Passive acoustic monitoring provides a fresh perspective on fundamental ecological questions

Functional Ecology, Journal Year: 2023, Volume and Issue: 37(4), P. 959 - 975

Published: Jan. 20, 2023

Abstract Passive acoustic monitoring (PAM) has emerged as a transformative tool for applied ecology, conservation and biodiversity monitoring, but its potential contribution to fundamental ecology is less often discussed, PAM studies tend be descriptive, rather than mechanistic. Here, we chart the most promising directions ecologists wishing use suite of currently available methods address long‐standing questions in explore new avenues research. In both terrestrial aquatic habitats, provides an opportunity ask across multiple spatial scales at fine temporal resolution, capture phenomena or species that are difficult observe. combination with traditional approaches data collection, could release from myriad limitations have, times, precluded mechanistic understanding. We discuss several case demonstrate estimation, population trend analysis, assessing climate change impacts on phenology distribution, understanding disturbance recovery dynamics. also highlight what horizon PAM, terms near‐future technological methodological developments have provide advances coming years. Overall, illustrate how can harness power ecological era no longer characterised by limitation. Read free Plain Language Summary this article Journal blog.

Language: Английский

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Towards a multisensor station for automated biodiversity monitoring

Basic and Applied Ecology, Journal Year: 2022, Volume and Issue: 59, P. 105 - 138

Published: Jan. 7, 2022

Rapid changes of the biosphere observed in recent years are caused by both small and large scale drivers, like shifts temperature, transformations land-use, or energy budget systems. While latter processes easily quantifiable, documentation loss biodiversity community structure is more difficult. Changes organismal abundance diversity barely documented. Censuses species usually fragmentary inferred often spatially, temporally ecologically unsatisfactory simple lists for individual study sites. Thus, detrimental global their drivers remain unrevealed. A major impediment to monitoring lack human taxonomic expertise that implicitly required large-scale fine-grained assessments. Another amount personnel associated costs needed cover scales, inaccessibility remote but nonetheless affected areas. To overcome these limitations we propose a network Automated Multisensor stations Monitoring Diversity (AMMODs) pave way new generation assessment centers. This combines cutting-edge technologies with informatics expert systems conserve knowledge. Each AMMOD station autonomous samplers insects, pollen spores, audio recorders vocalizing animals, sensors volatile organic compounds emitted plants (pVOCs) camera traps mammals invertebrates. AMMODs largely self-containing have ability pre-process data (e.g. noise filtering) prior transmission receiver storage, integration analyses. Installation on sites difficult access require sophisticated challenging system design optimum balance between power requirements, bandwidth transmission, service, operation under all environmental conditions years. An important prerequisite automated identification databases DNA barcodes, animal sounds, pVOCs, images used as training identification. thus become key component advance field research policy delivering at an unprecedented spatial temporal resolution.

Language: Английский

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BirdNET: applications, performance, pitfalls and future opportunities

Ibis, Journal Year: 2023, Volume and Issue: 165(3), P. 1068 - 1075

Published: Feb. 27, 2023

Automated recognition software is paramount for effective passive acoustic monitoring. BirdNET a free and recently developed bird sound recognizer. I performed literature review to evaluate the current applications performance of BirdNET, which growing in popularity but has been subject few assessments, provide recommendations future studies using BirdNET. Prior research employed wide range purposes have linked detections ecological processes or real‐world monitoring schemes. Among evaluated studies, average precision (% correctly identified) usually ranged around 72–85%, recall rate target species vocalizations detected) 33–84%. Some did not assess performance, hampers interpretation results may poorly informed decisions. Recommendations on how efficiency are provided. The impact confidence score threshold, user‐selected parameter as minimum reported, output although variable among consistent. use high thresholds increases percentage classified lowers proportion calls detected. selection an optimal depend priorities user goals. great tool automated it should be used with caution due inherent challenges identification. continued refinement suggests further improvements coming years.

Language: Английский

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Relating forest structural characteristics to bat and bird diversity in the Italian Alps

Forest Ecology and Management, Journal Year: 2024, Volume and Issue: 554, P. 121673 - 121673

Published: Jan. 21, 2024

The global decline of biodiversity has affected European forests, involving many tree species and forest-dwelling threatened animals. An integrated approach linking forest structure multi-taxon diversity is increasingly needed to maintain the multifunctionality ecosystems. We investigated relationship between structure, deadwood elements, canopy attributes, tree-related microhabitats on bat bird communities in north-eastern Italian Alps. collected bats, data 40 plots encompassing types. To assess different contributions each attribute variables we performed a two-step statistical analysis using generalised linear models, including taxonomical functional indices as response variables. Our findings reveal that bats birds respond differently variation structural characteristics. Specifically, richness was higher forests with both standing lying volume. Shannon index for community high volumes coarse stumps. Moreover, mature trees, gaps, heterogeneous diameter distribution fostered presence generalist birds, while abundance not significant these two taxa. This study demonstrates optimal habitat conditions Alpine are multifaceted. Promoting distinctive elements within stands complex through adaptations management interventions would enhance conservation biodiversity.

Language: Английский

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Low-cost open-source recorders and ready-to-use machine learning approaches provide effective monitoring of threatened species

Ecological Informatics, Journal Year: 2022, Volume and Issue: 72, P. 101910 - 101910

Published: Nov. 12, 2022

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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Soundscape classification with convolutional neural networks reveals temporal and geographic patterns in ecoacoustic data

Ecological Indicators, Journal Year: 2022, Volume and Issue: 138, P. 108831 - 108831

Published: April 5, 2022

Interest in ecoacoustics has resulted an influx of acoustic data and novel methodologies to classify relate landscape sound activity biodiversity ecosystem health. However, indicators used summarize quantify the effects disturbances on can be inconsistent when applied across ecological gradients. This study dataset 487,148 min from 746 sites collected over 4 years Sonoma County, California, USA, by citizen scientists. We built a custom labeled soundscape components deep learning framework test our ability predict these components: human noise (Anthropophony), wildlife vocalizations (Biophony), weather phenomena (Geophony), Quiet periods, microphone Interference. These allowed us balance predicting variation environmental recordings relative time build dataset. patterns space that could useful for planning, conservation restoration, monitoring. describe pre-trained convolutional neural network, fine-tuned with reference data, classification achieving overall F0.75-score 0.88, precision 0.94, recall 0.80 five target components. deployed model all assess their hourly patterns. noted increase Biophony early morning evening, coinciding peak animal community vocalization (e.g., dawn chorus). Anthropophony increased during morning/daylight hours was lowest evenings, diurnal activity. Further, we examined related geographic properties at recording sites. decreased increasing distance major roads, while increased. were comparable more urban/developed agriculture/barren sites, significantly higher than less-developed shrubland, oak woodland, conifer forest results demonstrate broad is possible small datasets, classifications large gain knowledge.

Language: Английский

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Ecological inferences about marine mammals from passive acoustic data

Biological reviews/Biological reviews of the Cambridge Philosophical Society, Journal Year: 2023, Volume and Issue: 98(5), P. 1633 - 1647

Published: May 4, 2023

ABSTRACT Monitoring on the basis of sound recordings, or passive acoustic monitoring, can complement serve as an alternative to real‐time visual aural monitoring marine mammals and other animals by human observers. Passive data support estimation common, individual‐level ecological metrics, such presence, detection‐weighted occupancy, abundance density, population viability structure, behaviour. also some community‐level species richness composition. The feasibility certainty estimates is highly context dependent, understanding factors that affect reliability measurements useful for those considering whether use data. Here, we review basic concepts methods sampling in systems often are applicable mammal research conservation. Our ultimate aim facilitate collaboration among ecologists, bioacousticians, analysts. Ecological applications acoustics require one make decisions about design, which turn requires consideration propagation, signals, storage. One must signal detection classification evaluation performance algorithms these tasks. Investment development automate classification, including machine learning, increasing. more reliable presence than species‐level metrics. Use distinguish individual remains difficult. However, information probability, vocalisation cue rate, relations between vocalisations number behaviour increases estimating density. Most sensor deployments fixed space sporadic, making temporal turnover composition tractable estimate spatial turnover. Collaborations acousticians ecologists most likely be successful rewarding when all partners critically examine share a fundamental target variables, process, analytical methods.

Language: Английский

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A First Assessment of Birdnet Performance at Varying Distances: A Playback Experiment

Ardeola, Journal Year: 2023, Volume and Issue: 70(2)

Published: May 15, 2023

Las vocalizaciones de las aves, como cualquier otra señal acústica, se atenúan con la distancia y, por lo tanto, estructura aves degrada progresivamente. Tal degradación puede tener un impacto en capacidad programas automatizados reconocimiento señales a hora detectar e identificar correctamente aves. BirdNET es reconocedor automatizado cantos pájaros reciente creación y comúnmente empleado investigadores el público. Sin embargo, pocos estudios han evaluado su rendimiento nuestro conocimiento actual sobre cómo variar función o entre especies muy limitado. Aquí, mi objetivo era evaluar si habilidad para tres variaba según distancia, tipo grabadora empleada especies, utilizando una grabación reproducida 10 150 m. La los varió general, disminuyó pero no dos tipos grabadores testados. tasa detección BirdNET, definida porcentaje detectadas identificadas software, fue del 59,9% (499 840 reproducidas). Se identificó manera correcta significativa mayor número cuando emitieron 50 m más cerca (tasa media 92,2%), comparación emitidas esa 34,9%). también significativamente alta chingolo saltamontes reinita encapuchada, vireo gris. El clasificaciones erróneas distancias siguió patrón lineal. Ese estudio proporciona información valiosa que contribuir mejorar futuros muestreos expandir uso censar comunidades usando monitoreo acústico pasivo.—Pérez-Granados, C. (2023). Un primer análisis variables: experimento playback. Ardeola, 70: 221-233.

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Passive acoustic surveys and the BirdNET algorithm reveal detailed spatiotemporal variation in the vocal activity of two anurans

Bioacoustics, Journal Year: 2023, Volume and Issue: 32(5), P. 532 - 543

Published: May 15, 2023

Passive acoustic monitoring has proven effective for broad-scale population surveys of acoustically active species, making it a valuable tool conserving threatened species. However, successful automated classification anuran vocalisations in large audio datasets been limited. We deployed five autonomous recording units at three known breeding areas the Yosemite toad (Anaxyrus canorus), which is and relatively uncommon, sympatric Pacific chorus frog (Pseudacris regilla), widespread more common, to test viability bioacoustics as means supplementing ongoing, human survey efforts. analysed data with BirdNET algorithm, was originally developed birds but expanded include both achieved efficient accurate identification species 2,756 h audio, yielded high-resolution phenological about seasonal daily vocal activity well detection counts. These findings demonstrate that newly machine learning detector, BirdNET, can effectively process passive these Further exploration how may complement existing techniques other Anurans warranted.

Language: Английский

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