River ecosystems are facing a deepening biodiversity crisis. Developing robust biotic indicators to assess ecological status across large spatial scales are important. In the subtropical Liuxi River of southern China, 34 fish indicators, including 4 genera and 30 species, were selected from 108 fish species by linear discriminant analysis. These indicators were combined into 18 groups and assigned scores according to their species-specific requirements for food resources and habitat patterns. The ecological and trophic functioning of optimized indicators can reflect not only the community diversity and food web properties but also the environmental quality of the ecosystem. Three formulas for calculating the index of fish indicators ( IFI) were developed based on the scoring of each indicator and weighted by relative abundance (individual number, i.e., IFIN) and relative biomass (wet weight, i.e., IFIB). Spearman correlation analysis showed that IFIB exhibited a more powerful explanation of biodiversity and environmental factors than IFIN and unweighted IFI. Therefore, we conclude that IFIB has absolute advantages in constructing an indicator-based environmental evaluation system since it contains comprehensive information on biology and ecology. In the future, the application of indicator scoring methods can contribute greatly to the conservation and development of aquatic ecosystems.

Fish play vital roles in river ecosystems; however, traditional investigations of fish usually cause certain ecological damage. Extracting DNA from aquatic environments and identifying DNA sequences offers an alternative, non-invasive approach for detecting fish species. In this study, environmental DNA (eDNA), coupled with PCR and next-generation sequencing, and electrofishing were used to compare their effects in identifying fish community characteristics. In three subtropical rivers of southern China, fish specimens and eDNA in water were collected from headwaters to estuaries. Both eDNA OTU richness and individual abundance (including number and biomass) could group 38 sampling sites into eight spatial zones with significant differences in local fish community composition. Compared with the order-/family-level grouping, the genus-/species-level grouping could more accurately recognize the differences between upstream zones I − III, midstream zones IV − V, and downstream zones VI – VIII. From headwaters to estuary, two environmental gradients significantly influenced the longitudinal distribution of fish species, including the first gradient composed of habitat and physical water parameters and the second gradient composed of chemical water parameters. The high regression coefficient of alpha diversity between eDNA and electrofishing methods as well as the accurate recognition of dominant, alien, and biomarker species at each spatial zone indicated that eDNA could characterize fish community attributes at a similar level of traditional approach. Generally, our results demonstrated that eDNA metabarcoding can be used as an effective tool in revealing fish composition and diversity, which is important for using the eDNA technique in aquatic field monitoring.