Florian Leese

COI metabarcoding of 81 arthropod mock communities shows PCR amplification bias is taxon-specific but non-exponential, so cycle calibration fails while a constant-bias model recovers mtDNA copies.

This study uses eDNA metabarcoding to monitor biodiversity across aquatic habitats, finding it provides more species data at lower cost than traditional methods.

This study uses DNA metabarcoding to survey insect biodiversity in Crete, revealing many new species and highlighting gaps in reference databases.

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

The paper uses environmental DNA metabarcoding of archived samples to track long-term fish biodiversity trends and identify drivers of change across six European river systems over 17 years.

This study examines the effects of flow intermittency and light pollution on macroinvertebrates in river networks, showing that combined stressors have stronger downstream impacts.

This study examines how fish predation affects drift and emergence behaviors of aquatic invertebrates in a mesocosm system, showing significant responses to both indirect and direct predation.

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 study evaluates two eDNA metabarcoding approaches for stream bioassessment under the WFD, finding they produce comparable ecological status results to bulk DNA and morphology-based methods.

This study evaluates de novo transcriptome assemblers and quantification tools for non-model arthropods, finding that Trinity and rnaSPAdes outperform IDBA-tran, and Salmon provides faster and more sensitive quantification than RSEM.

This study shows river sediment microbiomes are highly sensitive to reduced flow velocity, leading to altered community compositions and stress responses that recover after two weeks.

This study investigates how salinisation and warming affect predator-induced drift behaviour in stream invertebrates, finding that both stressors disrupt this anti-predator response.

This study compares amplicon sequencing, metagenomics, and total RNA sequencing for predicting environmental stressors using machine learning, finding 16S sequencing outperforms others despite moderate performance.

The paper demonstrates that rainwash eDNA metabarcoding can detect canopy invertebrate diversity, revealing species not present in water samples and showing host-specific patterns.

This paper shows that increasing field replicates improves detection of non-fish vertebrates in stream eDNA metabarcoding, while fish detection increases less.

TaxonTableTools provides a GUI for analysing and visualising DNA metabarcoding data, enabling users to perform ecological analyses and generate visualisations without bioinformatic expertise.

This study evaluates if DNA metabarcoding can assess mitochondrial genetic diversity changes in response to environmental stressors in river macrozoobenthic communities.

This paper tests a non-destructive DNA metabarcoding method using ethanol fixative to assess biodiversity, finding it effective for some taxa but lacking for others.

The paper introduces a centrifugation protocol that increases mitochondrial DNA yield 140-fold, enabling efficient sequencing of whole mitochondrial genomes for biodiversity studies.

This study shows that eDNA metabarcoding results vary with sampling time and location in rivers, highlighting the need for careful sampling design.