Estimating fish alpha- and beta-diversity along a small stream with environmental DNA metabarcoding

Yiyuan Li,Michael E Pfrender,David M Lodge,Gary A Lamberti,Nathan T Evans,Mark A Renshaw,Brett P Olds,Christopher L Jerde,Kristy Deiner,Arial J Shogren

doi:10.3897/mbmg.2.24262

Abstract

Environmental DNA (eDNA) metabarcoding has been increasingly applied to biodiversity surveys in stream ecosystems. In stream networks, the accuracy of eDNA-based biodiversity assessment depends on whether the upstream eDNA influx affects downstream detection. Biodiversity assessment in low-discharge streams should be less influenced by eDNA transport than in high-discharge streams. We estimated α- and β-diversity of the fish community from eDNA samples collected in a small Michigan (USA) stream from its headwaters to its confluence with a larger river. We found that α-diversity increased from upstream to downstream and, as predicted, we found a significant positive correlation between β-diversity and physical distance (stream length) between locations indicating species turnover along the longitudinal stream gradient. Sample replicates and different genetic markers showed similar species composition, supporting the consistency of the eDNA metabarcoding approach to estimate α- and β-diversity of fishes in low-discharge streams.

Highlights

Freshwater fishes provide vital ecosystem services to humans including protein, recreation (McIntyre et al 2016) and food web regulation (Holmlund and Hammer 1999)
In these Operational Taxonomic Units (OTUs), 43, 79 and 36 OTUs were identified as vertebrates with hidden Markov models (HMMs) filtering
We found a positive correlation between β-diversity amongst sample sites and stream distance, indicating our site sampling scheme generated sufficient statistical power to infer the patterns of fish community similarity within Eagle Creek

Summary

Introduction

Freshwater fishes provide vital ecosystem services to humans including protein, recreation (McIntyre et al 2016) and food web regulation (Holmlund and Hammer 1999). Fish diversity in rivers is traditionally assessed using a variety of census methods including netting, trapping and electrofishing. The accuracy of these methods relies heavily on the intensity of sampling efforts and the susceptibility of species and individuals to capture (Bonar et al 2009; Evans et al 2016). As a result of low sampling efficiencies, traditional sampling methods often underestimate true fish species diversity (Evans and Lamberti 2017; Olds et al 2016) leading to biased metrics of ecosystem health.

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Conclusion