Camille P. Albouy

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.

This paper uses convolutional neural networks to process eDNA metabarcoding data, achieving faster speeds than OBITools while maintaining comparable accuracy.

The paper investigates how ecological traits influence genetic diversity components in tropical reef fishes, finding that abundance and larval duration affect genetic diversity patterns.