Seasonal variation in environmental DNA detection in sediment and water samples

PLoS One. 2018 Jan 19;13(1):e0191737. doi: 10.1371/journal.pone.0191737. eCollection 2018.

Abstract

The use of aquatic environmental DNA (eDNA) to detect the presence of species depends on the seasonal activity of the species in the sampled habitat. eDNA may persist in sediments for longer than it does in water, and analysing sediment could potentially extend the seasonal window for species assessment. Using the great crested newt as a model, we compare how detection probability changes across the seasons in eDNA samples collected from both pond water and pond sediments. Detection of both aquatic and sedimentary eDNA varied through the year, peaking in the summer (July), with its lowest point in the winter (January): in all seasons, detection probability of eDNA from water exceeded that from sediment. Detection probability of eDNA also varied between study areas, and according to great crested newt habitat suitability and sediment type. As aquatic and sedimentary eDNA show the same seasonal fluctuations, the patterns observed in both sample types likely reflect current or recent presence of the target species. However, given the low detection probabilities found in the autumn and winter we would not recommend using either aquatic or sedimentary eDNA for year-round sampling without further refinement and testing of the methods.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • DNA / analysis*
  • DNA / genetics
  • DNA / isolation & purification
  • Ecosystem
  • England
  • Environmental Monitoring / methods*
  • Geologic Sediments / analysis*
  • Ponds / analysis
  • Seasons
  • Triturus / genetics
  • Water / analysis*

Substances

  • Water
  • DNA

Grants and funding

We would like to dedicate this paper to Sir Martin Wood (FRS) and Lady Audrey Wood in the year of their 90th Birthdays for their contribution to science, technology and nature conservation. We would like to thank them for their financial support of their grandson, Andrew Buxton’s PhD project of which this paper is part. This work was also made possible with funding directly from the University of Kent where Professor Jim Groombridge and Professor Richard Griffiths, are academic staff. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.