F. Leese

Fish predation induces drifting and emergence in an experimental stream mesocosm system

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.

Salinisation and warming disrupt predator-induced drift behaviour in aquatic predator-prey interactions

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

Complex compositional and cellular response of river sediment microbiomes to multiple anthropogenic stressors

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.

Upscaling biodiversity monitoring: Metabarcoding estimates 31,846 insect species from Malaise traps across Germany

The paper demonstrates a cost-effective DNA metabarcoding workflow for large-scale insect biodiversity monitoring, estimating 31,846 species from Malaise trap samples across Germany.

Fresh insights into Mediterranean biodiversity: Environmental DNA reveals spatio-temporal patterns of stream invertebrate communities on Sicily

The paper uses eDNA metabarcoding to study stream invertebrate biodiversity in Sicily, finding seasonal diversity changes and a dispersal barrier.

Individual small in-stream barriers contribute little to strong local population genetic structure five strictly aquatic macroinvertebrate taxa

The paper assesses the impact of small in-stream barriers on genetic structure of five aquatic macroinvertebrates, finding significant effects only for specific barriers and species.

Evaluating geographic variation within molecular operational taxonomic units (OTUs) using network analyses in Scandinavian lakes

The paper evaluates geographic variation within molecular operational taxonomic units using network analyses on metabarcoding data from Scandinavian lakes and finds no assortative clustering or increased connectivity between neighboring lakes.

Deep learning and computer vision will transform entomology

This paper discusses how deep learning and computer vision can improve insect monitoring by enabling non-invasive, continuous data collection and analysis of insect abundance, diversity, and phenotypic traits.

Improved freshwater macroinvertebrate detection from eDNA through minimized non-target amplification

This study improves freshwater macroinvertebrate detection from eDNA by designing a new primer that reduces non-target amplification, increasing target read percentages and detected taxa.

DNA barcode reference libraries for the monitoring of aquatic biota in Europe: Gap-analysis and recommendations for future work

This paper analyzes gaps in DNA barcode reference libraries for European aquatic species and recommends strategies to improve their completeness and quality for biomonitoring.