ArcticBirdSounds: An open-access, multiyear, and detailed annotated dataset of bird songs and calls.
Ecology
; 104(6): e4047, 2023 06.
Article
en En
| MEDLINE
| ID: mdl-37261395
Tracking biodiversity shifts is central to understanding past, present, and future global changes. Recent advances in bioacoustics and the low cost of high-quality automatic recorders are revolutionizing studies in biogeography and community and behavioral ecology with a robust assessment of phenology, species occurrence, and individual activity. This large volume of acoustic recordings has recently generated a plethora of datasets that can now be handled automatically, mostly via big data methods such as deep learning. These approaches need high-quality annotations to classify and detect recorded sounds efficiently. However, very few strongly annotated datasets-that is, with detailed information on start and end time of each vocalization-are openly accessible to the public. Moreover, these datasets mostly cover temperate species and are usually limited to a single year of recordings. Here, we present ArcticBirdSounds, the first open-access, multisite, and multiyear strongly annotated dataset of arctic bird vocalizations. ArcticBirdSounds offers 20 h of annotated recordings over 2 years (2018, 2019), taken from 15 distinct plots within six locations across the Arctic, from Alaska to Greenland. Recordings cover the arctic vertebrates' breeding period and are evenly spaced during the day; they capture most species breeding there with 12,933 temporal annotations in 49 classes of sounds. While these data can be used for many pressing ecological questions, it is also a unique resource for methodological development to help meet the challenges of fast ecosystem transformations such as those happening in the Arctic. All data, including audio files, annotation files, and companion spreadsheets, are available in an Open Science Framework repository published under a CC BY 4.0 License.
Palabras clave
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Aves
/
Ecosistema
Límite:
Animals
País/Región como asunto:
America do norte
Idioma:
En
Revista:
Ecology
Año:
2023
Tipo del documento:
Article
País de afiliación:
Canadá
Pais de publicación:
Estados Unidos