Title
Species-level ichthyoplankton dynamics for 97 fishes in two major river basins of the Amazon using quantitative metabarcoding
Date Issued
01 March 2022
Access level
open access
Resource Type
journal article
Publisher(s)
John Wiley and Sons Inc
Abstract
The Amazon basin holds the world's largest freshwater fish diversity. Information on the intensity and timing of reproductive ecology of Amazonian fish is scant. We use a metabarcoding method by capture using a single probe to quantify species-level ichthyoplankton dynamics. We sampled the Marañón and the Ucayali rivers in Peru monthly for 2 years. We identified 97 species that spawned mainly during the flood start, the flood end or the receding periods, although some species had spawning activity in more than one period. This information was new for 40 of the species in the Amazon basin and 80 species in Peru. Most species ceased spawning for a month during a strong hydrological anomaly in January 2016, demonstrating the rapidity with which they react to environmental modifications during the breeding season. We also document another unreported event in the Amazon basin, the inverse phenology of species belonging to one genus (Triportheus). Overall larval flow in the Marañón was more than twice that of the Ucayali, including for most commercial species (between two and 20 times higher), whereas the Ucayali accounts for ~80% of the fisheries landings in the region. Our results are discussed in the light of the main anthropogenic threats to fishes, hydropower dam construction and the Hidrovía Amazónica, and should serve as a pre-impact baseline.
Start page
1627
End page
1648
Volume
31
Issue
6
Language
English
OCDE Knowledge area
Ecología Biología marina, Biología de agua dulce, Limnología
Scopus EID
2-s2.0-85106324208
PubMed ID
Source
Molecular Ecology
ISSN of the container
09621083
Sponsor(s)
The two years of larvae collection in the Marañón and Ucayali rivers were financed by the Concejo Nacional de Ciencia y Tecnología (CONCYTEC) of Peru, who through the Fondo Nacional de Desarrollo Científico, Tecnológico y de Innovación Tecnológica (FONDECYT), project 088‐2014‐FONDECYT‐DE. The LMI EDIA and UMR DIADE financed the metabarcoding analyses. The authors acknowledge the IRD itrop HPC (South Green Platform) at IRD Montpellier for providing HPC resources that contributed to the research results reported within this paper ( https://bioinfo.ird.fr/ ‐ http://www.southgreen.fr ). We are also grateful to Domingo García for his assistance during field work. We are also grateful to Juan José Palacios Vega (IIAP) for the elaboration of Figure 1 .
Sources of information: Directorio de Producción Científica Scopus