Autonomous sound recording outperforms human observation for sampling birds: a systematic map and user guide

Ecological Applications, Год журнала: 2019, Номер 29(6)

Опубликована: Июнь 17, 2019

Abstract Autonomous sound recording techniques have gained considerable traction in the last decade, but question remains whether they can replace human observation surveys to sample sonant animals. For birds particular, survey methods been tested extensively using point counts and surveys. Here, we review latest evidence for this taxon within frame of a systematic map. We compare sampling effectiveness these two methods, output variables produce, their practicality. When assessed against standard counts, autonomous proves be powerful tool that samples at least as many species. This technology monitor an exhaustive, standardized, verifiable way. Moreover, recorders give access entire soundscapes from which new data types derived (vocal activity, acoustic indices). Variables such abundance, density, occupancy, or species richness obtained yield sets are comparable compatible with counts. Finally, allow investigations high temporal spatial resolution coverage, more cost effective cannot achieved by observations alone, even though small‐scale studies might when carried out Sound deployed places, scalable reliable, making them better choice bird increasingly data‐driven time. provide overview currently available discuss specifications guide future study designs.

Язык: Английский

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Sounding the Call for a Global Library of Underwater Biological Sounds

Frontiers in Ecology and Evolution, Год журнала: 2022, Номер 10

Опубликована: Фев. 8, 2022

Aquatic environments encompass the world’s most extensive habitats, rich with sounds produced by a diversity of animals. Passive acoustic monitoring (PAM) is an increasingly accessible remote sensing technology that uses hydrophones to listen underwater world and represents unprecedented, non-invasive method monitor environments. This information can assist in delineation biologically important areas via detection sound-producing species or characterization ecosystem type condition, inferred from properties local soundscape. At time when worldwide biodiversity significant decline soundscapes are being altered as result anthropogenic impacts, there need document, quantify, understand biotic sound sources–potentially before they disappear. A step toward these goals development web-based, open-access platform provides: (1) reference library known unknown biological sources (by integrating expanding existing libraries around world); (2) data repository portal for annotated unannotated audio recordings single soundscapes; (3) training artificial intelligence algorithms signal classification; (4) citizen science-based application public users. Although individually, resources often met on regional taxa-specific scales, many not sustained and, collectively, enduring global database integrated has been realized. We discuss benefits such program provide, previous calls data-sharing libraries, challenges be overcome bring together bio- ecoacousticians, bioinformaticians, propagation experts, web engineers, processing specialists (e.g., intelligence) necessary support funding build sustainable scalable could address needs all contributors stakeholders into future.

Язык: Английский

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Soundscapes and deep learning enable tracking biodiversity recovery in tropical forests

Nature Communications, Год журнала: 2023, Номер 14(1)

Опубликована: Окт. 17, 2023

Tropical forest recovery is fundamental to addressing the intertwined climate and biodiversity loss crises. While regenerating trees sequester carbon relatively quickly, pace of remains contentious. Here, we use bioacoustics metabarcoding measure post-agriculture in a global hotspot Ecuador. We show that community composition, not species richness, vocalizing vertebrates identified by experts reflects restoration gradient. Two automated measures - an acoustic index model bird composition derived from independently developed Convolutional Neural Network correlated well with (adj-R² = 0.62 0.69, respectively). Importantly, both reflected non-vocalizing nocturnal insects via metabarcoding. such monitoring tools, based on new technologies, can effectively monitor success recovery, using robust reproducible data.

Язык: Английский

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Feature embeddings from the BirdNET algorithm provide insights into avian ecology

Ecological Informatics, Год журнала: 2023, Номер 74, С. 101995 - 101995

Опубликована: Янв. 18, 2023

Язык: Английский

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The Rapid Rise of Next-Generation Natural History

Frontiers in Ecology and Evolution, Год журнала: 2021, Номер 9

Опубликована: Июль 21, 2021

Many ecologists have lamented the demise of natural history and attributed this decline to a misguided view that is outdated unscientific. Although there perception focus in ecology conservation shifted away from descriptive research training toward hypothetico-deductive research, we argue has entered new phase call “next-generation history.” This renaissance characterized by technological statistical advances aid collecting detailed observations systematically over broad spatial temporal extents. The increased exponentially last decade include electronic sensors such as camera-traps acoustic recorders, aircraft- satellite-based remote sensing, animal-borne biologgers, genetics genomics methods, community science programs. Advances statistics computation aided analyzing growing quantity reveal patterns nature. These robust next-generation datasets transformed anecdotal into collected collectively constitute foundation for can be leveraged applied management. are encouraging scientists conduct embrace descriptions nature remain critically important component scientific endeavor. Finally, these engaging non-scientists alike with documentations wonders Thus, celebrate people experience directly.

Язык: Английский

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The sound of restored soil: using ecoacoustics to measure soil biodiversity in a temperate forest restoration context

Restoration Ecology, Год журнала: 2023, Номер 31(5)

Опубликована: Май 22, 2023

Forest restoration requires monitoring to assess above‐ and belowground communities, which is challenging due practical resource limitations. Ecological acoustic survey methods––also known as “ecoacoustics”––are increasingly available provide a rapid, effective, non‐intrusive means of biodiversity. Aboveground ecoacoustics widespread, but soil has yet be utilized in despite its demonstrable effectiveness at detecting soniferous meso‐ macrofauna. This study applied ecoacoustic tools indices (Acoustic Complexity Index, Normalized Difference Soundscape Bioacoustic Index) measure (and aboveground secondary) biodiversity forest site spanning two age classes. We collected n = 198 samples 180 from three recently deforested (felled <3 years ago) deciduous plots undergoing (for the last 30–51 years) across monthly visits South Yorkshire, U.K. used sampling device sound‐attenuation chamber record communities passive sounds. found that restored plot complexity diversity were significantly higher than chamber, there no inter‐plot differences in‐situ or samples. also had greater high‐frequency low‐frequency ratio (suggesting biophony anthrophony ratios) for sound association Our results suggest immense potential monitor biodiversity, adding ecologist's toolkit supporting global ecosystem recovery.

Язык: Английский

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The environmentality of digital acoustic monitoring: Emerging formations of spatial power in forests

Political Geography, Год журнала: 2024, Номер 110, С. 103074 - 103074

Опубликована: Фев. 21, 2024

The rise of digital acoustic monitoring is having transformative effects within forest conservation geographies and practices. By featuring divergent signals (a gunshot, a bird call) as its evidentiary basis for targeted acts spatial intervention, promises to address myriad crises, from escalating poaching threats biodiversity loss. More than tool, we assert that facilitates diverse manifestations governance align with what Foucault (2008) termed "environmentality." Our central objective analyze how gives new formations power in landscapes--and by extension, other acoustically monitored environments. While acknowledging the potential enhance practices, also find evidence links promise algorithmically derived efficiency expanded forms scientific abstraction, militarized surveillance, capitalist speculation are propagating multiple environments worldwide. analyzing these developments operations environmentality, offer theoretical framework engaging technologies they now proliferating

Язык: Английский

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The uses and implications of avian vocalizations for conservation planning

Conservation Biology, Год журнала: 2020, Номер 35(1), С. 50 - 63

Опубликована: Янв. 28, 2020

There is a growing recognition that animal behavior can affect wildlife conservation, but there have been few direct studies of in conservation programs. However, great deal existing behavioral research be applied the context conservation. Research on avian vocalizations provides an excellent example. The conspicuous nature vocal birds makes it useful tool for monitoring populations and measuring biodiversity, importance goes beyond monitoring. Geographic song variants with population-specific signatures, or dialects, territory formation mate choice. Dialects are influenced by cultural evolution natural selection changes accumulate even during timescale interventions, such as translocations, reintroductions, ex situ breeding. Information from into used to improve planning increase success interventions. Vocalizations confer number benefits practitioners through monitoring, providing baseline data individuals. influence variation formation, choice, gene flow should taken account because differences could create obstacles programs bring multiple together so reduce interventions.Implicaciones y Usos de las Vocalizaciones Aves para la Conservación Planeación Resumen Hay un creciente reconocimiento que el comportamiento puede afectar conservación fauna, pero ha habido pocos estudios directos del en los programas conservación. Sin embargo, una gran cantidad investigación existente sobre aplicarse contexto Las investigaciones vocalizaciones aves son excelente ejemplo. La naturaleza conspicua hace sea herramienta útil monitoreo poblaciones medidas biodiversidad, importancia va más allá monitoreo. variantes geográficas canto con firmas específicas cada población, también conocidas como dialectos, pueden formación territorio elección pareja. Los dialectos están influenciados por evolución selección cambios acumularse incluso durante escala tiempo intervenciones conservación, reubicaciones, reintroducciones reproducción situ. información disponible partir existentes usarse mejorar planeación e incrementar éxito intervenciones. otorgar número beneficios quienes practican través monitoreo, proporcionando línea base individuos. influencia variación territorio, pareja flujo génico deberían considerarse ya diferencias culturales podrían crear obstáculos agrupan diferentes ello reducen intervenciones.目前, 人们已越来越多地认识到动物行为可以影响野生动物保护, 但在保护项目中对动物行为的直接研究还很少。不过, 大量现有的行为研究都可以应用于到保护之中。鸟类声音的研究就是一个很好的例子。鸟类鸣叫行为十分引人注意, 可以作为监测种群和衡量生物多样性的有用工具, 但鸟鸣在保护中的重要意义不仅仅在于监测。鸟类的叫声具有特定种群特征的地理变异, 或称之为方言, 这可以影响领域形成和配偶选择。鸟类的方言受文化演化和自然选择的影响, 且在物种保护措施 (如异地放归、重引入、迁地繁殖) 的时间尺度内也会不断积累变化。来自现有鸟鸣研究的信息可用于改进保护计划、促进干预措施的成功。鸟鸣研究可以通过监测, 提供种群和个体的基础数据, 为保护实践者带来许多好处。然而, 保护实践者还应该考虑鸟类种群的文化差异对领域形成、配偶选择和基因流的影响, 因为文化差异可能会阻碍将来自多个种群的鸟类聚集在一起的保护计划的实施, 从而降低干预措施的成功率。【翻译: 胡怡思; 审校: 聂永刚】.

Язык: Английский

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Mel-frequency cepstral coefficients outperform embeddings from pre-trained convolutional neural networks under noisy conditions for discrimination tasks of individual gibbons

Ecological Informatics, Год журнала: 2024, Номер 80, С. 102457 - 102457

Опубликована: Янв. 4, 2024

Passive acoustic monitoring – an approach that utilizes autonomous recording units allows for non-invasive of individuals, assuming it is possible to acoustically distinguish individuals. However, identifying effective analytical approaches individual identification remains a challenge. Our study investigates how the use different feature representations impacts our ability between female Northern grey gibbons (Hylobates funereus). We broadcast pre-recorded calls from twelve gibbon females and re-recorded at varying distances (directly under tree ~400 m away) using units. evaluated effectiveness automated extraction classify calls: Mel-frequency cepstral coefficients (MFCCs), embeddings three pre-trained neural networks (BirdNET, VGGish, Wav2Vec2), four commonly used indices. supervised classification (random forest) respective compared two unsupervised clustering (affinity propagation hierarchical density-based spatial clustering) evaluate which features were most distinguishing without class labels. MFCCs as baseline previous work has shown they can be high-quality females. Human annotators could only identify in spectrograms recordings <350 playback speaker with signal-to-noise ratio ~ 0 dB, so results focus on these recordings. Using classification, confirmed efficiency one network (BirdNET) individuals closer (signal-to-noise > 10 dB), while remaining did not perform well. Contrary expectations, we found outperformed all other tasks none performed well farther distances. The discriminate animals noisy conditions low important implications populations endangered animals, such gibbons. Focusing high discrimination may rare sounds, future should developing across noisy, real-world limited number training samples.

Язык: Английский

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Birds, bats and beyond: evaluating generalization in bioacoustics models

Frontiers in Bird Science, Год журнала: 2024, Номер 3

Опубликована: Июль 1, 2024

In the context of passive acoustic monitoring (PAM) better models are needed to reliably gain insights from large amounts raw, unlabeled data. Bioacoustics foundation models, which general-purpose, adaptable that can be used for a wide range downstream tasks, an effective way meet this need. Measuring capabilities such is essential their development, but design robust evaluation procedures complex process. review we discuss variety fields relevant bioacoustics as sound event detection, machine learning metrics, and transfer (including topics few-shot domain generalization). We contextualize these using particularities data, characterized by noise, strong class imbalance, distribution shifts (differences in data between training deployment stages). Our hope will help inform protocols more accurately predict ability deployed settings.

Язык: Английский

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