Playback‐Aided Surveys and Acoustic Monitoring in the Detection of the Endangered Forest Owlet Athene blewitti DOI Creative Commons
Amrutha Rajan, Aditi Neema, Pranav Trivedi

et al.

Ecology and Evolution, Journal Year: 2024, Volume and Issue: 14(11)

Published: Nov. 1, 2024

ABSTRACT Monitoring rare and endangered species over the long term is challenging due to limited historical data comparable methods. Climate landscape changes can significantly impact distributions, driving some extinction. The Forest Owlet an bird considered extinct but rediscovered after 113 years in 1997. Since its rediscovery, followed by description of calls, there have been regular recent sightings from newer locations, leading downlisting IUCN Red List critically endangered. In Dang region Gujarat, India, no records despite previous systematic ornithological studies three decades, multiple last few years. Although we now know a little more about broad association occurrence with habitat climate variables, major focus this study estimate reasons for “appearance” Dangs. We revisited locations past surveys determine if currently found sites where it was previously unrecorded. also examine whether new survey methods using playback call could enhance detection. During resurveys, located at new, unrecorded locations. Analyses satellite imagery products revealed significant broader landscape, including loss native forests, increased agriculture, shifts mean maximum temperature rainfall. Our research suggests detection, although effectiveness varies across landscapes. A detection strategy long‐term monitoring developed different acoustic detectors. An effective distance 300 m within achieved automated recording units (ARUs). responds change, cause reports remains undetermined. However, detections techniques involving bioacoustics. recommend these carefully future baseline studies, which are urgently required.

Language: Английский

Worldwide Soundscapes: a synthesis of passive acoustic monitoring across realms DOI Creative Commons
Kevin Darras, Rodney A. Rountree, Steven L. Van Wilgenburg

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: April 14, 2024

Abstract The urgency for remote, reliable, and scalable biodiversity monitoring amidst mounting human pressures on climate ecosystems has sparked worldwide interest in Passive Acoustic Monitoring (PAM), but there been no comprehensive overview of its coverage across realms. We present metadata from 358 datasets recorded since 1991 above land water constituting the first global synthesis sampling spatial, temporal, ecological scales. compiled summary statistics (sampling locations, deployment schedules, focal taxa, recording parameters) used eleven case studies to assess trends biological, anthropogenic, geophysical sounds. Terrestrial is spatially denser (42 sites/M·km 2 ) than aquatic (0.2 1.3 oceans freshwater) with only one subterranean dataset. Although diel lunar cycles are well-covered all realms, marine (65%) comprehensively sample seasons. Across biological sounds show contrasting activity, while declining distance equator anthropogenic activity. PAM can thus inform phenology, macroecology, conservation studies, representation be improved by widening terrestrial taxonomic breadth, expanding high seas, increasing spatio-temporal replication freshwater habitats. Overall, shows considerable promise support efforts.

Language: Английский

Citations

12
The sound of restored soil: using ecoacoustics to measure soil biodiversity in a temperate forest restoration context DOI Creative Commons
Jake M. Robinson, Martin F. Breed, Carlos Abrahams

et al.

Restoration Ecology, Journal Year: 2023, Volume and Issue: 31(5)

Published: May 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.

Language: Английский

Citations

22
Poor performance of acoustic indices as proxies for bird diversity in a fragmented Amazonian landscape DOI
Thiago Bicudo, Diego Llusia, Marina Anciães

et al.

Ecological Informatics, Journal Year: 2023, Volume and Issue: 77, P. 102241 - 102241

Published: July 29, 2023

Language: Английский

Citations

18
Species-specific spatial and temporal variability in anuran call detection: implications for deploying autonomous recording units DOI Creative Commons
Andrew Hall,

Amelia Walcott,

Anaïs Borrell

et al.

Wildlife Research, Journal Year: 2025, Volume and Issue: 52(2)

Published: Jan. 20, 2025

Context Ecosystem assessment using acoustic monitoring technologies can be an efficient method for determining species community composition and breeding activity, but many factors affect the quality of acoustics-data subsequent level confidence in derived inferences. Aims We aimed to assess variability detection probabilities five frog autonomous recording units (ARUs) deployed across a single 1 km2 wetland, comprising lagoon surrounding area, subsequently determine required number ARUs with 95% presence–absence data. Methods Ten were two rings around lagoon’s centroid close water’s edge. Occupancy models used derive calling from data describing temporal pattern at each site, which call recognition software. Key results Only target detected by all 10 ARUs. All species’ non-zero ARU varied factor 14, coefficients variation individual probability seven. Simulations revealed seven or eight are achieve confirming presence either highest observed probabilities, given they present calling. Even ten ARUs, successful other three known on any day was less than 40%. Conclusions Effective not achieved targeted several during period when hydrology season suited recruitment activity. Despite being locations favourable detecting species, stochastic drove spatial resulting markedly different species. Implications Data automated may representative due spatiotemporal that varies To improve deployment strategies, priori knowledge typical recorders set confidence.

Language: Английский

Citations

0
Mitigating bias in long‐term terrestrial ecoacoustic studies DOI Creative Commons
David Jarrett, R. Barnett, Tom Bradfer‐Lawrence

et al.

Journal of Applied Ecology, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 14, 2025

Abstract Long‐term biodiversity monitoring is needed to track progress towards ambitious global targets reduce species loss and restore ecosystems. The recent development of cheap robust acoustic recording devices offers a cost‐effective means gathering standardised long‐term datasets. Accounting for sources bias in ecological research fundamental part the study design process. To highlight this issue context terrestrial ecoacoustic monitoring, here we collate discuss arising from (i) hardware devices, (ii) firmware, software analysis tools (iii) deployment environment. One important source unavoidable changes hardware—to demonstrate how potentially introduces bias, present two case studies comparing output simultaneous recordings different recorders. mitigate biases, recommend effective documentation environmental hardware‐related variables, as well data storage strategy that facilitates reanalysis. Additionally, use regular calibration tests measure variation detection space will facilitate analytical approaches or post‐hoc AI solutions remove unwanted biases. Synthesis applications : suggested mitigations described be relevance manufacturers, researchers conservation practitioners. Researchers practitioners must fully aware relevant biases when designing should incorporate appropriate into their design.

Language: Английский

Citations

0
Letting ecosystems speak for themselves: An unsupervised methodology for mapping landscape acoustic heterogeneity DOI
Nestor Rendon, Maria J. Guerrero, Camilo Sánchez‐Giraldo

et al.

Environmental Modelling & Software, Journal Year: 2025, Volume and Issue: unknown, P. 106373 - 106373

Published: Feb. 1, 2025

Language: Английский

Citations

0
Leveraging passive acoustic monitoring for result-based agri-environmental schemes: Opportunities, challenges and next steps DOI Creative Commons
Anna F. Cord, Kevin Darras, Ryo Ogawa

et al.

Biological Conservation, Journal Year: 2025, Volume and Issue: 305, P. 111042 - 111042

Published: March 17, 2025

Language: Английский

Citations

0
Methods of acoustic data processing affect species detectability in passive acoustic monitoring of multi‐species playback DOI Open Access
Dominika Winiarska, Paweł Szymański, Tomasz S. Osiejuk

et al.

Ibis, Journal Year: 2025, Volume and Issue: unknown

Published: March 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.

Language: Английский

Citations

0
From valleys to peaks: characterizing soundscapes in the Northern European Limestone Alps DOI Creative Commons
Manuel Ebner, Ulrike Tappeiner, Uta Schirpke

et al.

Landscape Ecology, Journal Year: 2025, Volume and Issue: 40(5)

Published: April 29, 2025

Language: Английский

Citations

0
Soundscape components inform acoustic index patterns and refine estimates of bird species richness DOI Creative Commons
Colin A. Quinn, Patrick Burns, Christopher R. Hakkenberg

et al.

Frontiers in Remote Sensing, Journal Year: 2023, Volume and Issue: 4

Published: May 15, 2023

Ecoacoustic monitoring has proliferated as autonomous recording units (ARU) have become more accessible. ARUs provide a non-invasive, passive method to assess ecosystem dynamics related vocalizing animal behavior and human activity. With the ever-increasing volume of acoustic data, field grappled with summarizing ecologically meaningful patterns in recordings. Almost 70 indices been developed that offer summarized measurements bioacoustic activity conditions. However, their systematic relationships varying sonic conditions are inconsistent lead non-trivial interpretations. We used an dataset over 725,000 min recordings across 1,195 sites Sonoma County, California, evaluate relationship between 15 established using five soundscape components classified convolutional neural network: anthropophony (anthropogenic sounds), biophony (biotic geophony (wind rain), quiet (lack emergent sound), interference (ARU feedback). generalized additive models ecoacoustic indicators avian diversity. Models included explained degrees performance (avg. adj-R 2 = 0.61 ± 0.16; n 1,195). For example, we found normalized difference index was most sensitive while being less influenced by ambient sound. all were affected non-biotic sound sources degrees. combined highly predictive modeling bird species richness (deviance 65.8%; RMSE 3.9 species; 1,185 sites) for targeted, morning-only periods. Our analyses demonstrate confounding effects on indices, recommend applications be based anticipated environments. instance, presence extensive rain wind, suggest minimally geophony. Furthermore, evidence measure biodiversity (bird richness) is aggregate biotic (biophony). This adds recent work identifies reliable generalizable biodiversity.

Language: Английский

Citations

7