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103 results for “Soundscapes”
Hurricane impacts on a coral reef soundscape
Soundscape ecology is an emerging field in both terrestrial and aquatic ecosystems, and provides a powerful approach for assessing habitat quality and the ecological response of sound-producing species to natural and anthropogenic perturbations. Little is known of how underwater soundscapes respond during and after severe episodic disturbances, such as hurricanes. This study addresses the impacts of Hurricane Irma on the coral reef soundscape at two spur-and-groove fore-reef sites within the Florida Keys USA, using passive acoustic data collected before and during the storm at Western Dry Rocks (WDR) and before, during and after the storm at Eastern Sambo (ESB). As the storm passed, the cumulative acoustic exposure near the seabed at these sites was comparable to a small vessel operating continuously overhead for 1-2 weeks. Before the storm, sound pressure levels (SPLs) showed a distinct pattern of low frequency diel variation and increased high frequency sound during crepuscular periods. The low frequency band was partitioned in two groups representative of soniferous reef fish, whereas the high frequency band represented snapping shrimp sound production. Daily daytime patterns in low-frequency sound production largely persisted in the weeks following the hurricane. Crepuscular sound production by snapping shrimp was maintained post-hurricane with only a small shift (~1.5dB) in the level of daytime vs nighttime sound production for this high frequency band. This study suggests that on short time scales, temporal patterns in the coral reef soundscape were relatively resilient to acoustic energy exposure during the storm, as well as changes in the benthic habitat and environmental conditions resulting from hurricane damage.
Coral Reef Soundscapes - French Polynesia
<p>Repository to support the publication: Unlocking the soundscapes of coral reefs with artificial intelligence. Williams et al (2024) https://doi.org/10.1101/2024.02.02.578582.</p> <p>If using this data please cite or acknowledge the paper.</p> <p>This repository contains all the raw data from the French Polynesian coral reef soundscape dataset.</p>
Soundscape Monitoring Lecture: UCL Dec
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Supplementary material 1 from: Ednie A, Gale T (2021) Soundscapes and protected area conservation: Are noises in nature making people complacent? Nature Conservation 44: 177-195. https://doi.org/10.3897/natureconservation.44.69578
Connections to nature survey
Data from: The sound of recovery: coral reef restoration success is detectable in the soundscape
<p><span>1. Pantropical degradation of coral reefs is prompting considerable investment in their active restoration. However, current measures of restoration success are based largely on coral cover, which does not fully reflect ecosystem function or reef health. </span></p> <p><span>2. Soundscapes are an important aspect of reef health; loud and diverse soundscapes guide the recruitment of reef organisms, but this process is compromised when degradation denudes soundscapes. As such, acoustic recovery is a functionally important component of ecosystem recovery. </span></p> <p><span>3. Here, we use acoustic recordings taken at one of the world's largest coral reef restoration projects to test whether successful restoration of benthic and fish communities is accompanied by a restored soundscape. We analyse recordings taken simultaneously on healthy, degraded (extensive historic blast fishing) and restored reefs (restoration carried out for 1–3 years on previously-degraded reefs). We compare soundscapes using manual counts of biotic sounds (phonic richness), and two commonly used computational analyses (acoustic complexity index [ACI] and sound-pressure level [SPL]).</span></p> <p><span>4. Healthy and restored reef soundscapes exhibited a similar diversity of biotic sounds (phonic richness), which was significantly higher than degraded reef soundscapes. This pattern was replicated in some automated analyses but not others; the ACI exhibited the same qualitative result as phonic richness in a low-frequency, but not a high-frequency bandwidth, and there was no significant difference between SPL values in either frequency bandwidth. Further, the low-frequency ACI and phonic richness scores were only weakly correlated despite showing a qualitatively equivalent overall result, suggesting that these metrics are likely to be driven by different aspects of the reef soundscape. </span></p> <p><span>5<i>. Synthesis and applications: </i>These data show that coral restoration can lead to soundscape recovery, demonstrating the return of an important ecosystem function. They also suggest that passive acoustic monitoring (PAM) might provide functionally important measures of ecosystem-level recovery – but only some PAM metrics reflect ecological status, and those that did are likely to be driven by different communities of soniferous animals. Recording soundscapes represents a potentially valuable tool for evaluating restoration success across ecosystems, but caution must be exercised when choosing metrics and interpreting results. </span></p>
CT-Audiolink : Binaural Soundscapes - http://ct-audiolink.gr
<p>Soundscapes from the project CT - Audiolink. The soundscapes were recorded at Komotini and the Xanthi Bazaar, Greece. A pair of DIY binaural mics (panasonic capsules) and a ZOOM H2N handheld recorder were used.</p>
Data for the paper: "A soundscape approach for a short-term acoustic monitoring of a Critically Endangered Cuban frog"
<p>This 4 excel sheets contain the data sets for the paper “A soundscape approach for a short-term acoustic monitoring of a Critically Endangered Cuban frog” . The data comprises the call rate informatione xtracted from te recordings and the Acoustical index data for descibing the soundscape of the area</p>
Soundscape Datasets for Few-Shot Bird Sound Classification
<p>This repository provides easy access to open-source soundscape datasets of bird sounds, specifically optimized for few-shot classification.</p> <p><code>soundscapes.zip</code> contains evaluation soundscape datasets from the BIRB benchmark (https://arxiv.org/abs/2312.07439), downsampled to 16kHz, preprocessed using CNN14 from PANNs (https://arxiv.org/abs/1912.10211), to select a 6-second window with the highest bird activation, and converted to Pytorch (.pt) format to facilitate usability for evaluating deep neural networks. </p> <p>These preprocessed datasets are employed in the work "<em>Domain-Invariant Representation Learning of Bird Sounds</em>" (https://arxiv.org/abs/2409.08589), which evaluates the few-shot learning capabilities of deep learning models trained on focal recordings (e.g., Xeno-Canto) and tested on soundscape recordings.</p> <h2>Dataset Structure</h2> <h3>Validation Dataset</h3> <ul> <li><strong>POW (</strong><code>pow.pt</code><strong>): </strong>The validation dataset consists of 16,047 examples across 43 classes and is organized as a dictionary with <code>'data'</code> and<code> 'label'</code> keys representing bird sounds and their corresponding labels. Storing the entire validation dataset in a single tensor enables rapid loading and efficient processing, significantly accelerating the validation process. Classes with only one example are removed, as they are insufficient for one-shot classification tasks. Source: https://zenodo.org/records/4656848#.Y7ijhOxudhE</li> </ul> <h3>Test Datasets </h3> <p>Each test dataset is structured with multiple subfolders, each labeled with an eBird species code to represent data for a specific bird species.</p> <ul> <li><strong>SSW (</strong><code>ssw/</code><strong>):</strong> Contains 50,760 examples across 96 classes. Source: https://zenodo.org/records/7079380#.Y7ijHOxudhE</li> <li><strong>NES (</strong><code>coffee_farms/</code><strong>):</strong> Contains 6,952 examples across 89 classes. Source: https://zenodo.org/records/7525349#.ZB8z_-xudhE</li> <li><strong>UHH (</strong><code>hawaii/</code><strong>):</strong> Contains 59,583 examples across 27 classes. Source: https://zenodo.org/records/7078499#.Y7ijPuxudhE</li> <li><strong>HSN (</strong><code>high_sierras/</code><strong>):</strong> Contains 10,296 examples across 19 classes. Source: https://zenodo.org/records/7525805#.ZB8zsexudhE</li> <li><strong>SNE (</strong><code>sierras_kahl/</code><strong>):</strong> Contains 20,147 examples across 56 classes. Source: https://zenodo.org/records/7050014#.Y7ijWexudhE</li> <li><strong>PER (</strong><code>peru/</code><strong>):</strong> Contains 14,768 examples across 132 classes. Source: https://zenodo.org/records/7079124#.Y7iis-xudhE</li> </ul> <p>Code and detailed instructions, including data loading, model implementation, and few-shot evaluation, can be found at: https://github.com/ilyassmoummad/ProtoCLR</p>
Data from: The sound of recovery: coral reef restoration success is detectable in the soundscape
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Data from: Lost at sea: ocean acidification undermines larval fish orientation via altered hearing and marine soundscape modification
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Hurricane impacts on a coral reef soundscape
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Data from: Silent oceans: ocean acidification impoverishes natural soundscapes by altering sound production of the world’s noisiest marine invertebrate
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Soundscapes to Landscapes Acoustic Recordings, Sonoma County, CA, 2017-2022
This dataset holds in situ sound recordings from sites in Sonoma County, California, USA as part of the Soundscapes to Landscapes citizen science project. Recordings were collected from 2017 to 2022 during the bird breeding season (mid-March thru mid-July). Sites (n=1399) were selected across the county; locations were stratified with respect to topographic position and broad land use/land cover types, such as forest, shrubland, herbaceous, urban, agriculture, and riparian areas. Two types of automated recorders were used: Android-based smartphones with attached microphones and AudioMoths. Recorders were deployed at sites for at least 3 days, and programmed to record 1 min of every 10, thus providing temporal sampling through day and night. Each recording was saved in a waveform audio file format (.wav) with 16-bit digitization depth and 44.1 kHz or 48 kHz sampling rate for smartphone and AudioMoth recorders, respectively. The dataset also includes site information including site location when so permitted by landowners in tabular form and photographs of field sites.
Data from: The theory of island biogeography and soundscapes: species diversity and the organization of acoustic communities
Aim: On islands, species richness is reduced and interspecific competition relaxed in relation to the mainland, allowing species to use broader ecological niches. These factors are known to affect diet and morphology, but can also affect communication and acoustic signaling in particular. However, no study has ever compared insular and continental soundscapes to determine to which extent islands present reduced acoustic richness (number of co-vocalizing species) and fewer constraints for vocalizing species. Location: São Tomé Island, Mount Cameroon, Madeira Island, Southern France Taxon: Birds Methods: We compared two pairs of insular and continental soundscapes: one in a temperate zone, the other in the tropics. We recorded sounds produced in similar types of primary forests and measured acoustic richness and ambient noise profiles. We then assessed acoustic niche organization by computing, for each community, species turnover, temporal and frequency overlaps, and acoustic avoidance. Results: We found fewer species co-vocalizing on islands compared to mainland and in temperate compared to tropical region. Ambient noise was louder in the tropics and occupied a wider frequency range, especially on the mainland, thereby revealing a reduction in available acoustic space for tropical mainland birds. In this more crowded and noisy soundscape, species presented a higher acoustic turnover, overlapped less in time and in frequency with each other and acoustically avoided each other more when compared to the three other communities. Main conclusions: Soundscapes differed and imposed fewer constraints on vocalizing species along the species diversity gradient from tropical mainland to temperate island. Acoustic niche partitioning increased with species richness and was associated with increased levels of acoustic interference. Results set a scene for an effect of relaxed competition on song evolution on islands, especially in the tropics.
Data from: Marine soundscape shaped by fishing activity
Marine communities face anthropogenic pressures that degrade ecosystems. Because underwater soundscapes carry information about habitat quality, we explored whether destructive impacts of fishing could be evaluated via the soundscape. Maerl beds are recognized as biodiversity hotspots and they experience major worldwide degradation owing to fishing. We collected field acoustic recordings in maerl beds exposed to different fishing practices. We found that unfished maerl beds were threefold louder and exhibited sound frequencies more diversified than those recorded in fished maerl beds. Analyses of associated fauna samples indicated that snapping shrimps provided a major contribution to the maerl bed soundscape. Moreover, sea urchins and squat lobsters most likely contributed to differences between the soundscapes of unfished and fished maerl beds. Our results supported the idea that the soundscape can provide valuable information on maerl bed ecosystem health related to fishing activity.
Data associated with audioset_soundscape_feats_sethi2019 (Nov 2019 release)
<p>Data associated with the GitHub repo: https://github.com/sarabsethi/audioset_soundscape_feats_sethi2019 for reproduction of analysis and figures from Sethi et. al. (in prep.)</p> <p>Unzip the file provided here, and place all folders in the base directory of the GitHub code.</p> <p> </p>
Effect of Soundscapes on Emotional Distress in Fibromyalgia: a 4×4 Crossover Trial
ClinicalTrials.gov study NCT07231289. IPD Sharing: UNDECIDED. Countries: 1. Publications: 0.
A Study of Soundscapes for Patient Wellbeing
ClinicalTrials.gov study NCT05650073. IPD Sharing: NO. Countries: 1. Publications: 0.
Data from: The theory of island biogeography and soundscapes: species diversity and the organization of acoustic communities
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Data from: Marine soundscape shaped by fishing activity
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OpenNeuro
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