Jos Barlow

This paper introduces an unsupervised method for estimating avian species richness from soundscape recordings, showing it outperforms traditional acoustic indices and automated identification models in hyperdiverse systems.

This study shows that anthropogenic disturbance inverts vertical microclimate stratification in Amazonian forests, with burned forests having hotter understory temperatures during the day and cooler temperatures at night compared to undisturbed forests.

The paper examines hyperdominance in Amazonian secondary forests, finding that a small number of species dominate abundance and carbon storage across different successional stages.

This study evaluates how classification model accuracy affects the reliability of detecting avian vocalisation patterns in ecological datasets.

The paper compares the biodiversity and carbon benefits and costs of three interventions in tropical forests, finding that avoiding disturbances is most cost-effective, but combined interventions yield the greatest gains.