Unraveling fish diversity and assembly patterns in a temperate river: Evidence from environmental DNA metabarcoding and morphological data

Abstract

The loss of freshwater biodiversity has drawn greater attention to fish diversity and community assembly patterns. However, traditional survey methods, such as ground cages and electrofishing, may cause damage to fish communities and have become increasingly unsuitable for frequent and large-scale fish diversity surveys. In this study, environmental DNA (eDNA) metabarcoding and morphological data were both used to investigate the distribution and diversity of fish communities in the Taizi River basin, a temperate river in Northeast China, and the fish diversity and assembly patterns were investigated by using the null model. The results showed that a total of 7 orders, 17 families, 49 genera and 56 species were detected by the eDNA metabarcoding (6 orders, 15 families, 40 genera and 45 species) and morphological method (6 orders, 10 families, 31 genera and 34 species), and the eDNA method had a higher detection probability. Cypriniformes was detected most frequently, followed by Perciformes. Principal coordinate analysis revealed that fish communities in the Taizi River exhibited different spatial structures between the upper and lower reaches, with fish sensitive to environmental changes mostly found in the upper reaches and higher fish richness in the same area. The beta diversity in the upper reaches was higher than that in the lower reaches. The null model results showed the main factor that affected the distribution of fish in the Taizi River is the stochastic processes. Among the deterministic processes, the main environmental filter factors affecting fish community structure include total phosphorus, biochemical oxygen demand and temperature. We also confirm that eDNA metabarcoding has a higher detection rate compared to traditional survey methods, so it is feasible for freshwater ecosystem and fish resource monitoring. Therefore, the utilization of eDNA metabarcoding can effectively enhance monitoring efficiency and minimize interference with water bodies.