monitoraSom: an easy path from Soundscapes to Ecology

Abstract

Soundscape analysis for biodiversity monitoring with data from autonomous recorders has become a vital tool for biodiversity research. Yet, workflows fragmented across multiple software and technical barriers make the analysis of such large datasets a challenging task. Here, we present monitoraSom, an efficient and user-friendly toolbox that facilitates the path between Passive Acoustic Monitoring (PAM) with ecological studies. This R package includes (1) modular workflows adaptable to diverse study designs, (2) an efficient and responsive user interface for fast soundscape recording segmentation; (3) validation methods adaptable to most data availability scenarios, including an interface for manual validation, and (4) dynamic diagnostics for threshold optimization to refine detection performance. The package is designed for scalability, with simple and easy to use batch processing and parallelization options, as well as simple data formats, making it accessible to beginners and advanced users. By reducing the technical hurdles and ensuring reproducibility, it accelerates the transformation of acoustic data into ecological information from rare species monitoring to community level surveys.