<scp>WABAD</scp> : A world annotated bird acoustic dataset for passive acoustic monitoring

Under the current global biodiversity crisis, there is a need for automated and noninvasive monitoring techniques that can gather large amounts of data cost-effectively at various ecological scales, from local to large spatial scales. These data can then be analyzed to inform stakeholders and decision-makers. One such technique is passive acoustic monitoring, which is commonly coupled with automatic identification of animal species based on their sound. Automated sound analyses usually require the training of sound detection and identification algorithms. These algorithms are based on annotated acoustic datasets which mark the occurrence of sounds of species inside sound recordings. However, compiling large annotated acoustic datasets is time-consuming and requires experts, and therefore, they normally cover reduced spatial, temporal, and taxonomic scales. This data paper presents WABAD, the World Annotated Bird Acoustic Dataset for passive acoustic monitoring. WABAD is designed to provide the public, the research community, and conservation managers with a novel and globally representative annotated acoustic dataset. This database includes 5047 min of audio files annotated to species-level by local experts with the start and end time and the upper and lower frequencies of each identified bird vocalization in the recordings. The database has a wide taxonomic and spatial coverage, including information on 91,931 vocalizations from 1192 bird species recorded at 72 recording sites in 29 recording locations (mainly countries) and distributed across 13 biomes. WABAD can be used, for example, for developing and/or validating automatic species detection algorithms, answering ecological questions, such as assessing geographical variations on bird vocalizations, or comparing acoustic diversity indices with species-based diversity indices. The dataset is published under a Creative Commons Attribution 4.0 International license that permits redistribution and reuse on the condition that the original work is properly credited.

Institutions

Publication Details

Journal
Ecology
Published
2026-02-01
DOI
https://doi.org/10.1002/ecy.70317
Citations
1
Primary Topic
Animal Vocal Communication and Behavior
Type
article
Field-Weighted Citation Impact
13.66
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article

WABAD : A world annotated bird acoustic dataset for passive acoustic monitoring

1 citations
Ecology
Animal Vocal Communication and Behavior
13.66
article

WABAD : A world annotated bird acoustic dataset for passive acoustic monitoring

article en
1 citations

Abstract

Under the current global biodiversity crisis, there is a need for automated and noninvasive monitoring techniques that can gather large amounts of data cost-effectively at various ecological scales, from local to large spatial scales. These data can then be analyzed to inform stakeholders and decision-makers. One such technique is passive acoustic monitoring, which is commonly coupled with automatic identification of animal species based on their sound. Automated sound analyses usually require the training of sound detection and identification algorithms. These algorithms are based on annotated acoustic datasets which mark the occurrence of sounds of species inside sound recordings. However, compiling large annotated acoustic datasets is time-consuming and requires experts, and therefore, they normally cover reduced spatial, temporal, and taxonomic scales. This data paper presents WABAD, the World Annotated Bird Acoustic Dataset for passive acoustic monitoring. WABAD is designed to provide the public, the research community, and conservation managers with a novel and globally representative annotated acoustic dataset. This database includes 5047 min of audio files annotated to species-level by local experts with the start and end time and the upper and lower frequencies of each identified bird vocalization in the recordings. The database has a wide taxonomic and spatial coverage, including information on 91,931 vocalizations from 1192 bird species recorded at 72 recording sites in 29 recording locations (mainly countries) and distributed across 13 biomes. WABAD can be used, for example, for developing and/or validating automatic species detection algorithms, answering ecological questions, such as assessing geographical variations on bird vocalizations, or comparing acoustic diversity indices with species-based diversity indices. The dataset is published under a Creative Commons Attribution 4.0 International license that permits redistribution and reuse on the condition that the original work is properly credited.

EcologyVol. 107(2)
Dartmouth College (US), Universidad de Valladolid (ES), University of Copenhagen (DK), Universidade Federal da Bahia (BR), Universidade Estadual de Londrina (BR), Centre National de la Recherche Scientifique (FR), University of Alicante (ES), National Park Service (US), Environment and Climate Change Canada (CA), Université Toulouse III - Paul Sabatier (FR), University of Quindío (CO), Universidad del Norte (CO), Guangxi University (CN), Universidad de San Carlos de Guatemala (GT), University of Freiburg (DE), Universidade Federal da Paraíba (BR), Pontifícia Universidade Católica de Minas Gerais (BR), Copenhagen Business School (DK), Université du Québec en Abitibi-Témiscamingue (CA), University of Washington (US), Bradley University (US), Edinburgh Napier University (GB), Scotland's Rural College (GB), Swiss Ornithological Institute (CH), Royal Botanic Gardens, Kew (GB), Danish Nature Agency (DK), Portuguese Army (PT), Museum and Institute of Zoology (PL), Instituto Federal de Educação Ciência e Tecnologia da Paraíba (BR), Universidade Federal de Mato Grosso (BR), University of Cyprus (CY), Universidade Federal do Rio Grande do Norte (BR), University of Hawaii at Hilo (US), Universidad de Antioquia (CO), Frederick University (CY), Universidad de Cádiz (ES), University of Oxford (GB), Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement (FR), Estación Biológica de Doñana (ES), Sustainability Institute (ZA), Institute for Biodiversity (DE), Zoological Research Museum Alexander Koenig (DE), Eurofins (Netherlands) (NL), Instituto de Investigación en Recursos Cinegéticos (ES), Forest Science and Technology Centre of Catalonia (ES), Centre for Research on Ecology and Forestry Applications (ES), Forest Research Institute (BG), Biodiversity Research Center, Academia Sinica (TW), Instituto de Biología Subtropical (AR), International Center for Tropical Agriculture (VN), Severtsov Institute of Ecology and Evolution (RU), Instituto de Ecología (MX), Génétique Physiologie et Systèmes d'Elevage (FR), Complejo Hospitalario de Cáceres (ES), Centro Universitário de João Pessoa (BR), Station d’Écologie Théorique et Expérimentale (FR), Bronberg Observatory (ZA), Imperial College London (GB), University of Salford (GB), Adam Mickiewicz University in Poznań (PL), Universidad Autónoma de Madrid (ES), Universidade Federal de Goiás (BR), Xi’an Jiaotong-Liverpool University (CN), Universidad de Sevilla (ES), V. N. Karazin Kharkiv National University (UA), Universidad Politécnica de Madrid (ES), University of Gothenburg (SE), Universidad Autónoma del Estado de Morelos (MX), Colorado State University (US), Polish Academy of Sciences (PL)
Openalex Percentile: Top 3%
Animal Vocal Communication and Behavior
13.66
DOIOpen Access PDFOpenAlex
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