss, Animals, Humans, Oncorhynchus kisutch, DNA, Environmental, Ecosystem

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
12
Top 10%
Average
Top 10%
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