Temporal patterns in the soundscape of a Norwegian gateway to the Arctic

Aniceto, Ana Sofia; Ferguson, Elizabeth; Pedersen, Geir; Tarroux, A; Primicerio, Raul

doi:10.1038/s41598-022-11183-y

Cited by 3 publications

(3 citation statements)

References 78 publications

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“…ML algorithms such as BirdNET 9 can accurately identify hundreds of species from recordings and anthropogenic noise pollution, while others are used to detect biodiversity pressures such as noise pollution 10 or signs of illegal hunting, such as gunshots 11 . Autonomous acoustic data collection via cellular network connection and self-powered units (via solar power or connection to a grid) is also growing 12,13 , but few studies have put data collection and analysis together to deliver biodiversity insight at scales and resolutions that would not be possible with traditional methods.…”

Section: Mainmentioning

confidence: 99%

National-scale acoustic monitoring of avian biodiversity and phenology

Bick,

Bakkestuen,

Cretois

et al. 2024

Preprint

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Birds migrate over large spatial scales and with complex dynamics which play out over extended time periods, making monitoring of phenology challenging with traditional biodiversity survey approaches. In this study, over a complete spring season, we collected 37,429 hours of audio from 28 networked sensors in forests across the latitudinal extent of Norway to demonstrate how acoustic monitoring can transform avian phenology monitoring. We used machine learning to automatically detect and identify bird vocalizations, and with expert validation found we were able to classify 55 species (14 full migrants) with over 80% precision. We compared audio data to existing avian biodiversity datasets and demonstrated that acoustic surveys could fill large data gaps and improve the temporal resolution at which metrics such as date of arrival for individual species could be estimated. Finally, we combined acoustic data with ecoclimatic variables from satellites and were able to map migratory waves of 10 species across the country at fine spatial resolutions (0.2 degrees). Our study demonstrates how acoustic monitoring can inexpensively and reliably complement existing national-scale biodiversity datasets, delivering high quality data which can support the design and implementation of effective policy and conservation measures.

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Section: Mainmentioning

confidence: 99%

National-scale acoustic monitoring of avian biodiversity and phenology

Bick,

Bakkestuen,

Cretois

et al. 2024

Preprint

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“…Passive acoustic monitoring using long-term recorders is a wellvetted tool that provides an indirect measure of marine mammal temporal and spatial occurrence (Wiggins & Hildebrand, 2007;Lammers et al, 2008;Aniceto et al, 2022). Continuous acoustic monitoring is becoming more prevalent and dependable as a conservation approach, leading to recommendations for longer term acoustic studies during offshore wind development operations and incorporation of hydrophones at long-term monitoring sites (Trowbridge et al, 2019;Van Parijs et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

Acoustic indices respond to specific marine mammal vocalizations and sources of anthropogenic noise

Ferguson¹,

Clayton

Sakai

2023

Front. Mar. Sci.

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Using passive acoustic methods for biodiversity conservation and effective ecosystem monitoring is hindered by laborious, human-mediated processes of accurately identifying biologic and anthropogenic sounds within large datasets. Soundscape ecology provides a potential means of addressing this need through the use of automated acoustic-based biodiversity indices, which show promise in representing biodiversity in terrestrial environments. However, the direct relationship between specific underwater sounds and acoustic index measurements are largely unexplored. Using passive acoustic data collected from three broadband hydrophones within the Ocean Observatories Initiative’s cabled arrays in the Pacific northwest, we identified periods of vocalizing marine mammals and sources of anthropogenic noise. Automated calculations of seven acoustic indices were compared were compared across biologic and anthropogenic sound type and call parameters. Although several index measurements did not vary significantly, the Acoustic Complexity Index (ACI) measurements increased in response to echolocation clicks from sperm whales (Physeter macrocephalus) and burst pulses originating from unidentified delphinid species. Measurements of the Bioacoustic Index (BI) decreased dramatically in responses sperm whale echolocation clicks, a more obvious trend when loud clicks were parsed from moderate and quite clicks. Correlations coefficient and confidence interval values between ACI and BI measurements and call characteristics from sperm whales indicate a moderate to strong relationship, which was not found in correlations with delphnid calls. A generalized linear mixed-effect model indicated multiple species and sound types contribute significantly to the variation of several index measurements. Noise generated by passing ships consistently resulted in decreased values for the Normalized Difference Soundscape Index (NDSI) and Total Entropy (H) as compared to quiet periods and periods with vocalizing marine mammals. These findings provide information on the relationship between several acoustic indices and specific underwater sounds produced by marine mammals and anthropogenic sources. This ground-truthing endeavor expands the understanding of acoustic indices and their potential use as a tool for conservation and ecosystem health management purposes.

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“…Particularly, much of the theoretical framework and terms of Ecoacoustics in the subfield of soundscape ecology adheres to those analogous to many supported tenants of Landscape Ecology Theory (Pijanowski et al, 2011;Farina, 2014) including patches, ecotopes, temporal patterns, and spatial heterogeneity (Whittaker et al, 1973;Whittaker et al, 1975;Turner, 1989;Juan et al, 2023) (Table 1). However, much of our current understanding of the spatio-temporal attributes of the sonic environment have centered on soundscapes (Krause et al, 2011;Gage and Axel, 2014;Mullet et al, 2016;Aniceto et al, 2022) and acoustic communities (Lellouch et al, 2014;de Camargo et al, 2019;Farina et al, 2021a).…”

Section: Introductionmentioning

confidence: 99%

Sonotopes reveal dynamic spatio-temporal patterns in a rural landscape of Northern Italy

Farina,

Mullet,

Bazarbayeva

et al. 2023

Front. Ecol. Evol.

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A sonotope is characterized as a sonic patch that forms a hierarchical link between a finer, local scaled acoustic community and the coarser landscape scaled sonoscape. Unfortunately, the concept of sonotopes has yet to be empirically supported. We tested the hypothesis that a spatially explicit sample of sonic information from a heterogeneous landscape would exhibit spatially unique sonotopes with distinct spatio-temporal patterns and acoustic communities. We used the Acoustic Complexity Index (ACItf) to analyze sonic information (WAV) gathered from an array of 10 sound recorders deployed within a lattice of 10, 4-ha hexagonal sample sites distributed evenly throughout a 48-ha undivided heterogeneous landscape in Northern Italy. We examined the temporal patterns of sonic activity (ACItf) between seasons (March – July and August – November 2021) and across five astronomical periods of a 24-h day (Night I, Morning Twilight, Day, Evening Twilight, and Night II). We used cluster analyses to identify sonotopes from groupings of similar ACItf values for each sample site and visualized the spatial arrangements of sonotopes throughout our study area between seasons and among astronomical periods. Sonic activity from bird biophonies increased in March – July during the Day but in August – November greater sonic activity shifted to crepuscular and nocturnal periods with the biophonies from crickets. Sonotopes exhibited spatially unique, dynamic arrangements of patch size and placement depending on the season and astronomical period. We discuss how acoustic communities and continuous geophonies play a role in the arrangement of sonotopes and their relation to the sonoscape.

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Temporal patterns in the soundscape of a Norwegian gateway to the Arctic

Cited by 3 publications

References 78 publications

National-scale acoustic monitoring of avian biodiversity and phenology

National-scale acoustic monitoring of avian biodiversity and phenology

Acoustic indices respond to specific marine mammal vocalizations and sources of anthropogenic noise

Sonotopes reveal dynamic spatio-temporal patterns in a rural landscape of Northern Italy

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