ecoSound-web: an open-source, online platform for ecoacoustics

Darras, Kevin; Pérez, Noemí; Mauladi,; Dilong, Liu; Hanf‐Dressler, Tara; Markolf, Matthias; Wanger, Thomas Cherico

doi:10.12688/f1000research.26369.2

Cited by 8 publications

(10 citation statements)

References 39 publications

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“…Metadata were validated by KD, YC, and FP by checking that all fields were filled and correctly formatted, and then cross-checked by their respective contributors who visualized site maps and recording timelines online on ecoSound-web (Kevin F. A. Darras et al 2023) (https://ecosound-web.de/ecosound_web/collection/index/106). Based on the IUCN GET (Keith et al 2022) definition of four ‘core’ realms, our database covers 215 terrestrial, 53 marine, 14 freshwater, and no subterranean, validated datasets.…”

Section: Resultsmentioning

confidence: 99%

“…New repositories should be created and existing ones made interoperable (Pijanowski, Farina, et al 2011; Parsons et al 2022; Looby et al 2022; Kevin F. A. Darras et al 2023). Fundamental bioacoustics continue to be needed to establish the taxonomic base: While vocalizations of marine and freshwater mammals are rather well studied, the sounds of most other aquatic wildlife still await proper documentation (R. A.…”

Section: Discussionmentioning

confidence: 99%

“…Analogously, re-use of data requires centralised soundscape repositories and species sound libraries (e.g., Xeno-Canto, ChiroVox). New repositories should be created and existing ones made interoperable Parsons et al 2022;Looby et al 2022;Kevin F. A. Darras et al 2023). Fundamental bioacoustics continue to be needed to establish the taxonomic base: While vocalizations of marine and freshwater mammals are rather well studied, the sounds of most other aquatic wildlife still await proper documentation (R. A. Rountree, Juanes, and Bolgan 2020).…”

Section: Discussionmentioning

confidence: 99%

“…KD resampled recordings to 44.1 kHz when higher sampling frequencies were used, and uploaded them on ecoSound-web (https://ecosound-web.de/ecosound_web/collection/show/49) (Kevin F. A. Darras et al 2023), where all recordings were listened to while visually inspecting the spectrograms (FFT window size of 1024) at 15 pixels per second, and creating annotations at a visual density of 1116 pixels per 10 minutes on the left channel. Sounds caused by microphone or recorder self-noise were not annotated.…”

Section: Phony Analysis Case Studymentioning

confidence: 99%

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Worldwide Soundscapes: a synthesis of passive acoustic monitoring across realms

Darras,

Rountree,

Van Wilgenburg

et al. 2024

Preprint

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The need for remote, reliable, and scalable monitoring of plummeting biodiversity amidst mounting human pressures on ecosystems and changing climate has sparked enormous interest in Passive Acoustic Monitoring (PAM) over multiple disciplines and ecosystems. Even though PAM could support UN Sustainable Development Goals and the Global Biodiversity Information Facility by facilitating the evaluation of management and conservation actions, global efforts have not yet been synthesised. We collated metadata from 293 soundscape datasets since 2001 describing sampling sites, deployment schedules, focal taxa, and recording parameters. We quantified biological, anthropogenic, and geophysical soundscape components across nine terrestrial and aquatic ecosystems. This is the first global, quantitative analysis of ecoacoustic sampling coverage across spatial, temporal, and ecological scales. Spatial sampling densities are two orders of magnitude higher in terrestrial realms (33 sites/Mkm2) compared to aquatic realms, while substantial data gaps remain in subterranean realms, extreme environments, and tropical waters. Diel and lunar cycles are well-covered, but in temperate regions, a third of freshwater and terrestrial datasets sample only one season while 57% of marine datasets cover all seasons. Opportunities arise for taxonomically broader sampling on land, for increasing spatial coverage in the high seas, and for more spatially-replicated deployments in freshwater. We illustrate the potential of soundscape ecology to address global questions related to macroecology, conservation biology, and phenology using sample soundscapes. PAM-enabled soundscape ecology has come of age to bridge different disciplines and quantify our progress towards Sustainable Development Goals on land and underwater.

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Section: Resultsmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Phony Analysis Case Studymentioning

confidence: 99%

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Worldwide Soundscapes: a synthesis of passive acoustic monitoring across realms

Darras,

Rountree,

Van Wilgenburg

et al. 2024

Preprint

Self Cite

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“…Thus, researchers may not need to wait for updated versions of BirdNET or resort to multivariate analyses to use BirdNET to identify species that are not already in the classifier but for which they have training data. Third, we encourage researchers with labelled audio samples of a species of interest to make annotated audio data publicly available with archives such as xeno‐canto (https://xeno-canto.org/) or ecoSound‐web (Darras et al, 2023). Many primates have diverse vocal repertoires and although BirdNET has proven capable of identifying many bird species on the basis of multiple very different sounds, prioritizing stereotyped vocalizations used for long‐range communication is likely to be the most efficient path forward.…”

Section: Comparison and Critiquementioning

confidence: 99%

Pairing a user‐friendly machine‐learning animal sound detector with passive acoustic surveys for occupancy modeling of an endangered primate

Wood

Cruz

Kahl

2023

American J Primatol

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Population declines and range contractions due to habitat loss are pervasive among nonhuman primates, with 60% of species threatened with extinction.However, the extensive vocal activity displayed by many primates makes them excellent candidates for passive acoustic surveys. Passive acoustic survey data is increasingly being used to support occupancy models, which have proven to be an efficient means of estimating both population trends and distributions.Passive acoustic surveys can be conducted relatively quickly and at broad scales, but efficient audio data processing has long proven elusive. The machine learning algorithm BirdNET was originally developed for birds but was recently expanded to include nonavian taxa. We demonstrate that BirdNET can accurately and efficiently identify an endangered primate, the Yucatán black howler monkey (Alouatta pigra), by sound in passive acoustic survey data (collected in southeastern Chiapas, Mexico), enabling us to use a single-season occupancy model to inform further survey efforts. Importantly, we also generated data on up to 286 co-occurring bird species, demonstrating the value of integrated animal sound classification tools for biodiversity surveys.BirdNET is freely available, requires no computer science expertise to use, and can readily be expanded to include more species (e.g., its species list recently tripled to >3000), suggesting that passive acoustic surveys, and thus occupancy modeling, for primate conservation could rapidly become much more accessible.Importantly, the long history of bioacoustics in primate research has yielded a wealth of information about their vocal behavior, which can facilitate appropriate survey design and data interpretation.

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