Evidence map›Paper›PMID 41912539›Full record

ArticleScientific data2026

A large-scale acoustic dataset of a passerine with spatially variable vocal behavior: fine-scale annotations of song and call types.

Cristian Pérez-Granados, Cristina D Alonso-Moya, Adrián Barrero, Pedro Sáez-Gómez, Gerard Bota, José J Lahoz-Monfort, Tomasz S Osiejuk, Alex Rogers, Karl-L Schuchmann, Juan Traba

Abstract readDataset
In one paragraph

Article in Scientific data, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Cristian Pérez-GranadosBiodiversity Management and Conservation Programme, Forest Science and Technology Centre of Catalonia, CTFC, Lleida, Spain. cristian.perez@ctfc.cat.
Cristina D Alonso-MoyaBiodiversity Management and Conservation Programme, Forest Science and Technology Centre of Catalonia, CTFC, Lleida, Spain.
Adrián BarreroTerrestrial Ecology Group (TEG-UAM), Departamento de Ecología, Universidad Autónoma de Madrid, 28049, Madrid, Spain.
Pedro Sáez-GómezTerrestrial Ecology Group (TEG-UAM), Departamento de Ecología, Universidad Autónoma de Madrid, 28049, Madrid, Spain.
Gerard BotaBiodiversity Management and Conservation Programme, Forest Science and Technology Centre of Catalonia, CTFC, Lleida, Spain.
José J Lahoz-MonfortInstituto Pirenaico de Ecología, CSIC, Jaca, Huesca, España.
Tomasz S OsiejukDepartment of Behavioural Ecology, Institute of Environmental Biology, Faculty of Biology, Adam Mickiewicz University, Poznań, Poland.
Alex RogersDepartment of Computer Science, University of Oxford, Oxford, OX1 3QD, UK.
Karl-L SchuchmannInstitute for Science and Technology in Wetlands (INAU), Federal University of Mato Grosso (UFMT), Computational Bioacoustics Research Unit (CO.BRA), Fernando Correa da Costa Av. 2367, Cuiabá, MT, 78060-900, Brazil.
Juan TrabaTerrestrial Ecology Group (TEG-UAM), Departamento de Ecología, Universidad Autónoma de Madrid, 28049, Madrid, Spain.

Funding

Spanish Ministry of Science, Innovation and Universities RYC2024-048830-I
6 · The paper itself

Abstract

The study of bird vocal behavior provides insights into ecology, evolution, and conservation. Prior research has mostly focused on bird songs, with limited attention to calling behavior. Although the origins and functions of these vocalizations differ, no detailed annotated acoustic datasets are currently available including both bird songs and calls. Here, we present an acoustic dataset with standardized recordings and detailed annotations of singing and calling behavior in the Dupont's lark (Chersophilus duponti), a passerine with spatially variable vocal behavior. Recordings were collected across a large spatial scale (20 populations) to capture geographic variation in vocalizations. The dataset includes 4,297 annotated songs from 191 singing males, representing 401 song types, and 795 annotated calls from 97 calling males, representing 80 call types. Annotations provide precise categorization of song and call types, enabling comparisons of individual and population vocal repertoires, geographic variation, and potential effects of habitat fragmentation on vocal behavior. This dataset is intended for reuse in studies of bird vocal behavior, comparative analyses of song and call patterns, and research on passerine acoustic communication.

Indexed as

PasseriformesVocalization, AnimalAcousticsAnimalsMale

Identifiers

PMID41912539
PMCPMC13194660

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.