Monitoring fish communities through environmental DNA metabarcoding in the fish pass system of the second largest hydropower plant in the world

Abstract The Itaipu Hydroelectric Power Plant is the second largest in the world in power generation. The artificial barrier created by its dam imposes an obstacle for fish migration. Thus, in 2002, a fish pass system, named Piracema Channel, was built to allow fish to access areas upstream of the r...

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Autores principales: Giorgi Dal Pont, Camila Duarte Ritter, Andre Olivotto Agostinis, Paula Valeska Stica, Aline Horodesky, Nathieli Cozer, Eduardo Balsanelli, Otto Samuel Mäder Netto, Caroline Henn, Antonio Ostrensky, Marcio Roberto Pie
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2021
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Acceso en línea:https://doaj.org/article/c958b3acc126485093e76187115f49f5
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Sumario:Abstract The Itaipu Hydroelectric Power Plant is the second largest in the world in power generation. The artificial barrier created by its dam imposes an obstacle for fish migration. Thus, in 2002, a fish pass system, named Piracema Channel, was built to allow fish to access areas upstream of the reservoir. We tested the potential of environmental DNA metabarcoding to monitor the impact of both the dam and associated fish pass system in the Paraná River fish communities and to compare it with traditional monitoring methods. Using a fragment of the 12S gene, we characterized richness and community composition based on amplicon sequence variants, operational taxonomic units, and zero-radius OTUs. We combined GenBank and in-house data for taxonomic assignment. We found that different bioinformatics approaches showed similar results. Also, we found a decrease in fish diversity from 2019 to 2020 probably due to the recent extreme drought experienced in southeastern Brazil. The highest alpha diversity was recorded in the mouth of the fish pass system, located in a protected valley with the highest environmental heterogeneity. Despite the clear indication that the reference databases need to be continuously improved, our results demonstrate the analytical efficiency of the metabarcoding to monitor fish species.