Biodiversity loss poses a significant environmental challenge, particularly in aquatic ecosystems. The advent of environmental DNA (eDNA) sampling technology offers a promising tool for monitoring biological communities with purported high efficiency. Yet, its efficacy compared to traditional sampling methods remains underexplored, especially in fish diversity research.
This study conducted a comparative analysis of fish diversity and distribution across 29 sampling points within the rivers of the Changqing Nature Reserve, Central China, employing both eDNA techniques and traditional sampling methods.
A total of 46 unique fish species were identified through this comprehensive approach. eDNA sampling detected 34 species, surpassing the 22 species identified by traditional methods. Interestingly, 10 species were detected by both methods, while traditional methods exclusively identified 12 species not detected by eDNA, and eDNA uniquely identified an additional 24 species. Despite eDNA's broader species detection range, traditional sampling methods typically yielded higher Shannon diversity index values. Both β-diversity indices (Bray-Curtis and Jaccard) and multivariate analyses (NMDS and PCoA) were applied, revealing no significant statistical differences in biodiversity measurement between the two sampling methods.
The findings suggest that while eDNA sampling excels in identifying a wider range of species, it does not significantly outperform traditional methods in overall biodiversity assessment. By integrating both methodologies, this study demonstrates a more comprehensive and precise assessment of riverine biodiversity, underscoring the benefits of a synergistic approach for enhancing species detection and understanding distribution patterns. The combined methodology notably improves alpha diversity evaluations, particularly regarding Shannon diversity and Berger-Parker dominance. This integrated approach advocates for the amalgamation of data from both eDNA and conventional methods, fostering a robust and accurate biodiversity appraisal.