Fine-tuning the performance of abundance estimation based on environmental DNA (eDNA) focusing on eDNA particle size and marker length

Reliable abundance estimation is a primary challenge in environmental DNA (eDNA) analysis, which has been addressed by considering the effects of eDNA transport and degradation. However, these eDNA spatial dynamics depend on the cellular and molecular structure of eDNA, with its persistence state (particle size and DNA fragment length) being essential for improved abundance estimation. To address the issue, we used datasets obtained from two types of aquarium experiments (targeting zebrafish [Danio rerio] and Japanese jack mackerel [Trachurus japonicus]) and compared the relationships between eDNA concentration and species abundance among different eDNA size fractions and target marker lengths. We reared the fish in experimental tanks with different individual numbers or biomass densities, filtered rearing water using different pore size filters, and quantified eDNA concentrations targeting different fragment lengths or genetic regions. Consequently, both experiments showed that the accuracy and sensitivity in abundance estimation were improved (i.e., R-2 values and slopes of linear regressions increased) when targeting eDNA at the 3- to 10 mu m size fraction. On the contrary, targeting eDNA at the >10 mu m size fraction yielded a lower R-2 value. This result indicates that the relationship between eDNA concentration and species abundance can be worsened when extremely larger size fractions are targeted. Conversely, the target marker length negatively affected the R-2 value. This study proposes that the relationship between eDNA concentration and species abundance relies on the complex interactions between the particle size, persistence, and spatial heterogeneity of eDNA in water.

Automated summary

This study investigates the effects of eDNA particle size and DNA fragment length on species abundance estimation. The results show that targeting eDNA at the 3-10 μm size fraction improves accuracy and sensitivity, while targeting larger size fractions yields lower accuracy.