Assessing the potential of BirdNET to infer European bird communities from large-scale ecoacoustic data

Ecological Indicators, Год журнала: 2024, Номер 164, С. 112146 - 112146

Опубликована: Май 20, 2024

Passive acoustic monitoring has become increasingly popular as a practical and cost-effective way of obtaining highly reliable data in ecological research projects. Increased ease collecting these means that, currently, the main bottleneck ecoacoustic projects is often time required for manual analysis passively collected recordings. In this study we evaluate potential current limitations BirdNET-Analyzer v2.4, most advanced generic deep learning algorithm bird recognition to date, tool assess community composition through automated large-scale data. To end, 3 datasets comprising total 629 environmental soundscapes 194 different sites spread across 19° latitude span Europe. We analyze using both BirdNET listening by local expert birders, then compare results obtained two methods performance at level each single vocalization entire recording sequences (1, 5 or 10 min). Since provides confidence score identification, minimum thresholds can be used filter out identifications with low scores, thus retaining only ones. The volume did not allow us estimate species-specific taxa, so instead evaluated global selected optimized when consistently applied all species. Our analyses reveal that if sufficiently high threshold used. However, inevitable trade-off between precision recall does obtain satisfactory metrics same time. found F1-scores remain moderate (<0.5) studied, extended duration seem currently necessary provide minimally comprehensive picture target community. estimate, however, usage species- context-specific would substantially improve benchmarks study. conclude judicious use AI-based provided represent powerful method assist assessment data, especially duration.

Язык: Английский

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Passive acoustic monitoring and automated detection of the American bullfrog

Biological Invasions, Год журнала: 2024, Номер 26(4), С. 1269 - 1279

Опубликована: Янв. 25, 2024

Abstract Biological invasions pose significant threats to biodiversity and ecosystem functioning. Removal of introduced species is most successful when detected early. We evaluate the effectiveness passive acoustics combined with automated recognition in detecting invasive American bullfrog ( Lithobates catesbeianus ). applied this technique two real-world monitoring programs aimed at determining optimal time day for Europe, which we recorded Belgium Italy; evaluating BirdNET (a free user-friendly recognizer) analyzing a large dataset collected Spain. was highly effective automatically presence, detection rate (compared visual inspection sonograms) 89.5% using default settings (85 95 recordings known presence), 95.8% user-specific (91 detected). The system showed remarkable precision, correctly identifying 99.7% (612 out 614) verified predictions, only one mislabelled recording (predicted be present it absent). species’ vocal activity Italy higher during night compared crepuscular periods. Recording analyses output verification Spain carried 3.8% time, resulted significantly reduced effort inspection. Our study highlights remotely surveying bullfrog, making potential tool informing management decisions, particularly early arrival new areas.

Язык: Английский

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Territorial Acoustic Species Estimation Using Acoustic Sensor Networks

Опубликована: Янв. 1, 2025

Язык: Английский

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Territorial Acoustic Species Estimation using Acoustic Sensor Networks

Опубликована: Янв. 1, 2025

Язык: Английский

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Methods of acoustic data processing affect species detectability in passive acoustic monitoring of multi‐species playback

Ibis, Год журнала: 2025, Номер unknown

Опубликована: Март 16, 2025

Passive acoustic monitoring (PAM) efforts have recently been accelerated by the development of automated detection tools, enabling quick and reliable analysis recordings. However, methods are still susceptible to errors, human processors achieve more accurate results. Our study evaluates efficacy three (auditory, visual using BirdNET) for 43 European bird species (31 diurnal, 12 nocturnal), analysing impact various factors on probability over different distances. We conducted transmission experiments in two forest types from March June, examining effect call characteristics, weather conditions habitat features, assess their at findings reveal that distance varies with each method, listening recordings obtaining highest detectability, followed method. Although BirdNET is less accurate, it proves useful detection, especially loud species. Large diurnal small nocturnal were most detected. emphasizes importance considering maximize detectability effective PAM research.

Язык: Английский

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NDVI and vegetation volume as predictors of urban bird diversity

Scientific Reports, Год журнала: 2025, Номер 15(1)

Опубликована: Апрель 15, 2025

Язык: Английский

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Birdnet Confidence Scores Decrease with Bird Distance from the Recorder: Revisiting Pérez-Granados (2023)

Ardeola, Год журнала: 2025, Номер 72(2)

Опубликована: Апрель 17, 2025

Язык: Английский

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Improving bird abundance estimates in harvested forests with retention by limiting detection radius through sound truncation

Ornithological Applications, Год журнала: 2024, Номер unknown

Опубликована: Окт. 16, 2024

ABSTRACT An inherent challenge with acoustically surveying birds is that the distance at which they can be detected depends on how far their song heard. We developed a distance-based sound detection space truncation method to correct for variable sampling radii due in forested or open conditions. The was pivotal evaluating bird responses retention patches; without this methodological advancement, impact of patches songbird abundance vastly underestimated. In boreal forest, these live trees are retained regenerating harvested forests provide ecological services species adapted natural disturbances. Although we did not verify our priori assumption ground observations, findings suggest limited-distance better captures effects use forests. When evaluated using unlimited surveys, had negligible effect abundance, whereas applying highlighted importance forest birds. found early mid-seral songbirds benefited from patches, notable increases after 10 years regeneration. size ranging 0.1 1.2 ha, have linear relationship abundance. Instead, edge stemming configuration emerged as key determinants majority studied. Retention were nearest unharvested used most, compared further into harvest areas. Our research only highlights underestimated small-scale tree but also introduces significant innovation field acoustic monitoring.

Язык: Английский

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Assessing the potential of BirdNET to infer European bird communities from large-scale ecoacoustic data

bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2023, Номер unknown

Опубликована: Дек. 12, 2023

Abstract Passive acoustic monitoring has become increasingly popular as a practical and cost-effective way of obtaining highly reliable data in ecological research projects. Increased ease collecting these means that, currently, the main bottleneck ecoacoustic projects is often time required for manual analysis passively collected recordings. In this study we evaluate potential current limitations BirdNET-Analyzer v2.4, most advanced generic deep learning algorithm bird recognition to date, tool assess community composition through automated large-scale data. To end, 3 datasets comprising total 629 environmental soundscapes 194 different sites spread across 19° latitude span Europe. We analyze recordings both with BirdNET by listening local expert birders, then compare results obtained two methods performance at level each single vocalization entire recording sequences (1, 5 or 10 min). Our analyses reveal that identifications can be if sufficiently high minimum confidence threshold used. However, recall markedly low when adjusted ensure levels precision. Thus, found F1-scores remain moderate (<0.5) all thresholds studied. therefore estimate extended duration are currently necessary provide minimally comprehensive picture target community. also suggest not significantly influenced type recorder used habitat recorded but modulated volume species-specific available online. conclude judicious use AI-based IDs provided represent novel powerful method assist assessment Finally, best recommendations optimal from communities.

Язык: Английский

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Assessing the Potential of Birdnet to Infer European Bird Communities from Large-Scale Ecoacoustic Data

Опубликована: Янв. 1, 2023

1. Passive acoustic monitoring has become increasingly popular as a practical and cost-effective way of obtaining highly reliable data in ecological research projects. Increased ease collecting these means that, currently, the main bottleneck ecoacoustic projects is often time required for manual analysis passively collected recordings. In this study we evaluate potential current limitations BirdNET-Analyzer v2.4, most advanced generic deep learning algorithm bird recognition to date, tool assess community composition through automated large-scale data. 2. To end, 3 datasets comprising total 629 environmental soundscapes 194 different sites spread across 19° latitude span Europe. We analyze recordings both with BirdNET by listening local expert birders, then compare results obtained two methods performance at level each single vocalization entire recording sequences (1, 5 or 10 min). 3. Our analyses reveal that identifications can be if sufficiently high minimum confidence threshold used. However, recall markedly low when adjusted ensure levels precision. Thus, found F1-scores remain moderate (<0.5) all thresholds studied. therefore estimate extended duration are currently necessary provide minimally comprehensive picture target community. also suggest not significantly influenced type recorder used habitat recorded but modulated volume species-specific available online. 4. conclude judicious use AI-based IDs provided represent novel powerful method assist assessment Finally, best recommendations optimal from communities.

Язык: Английский

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