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Dryad

Relationship between eDNA concentration from metabarcoding method and stream fish density under field conditions

Cite this dataset

Nakagawa, Hikaru (2022). Relationship between eDNA concentration from metabarcoding method and stream fish density under field conditions [Dataset]. Dryad. https://doi.org/10.5061/dryad.zcrjdfngd

Abstract

Estimating abundance or biomass using eDNA metabarcoding is a powerful emerging tool that may provide an alternative to conventional laborious methods for biological monitoring. However, inferring aquatic macroorganism abundance or biomass using eDNA concentrations remains challenging, especially in lotic environments, because of several potential confounding factors. In this study, we tested whether quantitative eDNA metabarcoding that uses internal standard DNA can be used to estimate the abundance of four fish species. We collected eDNA samples and concurrently estimated fish densities using the conventional removal method in small tributaries in four seasons during a year. The effects of potential confounding factors, including the body mass of the individuals, water temperature, and discharge volume, were assessed using an allometric scaling model. We found an increasing trend of eDNA concentration against the increase in abundance across all species. In the most abundant species, a significant increase in the precision of predicted abundance was achieved by considering confounding factors, such as season and discharge. Although this study successfully determined the relationships between eDNA concentration and fish abundance under lotic field conditions, it also identified several limitations of quantitative eDNA metabarcoding. The relationship between eDNA concentration and fish abundance in rare species showed significant variances in the regression. More sequencing depth may be necessary to detect rare species sufficiently. The eDNA concentration estimation error effect was significant, particularly among the samples that showed the same abundance figures by direct capture estimation. The utilization of quantitative eDNA metabarcoding may be suitable for organisms that are expected to have a substantial variation in their population density. More comparative studies with various conventional methods would be informative, especially in lotic field environments, to overcome these limitations and achieve wider applications of eDNA metabarcoding in future research and monitoring.

Funding

Japan Society for the Promotion of Science, Award: JP19K15857