Ecoacoustics: A Quantitative Approach to Investigate the Ecological Role of Environmental Sounds

Windy events detection in big bioacoustics datasets using a pre-trained Convolutional Neural Network

Passive Acoustic Monitoring (PAM), which involves using autonomous record units for studying wildlife behaviour and distribution, often requires handling big acoustic datasets collected over extended periods. While these data offer invaluable insights about wildlife, their analysis can present challenges in dealing with geophonic sources. A major issue in the process of detection of target sounds is represented by wind-induced noise. This can lead to false positive detections, i.e., energy peaks due to wind gusts misclassified as biological sounds, or false negative, i.e., the wind noise masks the presence of biological sounds. Acoustic data dominated by wind noise makes the analysis of vocal activity unreliable, thus compromising the detection of target sounds and, subsequently, the interpretation of the results. Our work introduces a straightforward approach for detecting recordings affected by windy events using a pre-trained convolutional neural network. This process facilitates identifying wind-compromised data. We consider this dataset pre-processing crucial for ensuring the reliable use of PAM data. We implemented this preprocessing by leveraging YAMNet, a deep learning model for sound classification tasks. We evaluated YAMNet as-is ability to detect wind-induced noise and tested its performance in a Transfer Learning scenario by using our annotated data from the Stony Point Penguin Colony in South Africa. While the classification of YAMNet as-is achieved a precision of 0.71, and recall of 0.66, those metrics strongly improved after the training on our annotated dataset, reaching a precision of 0.91, and recall of 0.92, corresponding to a relative increment of >28 %. Our study demonstrates the promising application of YAMNet in the bioacoustics and ecoacoustics fields, addressing the need for wind-noise-free acoustic data. We released an open-access code that, combined with the efficiency and peak performance of YAMNet, can be used on standard laptops for a broad user base.

Impact of rural soundscape on environmental restoration: An empirical study based on the Taohuayuan Scenic Area in Changde, China

Previous studies on environmental restorative effects have mainly focused on visual landscapes, and less on the influence of soundscapes on restorative, but soundscapes play a crucial role in restorative environments, especially rural soundscapes, but there is insufficient existing theoretical evidence on the subject. Therefore, this study aims to investigate the influence of Rural Soundscape Perception on Environmental Restoration Perception, and introduces two affective variables, tourism nostalgia and place attachment, to explore the mechanism of Rural Soundscape Perception on Environmental Restoration Perception, as well as the moderating role of the number of trips is also discussed. Based on the theory of restorative environment, this study took the Taohuayuan Scenic Spot in Changde, Hunan Province, China, as the case site, and selected the rural soundscape in the area as the research object; a total of 506 valid data were collected through questionnaire surveys, and structural equation modeling was used to validate the collected data. It was found that rural soundscape perception had a significant positive effect on tourism nostalgia, place attachment, and environmental restoration perception. The results also showed that tourism nostalgia and place attachment mediated the relationship between rural soundscape perception and environmental restoration perception. Additionally, the results revealed that the number of trips did not play a moderating role in the structural relationship between rural soundscape perception and environmental restoration perception. Last, the results of the study shed light on the complex influence path of "rural soundscape perception→tourism nostalgia→place attachment→environmental restoration perception", which provides a new perspective for understanding the mechanism of the rural environment to people's health, and also has a certain guiding significance for the landscape planning of rural tourism sites.

Optimal 2D audio features estimation for a lightweight application in mosquitoes species: Ecoacoustics detection and classification purposes

Mosquitoes are the vector of diseases that kill more than one million people per year worldwide. Surveillance systems are essential for understanding their complex ecology and behaviour. This is fundamental for predicting disease risk caused by mosquitoes and formulating effective control strategies against mosquito-borne diseases such as malaria, dengue, and Zika. Mosquito populations vary heterogeneously in urban and rural landscapes, fluctuating with seasonal and climatic trends and human activity. Several approaches provide environmental data for mosquito mapping and risk prediction. However, they rely traditionally upon labour-intensive techniques such as manual traps. This paper presents the optimal audio features for mosquito identification using ecoacoustics signals to automatically identify different mosquito species from their wingbeat sounds based on popular audio features. The audio selection method uses Density-Based Spatial Clustering of Applications with Noise (DBSCAN) and Silhouette coefficient to evaluate the clusters in the data through the optimal-combined audio features. To classify the mosquito species and distinguish them from environmental-urban noise, the method comprises the Gaussian Mixture Model (GMM) and Gibbs approach for Aedes aegypti, and Culex quinquefasciatus, using the acoustic recordings of their wingbeat signals. Finally, comparing GMM and Gibbs, the two have very similar accuracy, but the classification time is much faster for Gibbs sampling, making it a good candidate for a lightweight solution. These are essential when deploying the described models to monitor mosquito vectors in the wild with Internet of Things (IoT) technologies.

Research on key acoustic characteristics of soundscapes of the classical Chinese gardens

Soundscapes have played an important role in the design and building of classical Chinese gardens. In Chinese classical poetry, biophonies such as bird calls, and geophonies such as wind, are the preferable sound sources. Although these major sound sources have been categorized and summarized by scholars extensively, little research has been conducted to analyze the physical characteristics and preference matrix of these preferred sound sources. Moreover, the perceived loudness of sound in classical Chinese gardens has received more attention from scholars than acoustic frequency. In this study, we selected 12 sound sources that are most typically present in classical Chinese gardens based on extensive literature research on Chinese classical poetry, and acquired respective audio samples from the BBC's library of Sound Effects. Through the spectrogram analyses, pitch detection algorithm and LSTM audio classification methods, the sound sources were classified into discrete sound sources with pitch variation and continuous sound sources with spectral characteristics of white noise or pink noise. The reasoning behind the preference for these two types of sound sources was then discussed from physical and mental healing perspectives, which aims to help provide perspectives on the associated implications in the planning of urban green spaces.

Soundscape analysis using eco-acoustic indices for the birds biodiversity assessment in urban parks (case study: Isfahan City, Iran)

Biophony and anthrophony analysis as part of the urban soundscape is an efficient approach to bird biodiversity monitoring and to studying the impact of noise pollution in urban parks. Here, we analyzed the soundscape composition to monitor the diversity of birds using acoustic indices and machine learning in 21 urban parks of Isfahan, Iran, in spring 2019. To achieve this purpose four-step method was considered: (i) choosing parks and sampling of sound and bird species; (ii) calculated the six acoustic indices; (iii) calculated the six biodiversity indices; and (iv) statistical analysis for predicting biodiversity index from acoustic indices. Three regression models including support vector machine (SVM), random forest (RF), and elastic net regularization (GLMNET) applied the acoustic indices with minimum and maximum recorded thresholds to feature extraction to measure biodiversity indicators. The optimization model was applied to reduce the independent variables. Generally, more than 18,000 samples were modeled for the dependent variables in each model. The regression results demonstrated that the highest R square was related to the songbird (0.93), evenness (0.92), and richness (0.9) indecies in the SVM model and the Shannon index (0.86) in the RF model. The results of acoustics analysis demonstrated that the Acoustic Entropy Index (H), Normalized Difference Soundscape Index (NDSI), Bioacoustics Index (BI), and Acoustic Complexity Index (ACI) indices were suitable because they could serve as proxies for bird richness and activity that reflect differences in habitat quality. Our findings offer using acoustic indicators as an efficient approach for monitoring bird biodiversity in urban parks.

Blown away? Wind speed and foraging success in an acoustic predator

Foraging animals must contend with fluctuating environmental variables that affect foraging success, including conditions like wind noise, which could diminish the usefulness of particular sensory modes. Although the documented impact of anthropogenic noise on animal behavior has become clear, there is limited research on natural noise and its potential influence on mammalian behavior. We investigated foraging behavior in the myrmecophagous bat-eared fox (Otocyon megalotis), a species known to rely predominantly on hearing for prey detection. For a year, we monitored the foraging behavior of 18 bat-eared foxes from a habituated population in South Africa, amidst varying wind speeds (0–15.5 km/h). In contrast to expectations, foraging rates did not generally decline with increasing wind speed, except for foraging rate outside termite patches in fall. Furthermore, wind speed had little correlation with time spent in patches. In winter, however, we observed an increase in foraging rate with increasing wind speed both within and outside patches. At the observed wind speeds, these acoustically driven insectivores continue to forage effectively despite potentially distracting or masking noises. With anthropogenic noise producing sound across a broader frequency range, it is important to examine the responses of these canids to artificial sources of acoustic disturbance as well.

Effects of Soundscape Complexity on Urban Noise Annoyance Ratings: A Large-Scale Online Listening Experiment

Noise annoyance has been often reported as one of the main adverse effects of noise exposure on human health, and there is consensus that it relates to several factors going beyond the mere energy content of the signal. Research has historically focused on a limited set of sound sources (e.g., transport and industrial noise); only more recently is attention being given to more holistic aspects of urban acoustic environments and the role they play in the noise annoyance perceptual construct. This is the main approach promoted in soundscape studies, looking at both wanted and unwanted sounds. In this study, three specific aspects were investigated, namely: (1) the effect of different sound sources combinations, (2) the number of sound sources present in the soundscape, and (3) the presence of individual sound source, on noise annoyance perception. For this purpose, a large-scale online experiment was carried out with 1.2k+ participants, using 2.8k+ audio recordings of complex urban acoustic environments to investigate how they would influence the perceived noise annoyance. Results showed that: (1) the combinations of different sound sources were not important, compared, instead, to the number of sound sources identified in the soundscape recording (regardless of sound sources type); (2) the annoyance ratings expressed a minimum when any two clearly distinguishable sound sources were present in a given urban soundscape; and (3) the presence (either in isolation or combination) of traffic-related sound sources increases noise annoyance, while the presence (either in isolation or combination) of nature-related sound sources decreases noise annoyance.

Artificial Light at Night Drives Earlier Singing in a Neotropical Bird

Simple Summary

Urban birds have to cope with dominant stressors as anthropogenic noise and artificial light at night by adjusting their song traits. However, evidence of such adjustments has been studied thus far in temperate cities, rather than tropical cities. Here, I tested whether noise and light pollution influence earlier singing behavior in a tropical bird, the Saffron Finch. Birds in highly urbanized sites sang earlier at dawn and this timing difference was driven by light pollution instead of anthropogenic noise. Overall, these results suggest that light pollution could have a detrimental impact on the circadian rhythms of urban tropical birds such as daily singing routines.

Abstract

Anthropogenic noise and artificial light at night (ALAN) can disrupt the morning singing routines of urban birds, however, its influence on tropical species remains poorly explored. Here, I assessed the association between light and noise pollution with the dawn chorus onset of the Saffron Finch (Sicalis flaveola) in a city in Colombia. I studied 32 sites comprised of different conditions of urban development based on built cover. I recorded the time of the first song of the Saffron Finch, the conspecific density and measured anthropogenic noise and ALAN using smartphone apps. The findings of this study show that Saffron Finches living in highly developed sites sang earlier at dawn than those occupying less urbanized sites. Unexpectedly, this timing difference was related to ALAN instead of anthropogenic noise, suggesting that light pollution could drive earlier dawn chorus in a tropical urban bird. Saffron Finches could take advantage of earlier singing for signaling territorial ownership among neighbors. Future studies need to assess the influence of ALAN on the dawn chorus timing of Neotropical urban birds.

To drum or not to drum: Selectivity in tree buttress drumming by chimpanzees (Pan troglodytes verus) in the Nimba Mountains, Guinea

Chimpanzees live in fission-fusion social organizations, which means that party size, composition, and spatial distribution are constantly in flux. Moreover, chimpanzees use a remarkably extensive repertoire of vocal and nonvocal forms of communication, thought to help convey information in such a socially and spatially dynamic setting. One proposed form of nonvocal communication in chimpanzees is buttress drumming, in which an individual hits a tree buttress with its hands and/or feet, thereby producing a low-frequency acoustic signal. It is often presumed that this behavior functions to communicate over long distances and is, therefore, goal-oriented. If so, we would expect chimpanzees to exhibit selectivity in the choice of trees and buttresses used in buttress drumming. Selectivity is a key attribute of many other goal-directed chimpanzee behaviors, such as nut-cracking and ant dipping. Here, we investigate whether chimpanzees at the Seringbara study site in the Nimba Mountains, Guinea, West Africa, show selectivity in their buttress drumming behavior. Our results indicate that Seringbara chimpanzees are more likely to use larger trees and select buttresses that are thinner and have a greater surface area. These findings imply that tree buttress drumming is not a random act, but rather goal-oriented and requires knowledge of suitable trees and buttresses. Our results also point to long-distance communication as a probable function of buttress drumming based on selectivity for buttress characteristics likely to impact sound propagation. This study provides a foundation for further assessing the cognitive underpinnings and functions of buttress drumming in wild chimpanzees.

A Fish and Dolphin Biophony in the Boat Noise-Dominated Soundscape of the Cres-Lošinj Archipelago (Croatia)

Spatio-temporal variability of marine soundscapes reflects environmental dynamics and local habitat health. This study characterizes the coastal soundscape of the Cres-Lošinj Natura 2000 Site of Community Importance, encompassing the non-tourist (11–15 March 2020) and the tourist (26–30 July 2020) season. A total of 240 h of continuous recordings were manually analyzed and the abundance of animal vocalizations and boat noise was obtained; sound pressure levels were calculated for the low (63–2000 Hz) and high (2000–20,000 Hz) frequency range. Two fish sound types were drivers of both seasonal and diel variability of the low-frequency soundscape. The first is emitted by the cryptic Roche’s snake blenny (Ophidion rochei), while the second, whose emitter remains unknown, was previously only described in canyons and coralligenous habitats of the Western Mediterranean Sea. The high-frequency bands were characterized by bottlenose dolphin (Tursiops truncatus) vocalizations, indicating dolphins’ use of area for various purposes. Boat noise, however, dominated the local soundscape along the whole considered periods and higher sound pressure levels were found during the Tourist season. Human-generated noise pollution, which has been previously found 10 years ago, is still present in the area and this urges management actions.

Soundscape dynamics of a cold protected forest: dominance of aircraft noise

CONTEXT

One mainstay of soundscape ecology is to understand acoustic pattern changes, in particular the relative balance between biophony (biotic sounds), geophony (abiotic sounds), and anthropophony (human-related sounds). However, little research has been pursued to automatically track these three components.

OBJECTIVES

Here, we introduce a 15-year program that aims at estimating soundscape dynamics in relation to possible land use and climate change. We address the relative prevalence patterns of these components during the first year of recording.

METHODS

Using four recorders, we monitored the soundscape of a large coniferous Alpine forest at the France-Switzerland border. We trained an artificial neural network (ANN) with mel frequency cepstral coefficients to systematically detect the occurrence of silence and sounds coming from birds, mammals, insects (biophony), rain (geophony), wind (geophony), and aircraft (anthropophony).

RESULTS

The ANN satisfyingly classified each sound type. The soundscape was dominated by anthropophony (75% of all files), followed by geophony (57%), biophony (43%), and silence (14%). The classification revealed expected phenologies for biophony and geophony and a co-occurrence of biophony and anthropophony. Silence was rare and mostly limited to night time.

CONCLUSIONS

It was possible to track the main soundscape components in order to empirically estimate their relative prevalence across seasons. This analysis reveals that anthropogenic noise is a major component of the soundscape of protected habitats, which can dramatically impact local animal behavior and ecology.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s10980-021-01360-1.

Fish sounds and boat noise are prominent soundscape contributors in an urban European estuary

Passive acoustic monitoring is a valuable tool for non-intrusive monitoring of marine environments, also allowing the assessment of underwater noise that can negatively affect marine organisms. Here we provide for the first time, an assessment of noise levels and temporal soundscape patterns for a European estuary. We used several eco-acoustics methodologies to characterize the data collected over six weeks within May 2016 - July 2017 from Tagus estuary. Biophony was the major contributor dominated by fish vocalizations and the main driver for seasonal patterns. Maritime traffic was the major source of anthropogenic noise, with daily patterns monitored using 1584 Hz third-octave band level. This indicator avoided biophony and geophony, unlike other indicators proposed for the EU Marine Strategy Framework Directive. Furthermore, the frequency overlap between anthropophony and biophony demands precautionary actions and calls for further research. This study provides an assessment that will be useful for future monitoring and management strategies.

Estimating ecoacoustic activity in the Amazon rainforest through Information Theory quantifiers

Automatic monitoring of biodiversity by acoustic sensors has become an indispensable tool to assess environmental stress at an early stage. Due to the difficulty in recognizing the Amazon's high acoustic diversity and the large amounts of raw audio data recorded by the sensors, the labeling and manual inspection of this data is not feasible. Therefore, we propose an ecoacoustic index that allows us to quantify the complexity of an audio segment and correlate this measure with the biodiversity of the soundscape. The approach uses unsupervised methods to avoid the problem of labeling each species individually. The proposed index, named the Ecoacoustic Global Complexity Index (EGCI), makes use of Entropy, Divergence and Statistical Complexity. A distinguishing feature of this index is the mapping of each audio segment, including those of varied lengths, as a single point in a 2D-plane, supporting us in understanding the ecoacoustic dynamics of the rainforest. The main results show a regularity in the ecoacoustic richness of a floodplain, considering different temporal granularities, be it between hours of the day or between consecutive days of the monitoring program. We observed that this regularity does a good job of characterizing the soundscape of the environmental protection area of Mamirauá, in the Amazon, differentiating between species richness and environmental phenomena.

Sounds of Soil: A New World of Interactions under Our Feet?

Soils are biodiversity-dense and constantly carry chemical flows of information, with our mental image of soil being dark and quiet. But what if soil biota tap sound, or more generally, vibrations as a source of information? Vibrations are produced by soil biota, and there is accumulating evidence that such vibrations, including sound, may also be perceived. We here argue for potential advantages of sound/vibration detection, which likely revolve around detection of potential danger, e.g., predators. Substantial methodological retooling will be necessary to capture this form of information, since sound-related equipment is not standard in soils labs, and in fact this topic is very much at the fringes of the classical soil research at present. Sound, if firmly established as a mode of information exchange in soil, could be useful in an ‘acoustics-based’ precision agriculture as a means of assessing aspects of soil biodiversity, and the topic of sound pollution could move into focus for soil biota and processes.