# Assessment of Freshwater Unionidae Using Environmental DNA Metabarcoding in Lentic Ecosystems: Implications for Spatial Sampling Strategies

## TL;DR

This study shows that environmental DNA (eDNA) can effectively detect freshwater mussels in lakes, with spatial patterns influenced by habitat preferences rather than seasons.

## Contribution

The study introduces a validated eDNA metabarcoding method for freshwater mussels and provides insights into optimal sampling strategies in lentic ecosystems.

## Key findings

- Mussel genetic signals were detected in all lakes, even without direct observation.
- eDNA read abundance varied by location, with higher signals in central lake areas than near shorelines.
- Species-specific patterns suggest habitat preferences influence eDNA distribution more than seasonal changes.

## Abstract

Freshwater mussels play an important role in maintaining the health of lake ecosystems, but they are difficult to monitor because they live buried in sediments and are hard to detect using traditional survey methods. This study evaluated the effectiveness of eDNA metabarcoding in detecting freshwater Unionidae mussels in lake water columns and examined their spatial and seasonal distribution patterns. Water samples were collected from the edges and the central areas of four lakes during autumn and winter, from the surface, middle, and bottom layers. The results showed that mussel genetic signals were consistently detected in all lakes, even without direct observation of the animals. Overall detection did not change greatly between seasons, but clear differences were found among sampling locations. Genetic signals were lower near the shoreline and higher in central lake areas, while water depth within the central zone had little effect. Two common mussel species showed different spatial patterns, reflecting their habitat preferences rather than seasonal activity. These findings demonstrate that water-based genetic monitoring can provide an efficient, non-invasive means to assess freshwater mussel diversity in lakes. The study offers practical guidance for designing lake monitoring programs that support biodiversity conservation and ecosystem management.

Environmental DNA (eDNA) metabarcoding has become a powerful, non-invasive method for detecting aquatic organisms. However, optimal sampling strategies for benthic taxa in lentic ecosystems remain unclear. This study evaluated the effectiveness of eDNA metabarcoding in detecting freshwater Unionidae mussels in lake water columns and examined their spatial and seasonal distribution patterns. We validated a mini-barcode primer targeting the mitochondrial 16S rDNA of unionid mussels through controlled laboratory experiments and field tests, confirming reliable amplification and accurate taxonomic assignment of freshwater bivalve DNA. Field surveys were conducted in four lakes within the Nakdong River basin, where eDNA samples were collected from littoral zones and from surface, mid-, and bottom layers of central lake areas during autumn and winter. Metabarcoding analysis identified 79 amplicon sequence variants (ASVs) representing four unionid taxa, with Cristaria plicata and Sinanodonta lauta comprising the majority of reads and ASVs. Overall, the number of Unionidae eDNA reads showed no significant seasonal differences, but there was notable spatial variation among sampling locations. Read numbers were significantly lower in littoral zones compared to central lake areas, with no significant differences detected among depth layers within the central zones. Species-specific analyses revealed contrasting spatial patterns: C. plicata had higher read abundance in mid- and bottom layers, while S. lauta was more frequently detected in surface and littoral samples. These findings suggest that the distribution of freshwater mussel eDNA in lakes is primarily influenced by spatial factors related to habitat preference and hydrodynamic mixing, rather than by seasonal variation during stable periods. This study offers practical insights for designing effective eDNA sampling strategies for benthic invertebrates in lentic ecosystems.