TY - JOUR
T1 - Limited dispersion and quick degradation of environmental DNA in fish ponds inferred by metabarcoding
AU - Li, Jianlong
AU - Lawson Handley, Lori J.
AU - Harper, Lynsey R.
AU - Brys, Rein
AU - Watson, Hayley V.
AU - Di Muri, Cristina
AU - Zhang, Xiang
AU - Hänfling, Bernd
N1 - Funding Information:
This work is part of the PhD project of JL, who is supported by the University of Hull and the China Scholarship Council. We are particularly grateful to all staff (Alan Henshaw, Richard Pitman, Nick Gill, Dan Clark and James Rabjohns) of the National Coarse Fish Rearing Unit of the UK Environment Agency for their help with sampling and providing fish stock information, and Drs Christoph Hahn, Amir Szitenberg, Peter Shum, and Rob Donnelly for their assistance with bioinformatics analysis and laboratory work.
Publisher Copyright:
© 2019 The Authors. Environmental DNA published by John Wiley & Sons Ltd
PY - 2019/6/25
Y1 - 2019/6/25
N2 - Background: Environmental DNA (eDNA) metabarcoding is a promising tool for rapid, non-invasive biodiversity monitoring. Aims: In this study, eDNA metabarcoding is applied to explore the spatial and temporal distribution of fish communities in two aquaculture ponds and to evaluate the detection sensitivity of this tool for low-density species alongside highly abundant species. Materials & Methods: This study was carried out at two artificially stocked ponds with a high fish density following the introduction and removal of two rare fish species. Results & Discussion: When two rare species were introduced and kept at a fixed location in the ponds, eDNA concentration (i.e., proportional read counts abundance) of the introduced species typically peaked after two days. The increase in eDNA concentration of the introduced fish after 43 hrs may have been caused by increased eDNA shedding rates as a result of fish being stressed by handling, as observed in other studies. Thereafter, it gradually declined and stabilised after six days. These findings are supported by the highest community dissimilarity of different sampling positions being observed on the second day after introduction, which then gradually decreased over time. On the sixth day, there was no longer a significant difference in community dissimilarity between sampling days. The introduced species were no longer detected at any sampling positions on 48 hrs after removal from the ponds. eDNA is found to decay faster in the field than in controlled conditions, which can be attributed to the complex effects of environmental conditions on eDNA persistence or resulting in the vertical transport of intracellular DNA and the extracellular DNA absorbed by particles in the sediment. The eDNA signal and detection probability of the introduced species were strongest near the keepnets, resulting in the highest community variance of different sampling events at this position. Thereafter, the eDNA signal significantly decreased with increasing distance, although the signal increased slightly again at 85 m position away from the keepnets. Conclusions: Collectively, these findings reveal that eDNA distribution in lentic ecosystems is highly localised in space and time, which adds to the growing weight of evidence that eDNA signal provides a good approximation of the presence and distribution of species in ponds. Moreover, eDNA metabarcoding is a powerful tool for detection of rare species alongside more abundant species due to the use of generic PCR primers, and can enable monitoring of spatial and temporal community variance.
AB - Background: Environmental DNA (eDNA) metabarcoding is a promising tool for rapid, non-invasive biodiversity monitoring. Aims: In this study, eDNA metabarcoding is applied to explore the spatial and temporal distribution of fish communities in two aquaculture ponds and to evaluate the detection sensitivity of this tool for low-density species alongside highly abundant species. Materials & Methods: This study was carried out at two artificially stocked ponds with a high fish density following the introduction and removal of two rare fish species. Results & Discussion: When two rare species were introduced and kept at a fixed location in the ponds, eDNA concentration (i.e., proportional read counts abundance) of the introduced species typically peaked after two days. The increase in eDNA concentration of the introduced fish after 43 hrs may have been caused by increased eDNA shedding rates as a result of fish being stressed by handling, as observed in other studies. Thereafter, it gradually declined and stabilised after six days. These findings are supported by the highest community dissimilarity of different sampling positions being observed on the second day after introduction, which then gradually decreased over time. On the sixth day, there was no longer a significant difference in community dissimilarity between sampling days. The introduced species were no longer detected at any sampling positions on 48 hrs after removal from the ponds. eDNA is found to decay faster in the field than in controlled conditions, which can be attributed to the complex effects of environmental conditions on eDNA persistence or resulting in the vertical transport of intracellular DNA and the extracellular DNA absorbed by particles in the sediment. The eDNA signal and detection probability of the introduced species were strongest near the keepnets, resulting in the highest community variance of different sampling events at this position. Thereafter, the eDNA signal significantly decreased with increasing distance, although the signal increased slightly again at 85 m position away from the keepnets. Conclusions: Collectively, these findings reveal that eDNA distribution in lentic ecosystems is highly localised in space and time, which adds to the growing weight of evidence that eDNA signal provides a good approximation of the presence and distribution of species in ponds. Moreover, eDNA metabarcoding is a powerful tool for detection of rare species alongside more abundant species due to the use of generic PCR primers, and can enable monitoring of spatial and temporal community variance.
KW - community variances
KW - eDNA dynamics
KW - eDNA ecology
KW - fish monitoring
KW - ponds
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U2 - 10.1002/edn3.24
DO - 10.1002/edn3.24
M3 - Article
AN - SCOPUS:85076283300
SN - 2637-4943
VL - 1
SP - 238
EP - 250
JO - Environmental DNA
JF - Environmental DNA
IS - 3
ER -