F. Pellegrino

Improving the workflow to crack Small, Unbalanced, Noisy, but Genuine (SUNG) datasets in bioacoustics: the case of bonobo calls

The paper improves workflow for analyzing SUNG datasets in bioacoustics by applying machine learning to bonobo calls, identifying effective feature sets and classification methods.

Drilling down hotspots of intraspecific diversity to bring them into on-ground conservation of threatened species

The paper assesses the spatial and temporal dynamics of genetic diversity in a threatened toad species, highlighting the need for finer-scale conservation strategies.