bioRxiv · 10.1101/2024.05.21.595242
National-scale acoustic monitoring of avian biodiversity and phenology
Abstract
Billions of birds migrate annually, triggered by endogenous behaviors but also by ecoclimatic drivers which are shifting with climate change. These dynamics play out over huge spatiotemporal scales, making monitoring of phenology challenging with traditional biodiversity survey approaches. In this study, over a complete spring migration season (April through June), we collected 37,429 hours of audio from 28 networked sensors in forests across Norway using a nationwide passive acoustic monitoring (PAM) system. We applied an open-source detection algorithm to automatically classify bird vocalizations; through expert validation we found the algorithm classified 57 species (14 full migrants) with at least 80% precision. Using these automated detections, we developed regional arrival curves for three common migratory passerines: Willow Warbler, Common Chiffchaff, and Spotted Flycatcher. We then demonstrate that PAM detections can be used to train audio species distribution models that map how species vocalization probability changes across Norway during spring migration. Lastly, we discuss how PAM can complement existing manual surveys to support the design and implementation of effective policy and conservation measures.
Source connections
Explore related subjects
Keep this discovery
Explore connections, maps & timelines
Bick, A., Bakkestuen, V., Cretois, B., Hillier, B., Kalas, J. A., Pedersen, M., Raja, K., Rosten, C., Somveille, M., Stokke, B., Wiel, J., Sethi, S. S.. 2024-05-24. National-scale acoustic monitoring of avian biodiversity and phenology. https://doi.org/10.1101/2024.05.21.595242
Cite the original work for its findings. Save a collection to share your selection of sources.