ID:
publications-2484
Type:
Peer reviewed articles
Year:
2021
Authors:
Teja P. Muha,Ā Deiene Rodriguez-Barreto,Ā Richard O'Rorke,Ā Carlos Garcia de LeanizĀ andĀ Sofia Consuegra
Title:
Using eDNA Metabarcoding to Monitor Changes in Fish Community Composition After Barrier Removal
Venue/Journal:
Frontiers in Ecology and Evolution
DOI:
10.3389/fevo.2021.629217
Research type:
AI & Machine Learning
Water System:
Natural Water Bodies
Technical Focus:
Abstract:
Artificial instream barriers are a major cause of habitat fragmentation that reduce population connectivity and gene flow by limiting fish movements. To mitigate their impacts, obsolete barriers are increasingly been removed worldwide, but few barrier removal projects are monitored. We employed a powerful Before-After-Downstream-Upstream (BADU) approach using environmental DNA (eDNA) metabarcoding to examine the effects on fish community composition of removing a weir in the river Lugg (England) that had been suggested to have a detrimental effect on salmonid migration. We found no change in fish community diversity or relative abundance after the removal above or below the weir, but detected an important effect of sampling season, likely related to the species' life cycles. eDNA detected nine fish species that were also identified by electrofishing sampling and one additional species (Anguilla anguilla) that was missed by traditional surveys. Our results suggest that monitoring of barrier removal projects should be carried out to ensure that any ecological benefits are properly documented and that eDNA metabarcoding is a sensitive technique to monitor the effects of barrier removal.
Link with Projects:
689682
Link with Tools:
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