How to count bird calls? Vocal activity indices may provide different insights into bird abundance and behaviour depending on species traits

Methods in Ecology and Evolution, Journal Year: 2024, Volume and Issue: 15(6), P. 1071 - 1083

Published: May 10, 2024

Abstract Passive acoustic monitoring (PAM) has become an important tool for surveying birds, and there is a growing demand approaches to obtain abundance behavioural information from PAM recordings. Changes in bird populations have been assessed by counting recorded calls calculating the vocal activity rate (VAR, i.e. number of per recording time). However, could be counted various ways depending on species traits, these call counts give us different insights abundance, behaviour and/or habitat use. Our study had two goals: (1) present evaluate new indices based counts, detection (DR, 1‐min recordings which presence target vocalization detected) maximum count minute (MAX, found recording); (2) conceptual framework showing how interpretations VAR, DR MAX depend index traits. For three Neotropical with distinct we calculated data 25 sites Yucatan Peninsula (Mexico) that varied their degree anthropogenic disturbance. We moderate high correlations between higher temporal variability VAR compared MAX. also effect sizes disturbance indices. suggest might more reliable relative than whose calling exhibits cue may suitable estimating family or flock size gregarious birds. findings show potential usefulness developing generate ecological hypotheses assess changes behaviour.

Language: Английский

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Using automated passive acoustic monitoring to measure changes in bird and bat vocal activity around hedgerows of different ages

Biological Conservation, Journal Year: 2024, Volume and Issue: 296, P. 110722 - 110722

Published: July 19, 2024

Hedgerows are a semi-natural habitat that supports farmland biodiversity by providing food, shelter, and connectivity. Hedgerow planting goals have been set across many countries in Europe agri-environment schemes (AES) play key role reaching these targets. Passive acoustic monitoring using automated vocalisation identification (automated PAM), offers valuable opportunity to assess changes following AES implementation simple, community-level metrics, such as vocal activity of birds bats. To evaluate whether could be used indicate the effectiveness hedgerow future result-based or hybrid schemes, we surveyed twenty-four hedgerows England classified into chrono-sequence three age categories (New, Young, Old). We recorded 4466 h over course 30 days measured bird bat BirdNET for Kaleidoscope Vocal all birds, bats were modelled with predictors hedgerow, habitat, weather conditions occurring from maturity. show an increase Young Old compared New ones highlight elements surrounding landscape should considered when evaluating on communities. found high precision low species-level observations, argue may novel link payment component PAM results, incentivising effective management farmers landowners.

Language: Английский

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Unsupervised acoustic classification of individual gibbon females and the implications for passive acoustic monitoring

Methods in Ecology and Evolution, Journal Year: 2020, Volume and Issue: 12(2), P. 328 - 341

Published: Oct. 29, 2020

Abstract Passive acoustic monitoring (PAM) has the potential to greatly improve our ability monitor cryptic yet vocal animals. Advances in automated signal detection have increased scope of PAM, but distinguishing between individuals—which is necessary for density estimation—remains a major challenge. When individual identity known, supervised classification techniques can be used distinguish individuals. Supervised methods require labelled training data, whereas unsupervised do not. If signals individuals are sufficiently different, number clusters might represent sampled. The majority applications animal vocalizations focused on quantifying species‐specific call repertoires. However, with interest PAM applications, that needed. Here we use an existing dataset Bornean gibbon female calls known from five sites Malaysian Borneo test three different clustering algorithms (affinity propagation, K ‐medoids and Gaussian mixture model‐based clustering) Calls females readily distinguishable using techniques. For internal validation cluster solutions, calculated silhouette coefficients. external validation, compared results labels standard metric: normalized mutual information. We also accuracy by assigning solutions based which had highest particular female. found affinity propagation consistently outperformed other all metrics used. In particular, was more consistent as increased, when randomly sampled across sites. conclude may useful providing additional information regarding applications. stress although gibbons case study, these will applicable any individually distinct animal.

Language: Английский

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Physics‐based model to predict the acoustic detection distance of terrestrial autonomous recording units over the diel cycle and across seasons: Insights from an Alpine and a Neotropical forest

Methods in Ecology and Evolution, Journal Year: 2022, Volume and Issue: 14(2), P. 614 - 630

Published: Nov. 15, 2022

1. Passive acoustic monitoring of biodiversity is growing fast, as it offers an alternative to traditional aural point count surveys, with the possibility deploy long-term surveys in large and complex natural environments. However, there still a clear need evaluate how frequency-and distancedependent attenuation sound well ambient level impact detection distance soniferous species environments over diel cycles across seasons. This great importance avoid pseudoreplication provide relevant indicators, including richness, abundance density. 2. To address issue distance, we tested field-based protocol Neotropical rainforest (French Guiana, France) Alpine coniferous forest (Jura, France). standardized repeatable method consists recording session directly followed by experiment using calibrated white noise broadcast at different positions along 100 m linear transect. We then used laws reveal basic physics behind propagation attenuation. 3. demonstrate that habitat two kinds forests can be modelled exponential decay law dependence on frequency distance. also report attenuation, first approximation, summarized single value, coefficient habitat. 4. Finally, show predicted knowing contribution each factor, habitat, pressure amplitude bandwidth characteristics transmitted sound. 1 mostly depends may vary factor up 5 cycle These results reinforce take into account variation when performing passive producing reliable indicators.

Language: Английский

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Passive acoustic monitoring in terrestrial vertebrates: a review

Bioacoustics, Journal Year: 2023, Volume and Issue: 32(5), P. 506 - 531

Published: May 10, 2023

Passive acoustic monitoring (PAM) has become increasingly popular in ecological studies, but its efficacy for assessing overall terrestrial vertebrate biodiversity is unclear. To quantify this, performance species detection must be directly compared to that obtained using traditional observer-based (OBM). Here, we review such comparisons across all major classes and identify factors impacting PAM performance. From 41 found while PAM-OBM have been made classes, most focused on birds (65%) North America (52%). performed equally well or better (61%) OBM general. We no statistical difference between the methods total number of detected (excluding reptiles); however, recording period region study influenced relative PAM, analysis method which sampled longer showed impact. Further studies comparing non-avian vertebrates standardised are needed investigate more detail may influence While a valuable tool surveys, combined approach with targeted non-vocal should achieve comprehensive assessment communities.

Language: Английский

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