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      Improving the detection of rare native fish species in environmental DNA metabarcoding surveys

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      ARPHA Conference Abstracts

      Pensoft Publishers

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          Abstract

          The presence of threatened or endangered species often strongly influences management and conservation decisions. Within the Murray–Darling Basin (MDB), Australia, the presence of threatened native fish affects the management and allocation of water resources. These decisions are currently based on traditional fisheries data and a predictive MaxEnt model. However, it is important to verify the model's predictive power given the implication it may have, but this requires methods with a high detection sensitivity for rare species. Although the use of environmental DNA (eDNA) metabarcoding achieves a higher detection sensitivity compared with traditional methods, earlier surveys in the MDB have shown that the highly abundant and invasive common carp (Cyprinus carpio) can reduce detection probabilities for rare species. Consequently, a polymerase chain reaction (PCR) blocking primer designed to block the amplification of carp eDNA could increase the detection probabilities for rare native species while simultaneously reducing the required sampling effort and survey costs. Although PCR blocking primers are often used in ancient DNA and dietary studies, no aquatic eDNA metabarcoding study to date has evaluated the potential benefits of using PCR blocking primers. A laboratory and field‐based pilot study was used to address this knowledge gap and assess the impact of a blocking primer on the detection probabilities of native species and the minimum sampling effort required. Results showed that the inclusion of the blocking primer increased the detection probabilities for native species by 10–20% and reduced the minimum required sampling effort by 25–50%. These findings provide important insights into possible methods for optimizing eDNA metabarcoding surveys for the detection of rare aquatic species.

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          Author and article information

          Journal
          ARPHA Conference Abstracts
          ACA
          Pensoft Publishers
          2603-3925
          March 04 2021
          March 04 2021
          : 4
          Article
          10.3897/aca.4.e65387
          © 2021

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