Search Results (24)

Small urban parks act as local acoustic refuges, yet their nocturnal soundscapes are rarely quantified at fine spatial scales. We assessed within-park spatio-temporal heterogeneity in Langiewicz Park (~1.1 ha), Wrocław, Poland, using a network of five autonomous AudioMoth recorders mounted on lighting poles at 3.5 m height during early spring campaigns (March–April 2025). Continuous nocturnal recordings (18:00–06:00) were collected, and for each recording, we computed a suite of ecoacoustic indicators capturing acoustic energy (RMS), biophony–anthrophony balance (NDSI), temporal complexity (ACI), spectral diversity (ADI), biotic activity (BI), and acoustic Entropy (H). Indicator time series were aggregated to 15 min resolution to characterise nocturnal trajectories, and dominant patterns were quantified using polynomial trend models and principal component analysis. Despite the small park area and inter-sensor spacing of 50–70 m, indicator distributions differed significantly among microphone locations, with particularly strong spatial contrasts observed in NDSI and BI. Seasonal shifts between March and April further modified the multivariate soundscape structure and the positioning of monitoring sites. These results demonstrate fine-scale nocturnal heterogeneity within a single compact urban park. Our findings suggest that multipoint monitoring design is essential to capture the complex micro-soundscape structures in urban green spaces that single-sensor approaches typically overlook. Full article

The recent growth of Blue Economy-related human activities has increased underwater noise pollution. Sound is a key factor in ensuring the well-being of marine animals as it allows them to communicate with each other and extract valuable information from the environment. Although the Marine Strategy Framework Directive requires monitoring programs to achieve good environmental status, there remains a significant deficit of information concerning three key domains: the characteristics of the underwater soundscape, its transformation due to anthropogenic activities, and the effects of noise on marine animals. This study aimed to evaluate the impact of anthropogenic activities on marine acoustic environments. Acoustic metrics and ecoacoustic indices were applied to characterise variability and assess daily, weekly, and seasonal patterns, as well as the effects of trawling restrictions. Three underwater soundscapes were compared in this study: two natural environments in the Mediterranean Sea and one artificial environment, a land-based fish farm tank. High anthropogenic noise levels were found, primarily due to fishing vessels near the selected locations. Similarly, the soundscape exhibited notable seasonal variations (annual and weekly), demonstrating a significant dependence on tourist activities. The results highlight the benefits of acoustic parameters as a tool for monitoring environmental conditions over time. Full article

Passive acoustic monitoring (PAM) is a valuable tool for ecological research, but many eco-acoustic indices show inconsistent correlations with biodiversity due to methodological variability and environmental noise. We propose a complementary, physically interpretable approach using energy-derived metrics. We analyzed audio recordings from three sites near a major highway in the Ticino River Park (Milan, Italy) using 1 sec equivalent continuous sound pressure level (Leq_1s), peak interval statistics, maximal-overlap discrete-wavelet transform (MODWT), and temporal fractal analysis. This multi-resolution type of approach enabled frequency-specific tracking of acoustic energy and temporal structure. Our results reveal site-specific differences: Site 3, the most distant from the highway, showed higher high-frequency energy and longer temporal persistence, suggesting richer biophonic activity. Site 1, the closest to the highway, displayed flatter spectral profiles and faster autocorrelation decay. Diel patterns were reflected in hourly Leq trends, while fractal analysis revealed frequency- and site-dependent acoustic memory. These automated findings were corroborated by expert annotations of bird activity and traffic. The integration of Leq_1s, peak metrics, and wavelet decomposition offers a suitable framework for soundscape characterization, with strong potential for long-term ecoacoustic monitoring and habitat quality assessment in complex environments. Full article

Urban soundscapes are increasingly recognized as fundamental for both ecological integrity and human well-being, yet the complex interplay between the vegetation structure, seasonal dynamics, and microclimatic factors in shaping these soundscapes remains poorly understood. This study tests the hypothesis that vegetation structure and seasonally driven biological activity mediate the balance and the quality of the urban acoustic environment. We investigated seasonal and spatial variations in five acoustic indices (NDSI, ACI, AEI, ADI, and BI) within a historical urban garden in Castelfranco Veneto, Italy. Using linear mixed-effects models, we analyzed the effects of season, microclimatic variables, and vegetation characteristics on soundscape composition. Non-parametric tests were used to assess spatial differences in vegetation metrics. Results revealed strong seasonal patterns, with spring showing increased NDSI (+0.17), ADI (+0.22), and BI (+1.15) values relative to winter, likely reflecting bird breeding phenology and enhanced biological productivity. Among microclimatic predictors, temperature (p < 0.001), humidity (p = 0.014), and solar radiation (p = 0.002) showed significant relationships with acoustic indices, confirming their influence on both animal behaviour and sound propagation. Spatial analyses showed significant differences in acoustic patterns across points (Kruskal–Wallis p < 0.01), with vegetation metrics such as tree density and evergreen proportion correlating with elevated biophonic activity. Although the canopy height model did not emerge as a significant predictor in the models, the observed spatial heterogeneity supports the role of vegetation in shaping urban sound environments. By integrating ecoacoustic indices, LiDAR-derived vegetation data, and microclimatic parameters, this study offers novel insights into how vegetational components should be considered to manage urban green areas to support biodiversity and foster acoustically restorative environments, advancing the evidence base for sound-informed urban planning. Full article

The ongoing decline in global biodiversity constitutes a critical challenge for environmental science, necessitating the prompt development of effective monitoring frameworks and conservation protocols to safeguard the structure and function of natural ecosystems. Recent progress in ecoacoustic monitoring, supported by advances in artificial intelligence, might finally offer scalable tools for systematic biodiversity assessment. In this study, we evaluate the performance of BirdNET, a state-of-the-art deep learning model for avian sound recognition, in the context of selected bird species characteristic of the Italian Alpine region. To this end, we assemble a comprehensive, manually annotated audio dataset targeting key regional species, and we investigate a variety of strategies for model adaptation, including fine-tuning with data augmentation techniques to enhance recognition under challenging recording conditions. As a baseline, we also develop and evaluate a simple Convolutional Neural Network (CNN) trained exclusively on our domain-specific dataset. Our findings indicate that BirdNET performance can be greatly improved by fine-tuning the pre-trained network with data collected within the specific regional soundscape, outperforming both the original BirdNET and the baseline CNN by a significant margin. These findings underscore the importance of environmental adaptation and data variability for the development of automated ecoacoustic monitoring devices while highlighting the potential of deep learning methods in supporting conservation efforts and informing soundscape management in protected areas. Full article

As climate change alters subarctic ecosystems and human activities in Alaska, ecological baselines are critical for long-term conservation. We applied an ecoacoustic approach to characterize the ecological conditions of a rapidly deglaciating region in Kenai Fjords National Park, Alaska. Using automated recording units deployed at increasing distances from a road, we collected over 120,000 one-minute audio samples during the tourist seasons of 2021 and 2022. Ecoacoustic indices—Sonic Heterogeneity Index (SHI_tf), Spectral Sonic Signature (SSS), Weighted Proportion of Occupied Frequencies (wPOF), and Normalized Difference Sonic Heterogeneity Index (NDSHI)—were used to measure spatio-temporal patterns of the sonoscape. Results revealed higher sonic heterogeneity near the road attributed to technophony (vehicles) and geophony (wind) that spanned across the frequency spectrum, masking mid-high frequency biophony. Seasonal phenology and diel variations reflected ecological and human rhythms, including biophony from the dawn chorus from May–June, technophony from vehicle-based tourism from July–September, and decreased sonic activity in the form of geophonic ambience in October. Low-frequency geophonies were prevalent throughout the sonoscape with more natural sounds at greater distances from the road. Our findings demonstrate the benefits of using ecoacoustic methods to assess ecosystem dynamics for establishing ecological baselines useful for future comparisons in rapidly changing environments. Full article

Urban regions represent complex acoustic environments with few respites from noise other than small or remote patches of green infrastructure (GI). Recent noise action planning in the German Ruhr region indicates that urban expansion is fueling encroachment upon GI and subsequently the loss of quiet areas. A systematic exploration of this loss in Germany is needed. An explorative systematic review on Scopus with snowballing supports the synthesis of a conceptual framework linking acoustically relevant ecosystem services with GI. Our review identifies natural quietness, abatement, connection to nature, positive soundscape perception, fidelity, and bird sound presence as sound-related ecosystem functions or services. Empirical case studies justify the need to better understand the link between GI, ecosystem services, and the acoustic environment. Guidance for quiet area assessments in the EU to address this research gap in noise action planning is an emerging topic and needs further study. To address the knowledge gap and provide quiet area assessment guidance, we present a stratified habitat-based acoustic study design for a multi-community area in the middle of the German Ruhr region. A multi-tier sample of 120 locations across eleven habitat and land use strata in the Ruhr is presented, pointing out the scarcity of protected biotopes and large biotope complexes in the study area. This work is a contribution towards a conceptual and methodological basis for quiet area assessment, especially in German and EU noise action planning. Full article

Ecoacoustics examines the interactions between soundscapes, ecological processes, and anthropogenic disturbance. Acoustic communication is crucial for wildlife, making noise pollution a key factor in shaping biodiversity, though its effects are also modulated by habitat characteristics. In this work, we assess the influence of highway noise and vegetation structure on the soundscape and avian distribution of the Moriano oxbow lake (Bereguardo, PV, Italy), a Site of Community Importance in the Ticino Valley Regional Park. A two-week monitoring campaign (April 2022) used eight recorders arranged in a grid to analyze soundscape dynamics through eight ecoacoustic indices (ACI, ADI, AEI, BI, NDSI, H, DSC, ZCR). Vegetation surveys quantified tree diversity and structural parameters such as basal area, height, stem density, biomass, and leaf cover. Correlation analyses revealed that Quercus robur abundance and tree diversity significantly influenced the acoustic environment, while bird richness correlated positively with vegetation biomass and Quercus robur presence. Highway proximity was a key structuring factor, with indices (ADI, H, NDSI, ACI) increasing with distance. These findings underscore the dual role of noise and vegetation in shaping soundscapes and highlight the importance of incorporating habitat features into ecoacoustic assessments to better understand biodiversity patterns in anthropized landscapes. Full article

Urban noise pollution significantly degrades people’s health and well-being and, furthermore, traditional noise reduction strategies often overlook individual perception differences. This study proposed to explore the role of eco-acoustic indices in capturing the interplay between biophony, geophony, and anthrophony, and their relationship with classical acoustic metrics and the perceived soundscapes within a University Campus (University of “Mila-no-Bicocca”, Italy). The study area is divided in to eight different sites in “Piazza della Scienza” square. Sound measurements and surveys conducted in June 2023 across four paved sites and adjacent courtyards involved 398 participants (51.7% female, 45.6% male, 2.7% other). The main noise sources included road traffic, technical installations, and human activity, where traffic noise was more prominent at street-level sites (Sites 1–4) and technical installations dominated underground courtyards (6–8). Human activity was most noticeable at Sites 4–8, especially at Site 5, which showed the highest activity levels. A circumplex model revealed that street-level sites were less pleasant and eventful than courtyards. Pairwise comparisons of noise variability showed significant differences among sites, with underground locations offering quieter environments. Eco-acoustic analysis identified two site groups: one linked to noisiness and spectral features, the other to intensity distribution metrics. Technical installations, people, and traffic noises showed distinct correlations with acoustic indices, influencing emotional responses like stimulation and liveliness. These findings emphasize the need to integrate subjective perceptions with objective noise metrics in soundscape descriptions. Full article

Several researchers have tried to find relationships between acoustic indices and vocal animal communities to use acoustic indices as a passive monitoring method, as human-derived surveys are expensive, time-consuming, and suffer from observer bias. However, supplanting manual surveys with acoustic indices is a daunting task, considering effective indices for biological monitoring need to differentiate biologically relevant sounds from the broader soundscape, including anthropophony and geophony. The objective of our study was to test how well acoustic indices can be applied to avian community monitoring within a temperate grassland ecosystem in North America. We collected avian community data and calculated six commonly used acoustic indices from recordings in an intact lowland tallgrass prairie in the Central Platte River Valley of Nebraska throughout the avian breeding seasons of 2019–2021. Singular acoustic indices had only weak correlations with all community metrics. However, multivariate models including multiple acoustic indices showed potential for monitoring grassland bird abundance when anthropophony was considered. Fragmented grassland remnants likely experience significant anthropophony that needs to be accounted for when monitoring avian populations. Additionally, multivariate models incorporating several indices may provide a more accurate prediction of avian biophony than individual acoustic indices. Full article

Anthropized green zones in urban areas and their surroundings develop complex soundscapes, characterized by the presence of multiple sound sources. This makes the interpretation of the sound environment challenging. To accurately distinguish between different sound components, a combination of selective analysis techniques is necessary. Urban parks are significant and interesting examples, where the interaction between anthropogenic and biophonic sound sources persists over broad temporal and spatial scales, making them important sites for evaluating local soundscape quality. In this work, we suggest that a transfer entropy measure (TEM) may more efficiently disentangle relevant information than traditional eco-acoustic indices. The two study areas were Parco Nord in Milan, Italy, and Ticino River Park, also in Italy. For Parco Nord, we used 3.5-h (1-min interval) recordings taken over an area of about 20 hectares, employing 16 sensors. For the Ticino River Park, we used 5-day (1 min plus 5 min pause) recordings taken over an area of approximately 10 hectares, using a smaller set of eight sensors. We calculated the classical eco-acoustic indices and selected two of them: the acoustic entropy (H) and the bio-acoustic index (BI), calculated for all sites with a 1 min time resolution obtained after a principal components analysis. For these time series, we studied the TEM of all sites in both directions, i.e., from one site to another and vice-versa, resulting in asymmetric transfer entropies depending on the location and period of the day. The results suggest the existence of a network of interconnections among sites characterized by strong bio-phonic activity, whereas the interconnection network is damped at sites close to sources of traffic noise. The TEM seems to be independent of the choice of eco-acoustic index time series, and therefore can be considered a robust index of sound quality in urban and wild park environments, providing additional structural insights complementing the traditional approach based on eco-acoustic indices. Specifically, TEM provides directional information about intersite sound connectivity in the area of study, enabling a nuanced understanding of the sound flows across varying anthropogenic and natural sound sources, which is not available using conventional methods. Full article

Investigating the sonosphere can serve as a valuable proxy for understanding various ecosystem processes. Consequently, an ecoacoustic perspective broadens our capacity to understand how airborne sounds interact along an ecotone at the soil surface with the subterranean sounds generated within a pedon. We explored techniques that could detect, quantify, and analyze the sonic dimensions of a sonosphere in the form of sounds within a unit of soil (sonopedon), sounds from a landscape unit (sonotope), and the sonic ecotone (sonotone) where these phenomena converge. We recorded sounds for 24 h over 20 days in September 2024 at 40 sites distributed evenly across a small rural parcel of agricultural land in Northern Italy. We utilized a sound recording device fabricated with a sonic probe that simultaneously operated inside the soil and the grounds’ surface, which successfully captured sounds attributable both to the soilscape and to the landscape. We calculated the Sonic Heterogeneity Indices, SHI_tf and SHI_ft, and analyzed the Spectral and Temporal Sonic Signatures along with Spectral Sonic Variability, Effective Number of Frequency Bins, and Sonic Dissimilarity. Each calculation contributed to a detailed description of how the sonosphere is characterized across the frequency spectrum, temporal dynamics, and sound sources. The sonosphere in our study area, primarily characterized by the low-frequency spectra, possessed a mix of biological, geophysical, and anthropogenic sounds displaying distinct temporal patterns (sonophases) that coincided with astronomic divisions of the day (daytime, twilights, and nighttime). Full article

Eco-acoustic indices allow us to rapidly evaluate habitats and ecosystems and derive information about anthropophonic impacts. However, it is proven that indices’ values and trends are not comparable between studies. These incongruences may be caused by the availability on the market of recorders with different characteristics and costs. Thus, there is a need to reduce these biases and incongruences to ensure an accurate analysis and comparison between soundscape ecology studies and habitat assessments. In this study, we propose and validate an audio recording equalization protocol to reduce eco-acoustic indices’ biases, by testing three soundscape recorder models: Song Meter Micro, Soundscape Explorer Terrestrial and Audiomoth. The equalization process aligns the signal amplitude and frequency response of the soundscape recorders to those of a type 1 level meter. The adjustment was made in MATLAB R2023a using a filter curve generated comparing a reference signal (white noise); the measurements were performed in an anechoic chamber using 11 audio sensors and a type 1 sound level meter (able to produce a .WAV file). The statistical validation of the procedure was performed on recordings obtained in an urban and Regional Park (Italy) assessing a significant reduction in indices’ biases on the Song Meter Micro and Audiomoth. Full article

The ongoing biodiversity crisis, driven by factors such as land-use change and global warming, emphasizes the need for effective ecological monitoring methods. Acoustic monitoring of biodiversity has emerged as an important monitoring tool. Detecting human voices in soundscape monitoring projects is useful both for analyzing human disturbance and for privacy filtering. Despite significant strides in deep learning in recent years, the deployment of large neural networks on compact devices poses challenges due to memory and latency constraints. Our approach focuses on leveraging knowledge distillation techniques to design efficient, lightweight student models for speech detection in bioacoustics. In particular, we employed the MobileNetV3-Small-Pi model to create compact yet effective student architectures to compare against the larger EcoVAD teacher model, a well-regarded voice detection architecture in eco-acoustic monitoring. The comparative analysis included examining various configurations of the MobileNetV3-Small-Pi-derived student models to identify optimal performance. Additionally, a thorough evaluation of different distillation techniques was conducted to ascertain the most effective method for model selection. Our findings revealed that the distilled models exhibited comparable performance to the EcoVAD teacher model, indicating a promising approach to overcoming computational barriers for real-time ecological monitoring. Full article

The goal of estimating a soundscape index, aimed at evaluating the contribution of the environmental sound components, is to provide an accurate “acoustic quality” assessment of a complex habitat. Such an index can prove to be a powerful ecological tool associated with both rapid on-site and remote surveys. The soundscape ranking index (SRI), introduced by us recently, can empirically account for the contribution of different sound sources by assigning a positive weight to natural sounds (biophony) and a negative weight to anthropogenic ones. The optimization of such weights was performed by training four machine learning algorithms (decision tree, DT; random forest, RF; adaptive boosting, AdaBoost; support vector machine, SVM) over a relatively small fraction of a labeled sound recording dataset. The sound recordings were taken at 16 sites distributed over an area of approximately 22 hectares at Parco Nord (Northern Park) of the city Milan (Italy). From the audio recordings, we extracted four different spectral features: two based on ecoacoustic indices and the other two based on mel-frequency cepstral coefficients (MFCCs). The labeling was focused on the identification of sounds belonging to biophonies and anthropophonies. This preliminary approach revealed that two classification models, DT and AdaBoost, trained by using 84 extracted features from each recording, are able to provide a set of weights characterized by a rather good classification performance (F1-score = 0.70, 0.71). The present results are in quantitative agreement with a self-consistent estimation of the mean SRI values at each site that was recently obtained by us using a different statistical approach. Full article