Quantification of mesocosm fish and amphibian species diversity via environmental DNA metabarcoding

Abstract

Freshwater fauna are particularly sensitive to environmental change and disturbance. Management agencies frequently use fish and amphibian biodiversity as indicators of ecosystem health and a way to prioritize and assess management strategies. Traditional aquatic bioassessment that relies on capture of organisms via nets, traps and electrofishing gear typically has low detection probabilities for rare species and can injure individuals of protected species. Our objective was to determine whether environmental DNA (eDNA) sampling and metabarcoding analysis can be used to accurately measure species diversity in aquatic assemblages with differing structures. We manipulated the density and relative abundance of eight fish and one amphibian species in replicated 206‐L mesocosms. Environmental DNA was filtered from water samples, and six mitochondrial gene fragments were Illumina‐sequenced to measure species diversity in each mesocosm. Metabarcoding detected all nine species in all treatment replicates. Additionally, we found a modest, but positive relationship between species abundance and sequencing read abundance. Our results illustrate the potential for eDNA sampling and metabarcoding approaches to improve quantification of aquatic species diversity in natural environments and point the way towards using eDNA metabarcoding as an index of macrofaunal species abundance.

Document Details

Document Type
Pub Defense Publication
Publication Date
Jun 18, 2015
Source ID
10.1111/1755-0998.12433

Entities

People

  • Andrew R. Mahon
  • Brett P. Olds
  • Cameron R. Turner
  • Christopher L. Jerde
  • David M. Lodge
  • Gary A. Lamberti
  • Mark A. Renshaw
  • Michael E. Pfrender
  • Nathan T. Evans
  • Yiyuan Li

Organizations

  • Central Michigan University
  • United States Department of Defense
  • University of Notre Dame

Tags

Fields of Study

  • Environmental science

Readers

  • Aquatic Ecology
  • Computational Modeling and Simulation