Environmental DNA (eDNA) has emerged as a promising tool for aquatic biodiversity monitoring, yet its collection in lentic ecosystems remains technically constrained by filtration capacity and field logistics. In this study, we applied a novel eDNA concentration system, QuickConcTM, to evaluate freshwater mussel diversity in lakes, and compared its performance with the conventional GF/F filtration method. Water samples were collected from four reservoirs at surface, mid, bottom, and waterside layers, and processed using both filtration techniques. Metabarcoding of mitochondrial 16S rDNA revealed that QuickConcTM captured a higher average number of amplicon sequence variants (ASVs) and exhibited greater species richness and diversity indices (Shannon and Simpson), although the differences were not statistically significant. QuickConcTM samples showed a greater capacity to detect rare taxa and to recover higher ASV richness in certain cases, suggesting its potential to enhance biodiversity resolution. Species composition remained consistent across methods, with Cristaria plicata and Sinanodonta lauta being dominant in both cases. However, slight spatial variations in species assemblages were observed between center and waterside sampling points, highlighting the influence of habitat heterogeneity on eDNA distribution. Overall, our results demonstrate that the QuickConcTM system offers a practical and efficient alternative to traditional filtration methods for eDNA-based freshwater mussel monitoring, particularly in environments with high suspended solids. The findings underline the need for adaptive sampling strategies that consider both methodological and ecological factors when designing eDNA surveys in lentic ecosystems.

Freshwater bivalves contribute to key ecological functions in lake ecosystems, yet their cryptic and benthic lifestyles often hinder detection through conventional surveys. In this study, we applied environmental DNA (eDNA) metabarcoding to assess the diversity and distribution of unionid bivalves in six lakes across Republic of Korea. Water samples were collected from three sampling strategies-Center Surface, Center Mix, and Waterside Surface-and processed using 16S rDNA-targeted primers followed by high-throughput sequencing. A total of four unionid species (Cristaria plicata, Sinanodonta lauta, Unio (Nodularia) douglasiae, and Anodonta woodiana) were detected across 18 sampling points. Notably, eDNA successfully identified unionid presence in all lakes, even where conventional surveys failed to observe individuals. Among the sampling strategies, Center Mix exhibited the highest values for Shannon and Simpson indices as well as ASV richness. Waterside Surface samples generally showed lower diversity and detection frequency. A Venn diagram of ASV occurrences revealed three ASVs shared across all sampling strategies and one unique ASV found only in Center Mix. These results indicate that sampling location significantly affects detection sensitivity and diversity representation in eDNA-based bivalve monitoring. Combined application of Center Mix and Center Surface strategies may enhance both detection efficiency and species diversity coverage in lentic environments.