Shuo Zong

This paper proposes a remote-sensing-based stratification method for eDNA sampling in rivers, showing improved detection efficiency compared to random sampling and highlighting the need for hydrological integration.

This study reanalyzes global riverine fish eDNA datasets to show that biodiversity conclusions are robust despite varying bioinformatic workflows and reference databases.

This study uses global eDNA data to show how riverine fish biodiversity relates to drainage characteristics, revealing climate and human activity effects vary by biodiversity facet and catchment size.

The paper links terrestrial land cover changes to fish diversity in a subtropical river catchment, showing LULC effects up to 20 km upstream and explaining 60% of species richness variance.