Abstract
The persisting threats on migratory bird populations highlight the urgent need for effective monitoring techniques that could assist in their conservation. Among these, passive acoustic monitoring is an essential tool, particularly for nocturnal migratory species that are difficult to track otherwise. This work presents the Nocturnal Bird Migration (NBM) dataset, a collection of 13,359 annotated vocalizations from 117 species of the Western Palearctic, compiled through a crowd-sourcing effort. The dataset includes precise time and frequency annotations gathered by dozens of bird enthusiasts across France, enabling the automatic extraction of vocalizations in audio recordings and, further, novel downstream acoustic analysis. This comprises the development of a novel two-stage deep object detection model optimized for audio data, achieving competitive accuracy on the 45 most represented species, comparable to state-of-the-art systems trained on substantially larger datasets.
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Data availability
All data mentioned in this work, and which support the results presented here are freely accessible at the following address: https://zenodo.org/records/17573913.
Code availability
The code for downloading XC samples and for training or fine-tuning the NBM object detection model is accessible on the Github page of the project, https://github.com/LouisBearing/BirdSoundClassif, and on the following Zenodo repository: https://zenodo.org/records/15662728.
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Acknowledgements
The authors want to give credit to all the ornithologists who made this project possible. Special thanks to the original contributors: Adrien Pajot, Aymeric Mousseau, Christophe Mercier, Frédéric Cazaban, Gaëtan Mineau, Ghislain Riou, Guillaume Bigayon, Hervé Renaudineau, Kévin Leveque, Lionel Manceau, Mathurin Aubry, Maxence Pajot, Nidal Issa, Willy Raitiére, and equal thanks to all anonymous further contributors. The authors also want to thank Natural Solutions developers and other coding volunteers and particularly: Rhandy Grard, Gaëtan Duhamel, Javier Blanco, Ludovic Descateaux, Hervé Aymes. The authors also want to thank the members of the NBM association, Hervé Renaudineau and Léo Papet, and Paul Peyret for his reading and advice. Additionally, the authors want to highlight the support from the French biacoustics experts Yves Bas and Maxime Cauchoix. And finally, because of the complexity of crowd-sourcing projects, the authors want to warmly thank all the contributors who provided even punctual support through the project’s communication channels. Figure 4 pictures by Aurélie Jambon, Maxence Pajot and Louis Marsaud (CC BY NC ND 4.0).
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A.P. and J.L. managed the data collection project and were in charge of the animation of the annotator community. A.P. supervised the development of the web platform on which recordings were uploaded. L.A. reviewed the quality of the annotations and was in charge of the development and training of the object detection model. All three authors were involved in the writing of the present article.
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Airale, L., Pajot, A. & Linossier, J. An Open Dataset for the Acoustic Monitoring of Nocturnal Migratory Birds in Europe.
Sci Data (2026). https://doi.org/10.1038/s41597-026-07176-5
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DOI: https://doi.org/10.1038/s41597-026-07176-5
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