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Inference of genetic marker concentrations from field surveys to detect environmental DNA using Bayesian updating

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  • Martin T Schultz

Abstract

Field studies to detect environmental DNA (eDNA) can be undertaken to infer the presence of a rare or cryptic species in a water body. These studies are implemented by collecting water samples from the water body, processing those samples to isolate genetic material contained in the water sample, and using a laboratory assay to find a species-specific genetic marker within a sample of the genetic material. To date, conventional polymerase chain reaction (PCR) has been one of the most widely used assays in field studies to detect eDNA. This assay is strictly a test for the presence of the genetic marker. It provides no estimate of the concentration of the target genetic marker in the sample or in the environment. Understanding the concentration of a target marker in the environment is a critical first step toward using the results of eDNA field surveys to support inferences about the location and strength of eDNA sources. In this study, the results of eDNA field surveys are combined with a model of the sensitivity of the field survey methods to estimate target marker concentrations using Bayesian updating. The method is demonstrated for Asian carp in the Chicago Area Waterway System (CAWS) using the results of field surveys for eDNA carried out during the period 2009 through 2012, a four-year period during which more than 5,800 two-liter water samples were collected and analyzed using PCR. Concentrations of bighead carp (Hypophthalmichthys nobilis) and silver carp (Hypophthalmichthys molitrix) eDNA are estimated for twenty hydrologic reaches of the CAWS. This study also assesses the sensitivity of these concentration estimates to evidentiary criteria that limit what evidence is used in Bayesian updating based on requirements for sampling intensity and frequency.

Suggested Citation

  • Martin T Schultz, 2018. "Inference of genetic marker concentrations from field surveys to detect environmental DNA using Bayesian updating," PLOS ONE, Public Library of Science, vol. 13(1), pages 1-19, January.
  • Handle: RePEc:plo:pone00:0190603
    DOI: 10.1371/journal.pone.0190603
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