High acoustic diversity and behavioral complexity of katydids in the Mesozoic soundscape.

Acoustic communication has played a key role in the evolution of a wide variety of vertebrates and insects. However, the reconstruction of ancient acoustic signals is challenging due to the extreme rarity of fossilized organs. Here, we report the earliest tympanal ears and sound-producing system (stridulatory apparatus) found in exceptionally preserved Mesozoic katydids. We present a database of the stridulatory apparatus and wing morphology of Mesozoic katydids and further calculate their probable singing frequencies and analyze the evolution of their acoustic communication. Our suite of analyses demonstrates that katydids evolved complex acoustic communication including mating signals, intermale communication, and directional hearing, at least by the Middle Jurassic. Additionally, katydids evolved a high diversity of singing frequencies including high-frequency musical calls, accompanied by acoustic niche partitioning at least by the Late Triassic, suggesting that acoustic communication might have been an important driver in the early radiation of these insects. The Early-Middle Jurassic katydid transition from Haglidae- to Prophalangopsidae-dominated faunas coincided with the diversification of derived mammalian clades and improvement of hearing in early mammals, supporting the hypothesis of the acoustic coevolution of mammals and katydids. Our findings not only highlight the ecological significance of insects in the Mesozoic soundscape but also contribute to our understanding of how acoustic communication has influenced animal evolution.

Divergent ecological responses to typhoon disturbance revealed via landscape-scale acoustic monitoring.

Climate change is increasing the frequency, intensity, and duration of extreme weather events across the globe. Understanding the capacity for ecological communities to withstand and recover from such events is critical. Typhoons are extreme weather events that are expected to broadly homogenize ecological dynamics through structural damage to vegetation and longer-term effects of salinization. Given their unpredictable nature, monitoring ecological responses to typhoons is challenging, particularly for mobile animals such as birds. Here, we report spatially variable ecological responses to typhoons across terrestrial landscapes. Using a high temporal resolution passive acoustic monitoring network across 24 sites on the subtropical island of Okinawa, Japan, we found that typhoons elicit divergent ecological responses among Okinawa's diverse terrestrial habitats, as indicated by increased spatial variability of biological sound production (biophony) and individual species detections. This suggests that soniferous communities are capable of a diversity of different responses to typhoons. That is, spatial insurance effects among local ecological communities provide resilience to typhoons at the landscape scale. Even though site-level typhoon impacts on soundscapes and bird detections were not particularly strong, monitoring at scale with high temporal resolution across a broad spatial extent nevertheless enabled detection of spatial heterogeneity in typhoon responses. Further, species-level responses mirrored those of acoustic indices, underscoring the utility of such indices for revealing insight into fundamental questions concerning disturbance and stability. Our findings demonstrate the significant potential of landscape-scale acoustic sensor networks to capture the understudied ecological impacts of unpredictable extreme weather events.

Complex and highly saturated soundscapes in restored oak woodlands reflect avian richness and abundance.

Temperate woodlands are biodiverse natural communities threatened by land use change and fire suppression. Excluding historic disturbance regimes of periodic groundfires from woodlands causes degradation, resulting from changes in the plant community and subsequent biodiversity loss. Restoration, through prescribed fire and tree thinning, can reverse biodiversity losses, however, because the diversity of woodland species spans many taxa, efficiently quantifying biodiversity can be challenging. We assessed whether soundscapes in an eastern North American woodland reflect biodiversity changes during restoration measured in a concurrent multitrophic field study. In five restored and five degraded woodland sites in Wisconsin, USA, we sampled vegetation, measured arthropod biomass, conducted bird surveys, and recorded soundscapes for five days of every 15-day period from May to August 2022. We calculated two complementary acoustic indices: Soundscape Saturation, which focuses on all acoustically active species, and Acoustic Complexity Index (ACI), which was developed to study vocalizing birds. We used generalized additive models to predict both indices based on Julian date, time of day, and level of habitat degradation. We found that restored woodlands had higher arthropod biomass, and higher richness and abundance of breeding birds. Additionally, soundscapes in restored sites had higher mean Soundscape Saturation and higher mean ACI. Restored woodland acoustic indices exhibited greater magnitudes of daily and seasonal peaks. We conclude that woodland restoration results in higher soundscape saturation and complexity, due to greater richness and abundance of vocalizing animals. This bioacoustic signature of restoration offers a promising monitoring tool for efficiently documenting differences in woodland biodiversity.

Exploring potential relationships between acoustic indices and ecosystem functions: a test on insect herbivory.

Biodiversity loss is a global concern. Current technological advances allow the development of novel tools that can monitor biodiversity remotely with minimal disturbance. One example is passive acoustic monitoring (PAM), which involves recording the soundscape of an area using autonomous recording units, and processing these data using acoustic indices, for example, to estimate the diversity of various vocal animal groups. We explored the hypothesis that data obtained through PAM could also be used to study ecosystem functions. Specifically, we investigated the potential relationship between seven commonly used acoustic indices and insect leaf herbivory, measured as total leaf damage and as the damage from three major insect feeding guilds. Herbivory was quantified on seedlings in 13 plots in four subtropical forests in south China, and acoustic data, representing insect acoustic complexity, were obtained by recording the evening soundscapes in those same locations. Herbivory levels correlated positively with the acoustic entropy index, commonly reported as one of the best-performing indices, whose high values indicate higher acoustic complexity, likely due to greater insect diversity. Relationships for specific feeding guilds were moderately stronger for chewers, indicating that the acoustic indices capture some insect groups more than others (e.g., chewers include soniferous taxa such as crickets, whereas miners are mostly silent). Our findings suggest that the use of PAM to monitor ecosystem functions deserves to be explored further, as this is a research field with unexplored potential. Well-designed targeted studies could help us better understand how to best use novel technologies to monitor ecosystem functions.

Impact of exposure to natural versus urban soundscapes on brain functional connectivity, BOLD entropy and behavior.

BACKGROUND: Humans have been moving from rural to urban environments for decades. This process may have important consequences for our health and well-being. Most previous studies have focused on visual input, and the auditory domain has been understudied so far. Therefore, we set out to investigate the influence of exposure to natural vs urban soundscapes on brain activity and behavior. METHODS: Resting-state fMRI data was acquired while participants (N = 35) listened to natural and urban soundscapes. Two affective questionnaires (the Positive and Negative Affect Schedule (PANAS) and the Perceived Stress Scale) and two cognitive tasks (dual n-back (DNB) and the backward digit-span (BDS)) were assessed before and after each soundscape condition. To quantify brain function we used complexity and network measures, namely brain entropy (BEN) and whole brain functional connectivity (FC). To study the link between brain and behavior, changes in BEN and whole brain FC were correlated to changes in cognitive performance and self-reported affect. RESULTS: We found higher BEN when listening to urban sounds in posterior cingulate gyrus, cuneus and precuneus, occipital lobe/calcarine as compared to nature sounds, which was negatively correlated to (post-pre) differences in positive affect (PANAS) in the urban soundscape condition. In addition, we found higher FC between areas in the auditory, cinguloopercular, somatomotor hand and mouth networks when listening to nature as compared to urban sounds which was positively correlated to (post-pre) differences of the of the composite score of Digit span and N-back for nature soundscape. CONCLUSIONS: This study provides a framework for the neural underpinnings of how natural versus urban soundscapes affect both whole brain FC and BEN and bear implications for the understanding of how the physical auditory environment affects brain function and subsequently observed behavior. Moreover, correlations with cognition and affect reveal the meaning that exposure to soundscapes may have on the human brain. To the best of our knowledge this is the first study to analyze BEN and whole brain FC at rest during exposure to nature and urban soundscapes and to explore their relationship to behavior.

Pied tamarins change their vocal behavior in response to noise levels in the largest city in the Amazon.

Many animal species depend on sound to communicate with conspecifics. However, human-generated (anthropogenic) noise may mask acoustic signals and so disrupt behavior. Animals may use various strategies to circumvent this, including shifts in the timing of vocal activity and changes to the acoustic parameters of their calls. We tested whether pied tamarins (Saguinus bicolor) adjust their vocal behavior in response to city noise. We predicted that both the probability of occurrence and the number of long calls would increase in response to anthropogenic noise and that pied tamarins would temporally shift their vocal activity to avoid noisier periods. At a finer scale, we anticipated that the temporal parameters of tamarin calls (e.g., call duration and syllable repetition rate) would increase with noise amplitude. We collected information on the acoustic environment and the emission of long calls in nine wild pied tamarin groups in Manaus, Brazil. We found that the probability of long-call occurrence increased with higher levels of anthropogenic noise, though the number of long calls did not. The number of long calls was related to the time of day and the distance from home range borders-a proxy for the distance to neighboring groups. Neither long-call occurrence nor call rate was related to noise levels at different times of day. We found that pied tamarins decreased their syllable repetition rate in response to anthropogenic noise. Long calls are important for group cohesion and intergroup communication. Thus, it is possible that the tamarins emit one long call with lower syllable repetition, which might facilitate signal reception. The occurrence and quantity of pied tamarin' long calls, as well as their acoustic proprieties, seem to be governed by anthropogenic noise, time of the day, and social mechanisms such as proximity to neighboring groups.

Biases in Ecoacoustics Analysis: A Protocol to Equalize Audio Recorders.

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.

Sons al Balcó: A Comparative Analysis of WASN-Based LAeq Measured Values with Perceptual Questionnaires in Barcelona during the COVID-19 Lockdown.

The mobility and activity restrictions imposed in Spain due to the COVID-19 pandemic caused a significant improvement in the urban noise pollution that could be objectively measured in those cities with acoustic sensor networks deployed. This significant change in the urban soundscapes was also perceived by citizens who positively appraised this new acoustic scenario. In this work, authors present a comparative analysis between different noise indices provided by 70 sound sensors deployed in Barcelona, both during and before the lockdown, and the results of a perceptual test conducted in the framework of the project Sons al Balcó during the lockdown, which received more than one hundred contributions in Barcelona alone. The analysis has been performed by clustering the objective and subjective data according to the predominant noise sources in the location of the sensors and differentiating road traffic in heavy, moderate and low-traffic areas. The study brings out strong alignments between a decline in noise indices, acoustic satisfaction improvement and changes in the predominant noise sources, supporting the idea that objective calibrated data can be useful to make a qualitative approximation to the subjective perception of urban soundscapes when further information is not available.

Acoustic Comfort Prediction: Integrating Sound Event Detection and Noise Levels from a Wireless Acoustic Sensor Network.

There is an increasing interest in accurately evaluating urban soundscapes to reflect citizens' subjective perceptions of acoustic comfort. Various indices have been proposed in the literature to achieve this purpose. However, many of these methods necessitate specialized equipment or extensive data collection. This study introduces an enhanced predictor for dwelling acoustic comfort, utilizing cost-effective data consisting of a 30-s audio clip and location information. The proposed predictor incorporates two rating systems: a binary evaluation and an acoustic comfort index called ACI. The training and evaluation data are obtained from the "Sons al Balcó" citizen science project. To characterize the sound events, gammatone cepstral coefficients are used for automatic sound event detection with a convolutional neural network. To enhance the predictor's performance, this study proposes incorporating objective noise levels from public IoT-based wireless acoustic sensor networks, particularly in densely populated areas like Barcelona. The results indicate that adding noise levels from a public network successfully enhances the accuracy of the acoustic comfort prediction for both rating systems, reaching up to 85% accuracy.

Soundscape Characterization Using Autoencoders and Unsupervised Learning.

Passive acoustic monitoring (PAM) through acoustic recorder units (ARUs) shows promise in detecting early landscape changes linked to functional and structural patterns, including species richness, acoustic diversity, community interactions, and human-induced threats. However, current approaches primarily rely on supervised methods, which require prior knowledge of collected datasets. This reliance poses challenges due to the large volumes of ARU data. In this work, we propose a non-supervised framework using autoencoders to extract soundscape features. We applied this framework to a dataset from Colombian landscapes captured by 31 audiomoth recorders. Our method generates clusters based on autoencoder features and represents cluster information with prototype spectrograms using centroid features and the decoder part of the neural network. Our analysis provides valuable insights into the distribution and temporal patterns of various sound compositions within the study area. By utilizing autoencoders, we identify significant soundscape patterns characterized by recurring and intense sound types across multiple frequency ranges. This comprehensive understanding of the study area's soundscape allows us to pinpoint crucial sound sources and gain deeper insights into its acoustic environment. Our results encourage further exploration of unsupervised algorithms in soundscape analysis as a promising alternative path for understanding and monitoring environmental changes.

Mapping and assessing natural soundscape quality: An indicator-based model for landscape planning.

Natural soundscape quality (NSQ) has been recognized as an essential cultural ecosystem service that contributes significantly to human health and well-being. It also stands as an indispensable component of environmental quality, especially for landscape aesthetic quality. However, an assessment tool for NSQ in landscape planning and environmental impact assessments is still absent. Therefore, this paper aims to address this gap by proposing an indicator-based model for assessing and quantifying NSQ in the Geographic Information System. The model characterizes NSQ based on Calmness and Vibrancy, and employs several indicators, sub-indicators, and respective metrics as proxies to quantify and map them spatially. The evaluation criteria of the model correspond to the general public's preferences for soundscape features. The case study results in Springe municipality, Germany, show that the relative values of NSQ are high in green spaces, including forests, grasslands, and shrublands, whereas they are low in open farmlands. The multiple natural sounds yield higher NSQ scores than the individual ones. The same soundscape compositions in forests and in urban parks exhibit higher NSQ scores than in other land cover types. In addition, the shares of relative values show similar distribution patterns among Calmness, Vibrancy, and NSQ according to land cover types and soundscape compositions. The evaluation results align with public values and preferences for soundscape features. Unlike subjectivist approaches, our user-independent methodology is easily transferable and reproducible. The results are comparable and communicable among the assessed areas. These endow the indicator-based model with the potential to be applied at various planning and management scales. The findings can help to incorporate soundscape evaluation into landscape planning and management systems, supporting sustainable landscape development, and providing valuable information for policy-, plan- and decision-making.

Integrating spatial-temporal soundscape mapping with landscape indicators for effective conservation management and planning of a protected area.

Protected areas (PAs) possess generous biodiversity, making them great potential for human and wildlife well-being. Nevertheless, rising anthropogenic sounds may pose a serious challenge and threat to the habitats. Therefore, understanding the acoustic environments of PAs and implementing proper conservation strategies are essential for maintaining species richness within the territory. In this study, we investigate the spatial-temporal variations of soundscape distribution in the Dashanbao Protected Area (DPA) of China, ultimately discussing the planning and management strategies. Firstly, to systematically analyse the spatial-temporal soundscape distribution of the reserve, we generated single and multi-acoustic source maps by classifying geographical, biological, and anthropogenic sounds. In the region, we installed 35 recording points and collected sounds using the synchronic recording method. Secondly, we conducted Spearman correlation analyses to examine the relationships between the sound sources and i) temporal variations, ii) landscape feature indicators. Thirdly, we identified the dominant sound sources in the region and their conflict areas through the cross-analysis module of Grass Geographic Information Systems (GIS). Finally, we provided sound control strategies by discussing landscape indicators and land-use management policies. The results show that even though there is conservation planning in the DPA, anthropogenic sounds dominate in certain parts of the reserve depending on diurnal and seasonal cycles. This reveals deficiencies in the DPA's current planning concerning the soundscape and highlights the effectiveness of spatial-temporal mapping. Additionally, our correlation analyses demonstrate that landscape feature indicators can represent how sound environment is affected by landscape. The patch diversity (PD), landscape shape index (LSI), Shannon's Diversity Index (SHDI), woodland, shrubland, and water distance (WD) were identified as the primary predictors for both biological and anthropogenic sounds. None of the indicators exhibited a significant positive or negative correlation with geological sounds. Consequently, to enhance and conserve the acoustic quality of the region, spatial-temporal mapping with landscape indicators can be employed in the management and planning processes.

Understanding vessel noise across a network of marine protected areas.

Protected areas are typically managed as a network of sites exposed to varying anthropogenic conditions. Managing these networks benefits from monitoring of conditions across sites to help prioritize coordinated efforts. Monitoring marine vessel activity and related underwater radiated noise impacts across a network of protected areas, like the U.S. National Marine Sanctuary system, helps managers ensure the quality of habitats used by a wide range of marine species. Here, we use underwater acoustic detections of vessels to quantify different characteristics of vessel noise at 25 locations within eight marine sanctuaries including the Hawaiian Archipelago and the U.S. east and west coasts. Vessel noise metrics, including temporal presence and sound levels, were paired with Automatic Identification System (AIS) vessel tracking data to derive a suite of robust vessel noise indicators for use across the network of marine protected areas. Network-wide comparisons revealed a spectrum of vessel noise conditions that closely matched AIS vessel traffic composition. Shifts in vessel noise were correlated with the decrease in vessel activity early in the COVID-19 pandemic, and vessel speed reduction management initiatives. Improving our understanding of vessel noise conditions in these protected areas can help direct opportunities for reducing vessel noise, such as establishing and maintaining noise-free periods, enhancing port efficiency, engaging with regional and international vessel quieting initiatives, and leveraging co-benefits of management actions for reducing ocean noise.

Reductions in community noise levels in vancouver, Canada, during pandemic lockdown and association with land cover type.

BACKGROUND: Urban transportation noise is a major public concern because of its adverse effects on health. The determinants of urban noise exposure have not been widely explored but the "natural experiment" presented by the COVID-19 lockdowns presented a unique opportunity. This study examined the relationship between environmental characteristics and urban noise pollution during the COVID-19 related lockdown in Metro Vancouver, Canada, from March 21st to May 18th, 2020. METHODS: We used noise exposure data from the Vancouver International Airport (YVR) noise management program, comparing the noise levels during "Phase One" of the COVID-19 lockdown in 2020 to the corresponding time period in 2019 from 21 Noise Monitoring Terminals (NMTs) located throughout Metro Vancouver. We modelled the relationship between the change in noise level and the physical NMT environments, including land cover, and total length of roads at four different time periods (24Hr, daytime, evening and nighttime) and within three different buffer zones (100 m, 250 m, and 500 m). RESULTS: Of 59,472 hourly measurements of community noise, the 24-h noise level was reduced by an average of 2.20 dBA between 2019 and 2020. Higher proportions of greenspace, barren areas, and soil-cover around NMTs resulted in stronger noise reductions and higher density of building, pavement, and water weakened the amount of noise reduction. Proximity of high-volume traffic roads (highways) were associated with weaker noise reduction. CONCLUSION: The COVID-19 related lockdown was associated with reduced noise in Metro Vancouver, and the relative reduction depended on the types of the environment surrounding the NMT. Future research on the effects of urban environmental characteristics on geographic inequality in noise levels and health consequences of the COVID-19 related lockdown is merited.

Characterizing soundscapes across diverse ecosystems using a universal acoustic feature set.

Natural habitats are being impacted by human pressures at an alarming rate. Monitoring these ecosystem-level changes often requires labor-intensive surveys that are unable to detect rapid or unanticipated environmental changes. Here we have developed a generalizable, data-driven solution to this challenge using eco-acoustic data. We exploited a convolutional neural network to embed soundscapes from a variety of ecosystems into a common acoustic space. In both supervised and unsupervised modes, this allowed us to accurately quantify variation in habitat quality across space and in biodiversity through time. On the scale of seconds, we learned a typical soundscape model that allowed automatic identification of anomalous sounds in playback experiments, providing a potential route for real-time automated detection of irregular environmental behavior including illegal logging and hunting. Our highly generalizable approach, and the common set of features, will enable scientists to unlock previously hidden insights from acoustic data and offers promise as a backbone technology for global collaborative autonomous ecosystem monitoring efforts.

Sensorineural hearing loss alters auditory discrimination of natural soundscapes.

OBJECTIVE: The ability to discriminate natural soundscapes recorded in a temperate terrestrial biome was measured in 15 hearing-impaired (HI) listeners with bilateral, mild to severe sensorineural hearing loss and 15 normal-hearing (NH) controls. DESIGN: Soundscape discrimination was measured using a three-interval oddity paradigm and the method of constant stimuli. On each trial, sequences of 2-second recordings varying the habitat, season and period of the day were presented diotically at a nominal SPL of 60 or 80 dB. RESULTS: Discrimination scores were above chance level for both groups, but they were poorer for HI than NH listeners. On average, the scores of HI listeners were relatively well accounted for by those of NH listeners tested with stimuli spectrally-shaped to match the frequency-dependent reduction in audibility of individual HI listeners. However, the scores of HI listeners were not significantly correlated with pure-tone audiometric thresholds and age. CONCLUSIONS: These results indicate that the ability to discriminate natural soundscapes associated with changes in habitat, season and period of the day is disrupted but it is not abolished. The deficits of the HI listeners are partly accounted for by reduced audibility. Supra-threshold auditory deficits and individual listening strategies may also explain differences between NH and HI listeners.

Self-Consistent Soundscape Ranking Index: The Case of an Urban Park.

We have performed a detailed analysis of the soundscape inside an urban park (located in the city of Milan) based on simultaneous sound recordings at 16 locations within the park. The sound sensors were deployed over a regular grid covering an area of about 22 hectares, surrounded by a variety of anthropophonic sources. The recordings span 3.5 h each over a period of four consecutive days. We aimed at determining a soundscape ranking index (SRI) evaluated at each site in the grid by introducing 4 unknown parameters. To this end, a careful aural survey from a single day was performed in order to identify the presence of 19 predefined sound categories within a minute, every 3 minutes of recording. It is found that all SRI values fluctuate considerably within the 70 time intervals considered. The corresponding histograms were used to define a dissimilarity function for each pair of sites. Dissimilarity was found to increase significantly with the inter-site distance in space. Optimal values of the 4 parameters were obtained by minimizing the standard deviation of the data, consistent with a fifth parameter describing the variation of dissimilarity with distance. As a result, we classify the sites into three main categories: "poor", "medium" and "good" environmental sound quality. This study can be useful to assess the quality of a soundscape in general situations.

Toward the Definition of a Soundscape Ranking Index (SRI) in an Urban Park Using Machine Learning Techniques.

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.

Statistical study on shallow water soundscape variability of Eastern Arabian Sea using noise level metrics.

Underwater soundscape that spans a broad frequency band shows variability consistent with contributing noise sources and ocean environment. However, increased anthropogenic activities result in noise proliferation which can harm natural marine habitat. Continuous monitoring of background sound is useful to assess such spatio-temporal variability of soundscape. Standard noise level metrics, for instance, mean (µ), 90th percentiles (90P), standard deviation (σ), and kurtosis (ß), are constructed from noise field measured from three coastal stations in Eastern Arabian Sea. These metrics are found to be suitable to describe the soundscape variability with respect to season, frequency, and depth. Mean and 90P are used to compare the seasonal variations while kurtosis metrics are exercised to check the impulsive nature of composite signal. Histogram representation and probability density function (PDF) were utilized to analyze the spectral variation in soundscape with respect to season. Analysis was carried out at 500-ms temporal window in two spectral bands corresponding to traffic and wind noise fields. Seasonal analysis shows that in summer, mean noise level decreases as hydrophone depth increases, while in winter, deeper depths have higher mean value with the presence of seasonal surface duct. This implication of sound speed profile on noise field has also been confirmed using appropriate noise model.

"Listening Between the Lines": Soundscapes in Yusef Komunyakaa's Poetry.

Yusef Komunyakaa's poetry is widely acclaimed for its sui generis soundscapes, which shows the poet's highly sensitive auditory perception in his literary creations. Soundscapes, in his poetry, play a pivotal role in revealing social malaise-racial inequalities and gender-biased black relations-in the multiracial US. This article thus explores race- and gender-related societal problems mirrored in Komunyakaa's poetry through the prism of soundscapes. It first aims to examine how soundscapes are presented between poetic lines as a culture carrier, and then investigates the disciplinary power and oppositional function of soundscapes. Combining textual close reading with interdisciplinary research methodology, this article brings to light the complexity and specificity of soundscapes in Komunyakaa's poetry. For one thing, the soundscape constructed by the privileged serves as an oppressive force to discipline the disempowered groups; for another, the soundscape the underprivileged produce is utilized as an instrument of resistance and healing, offering them a sonic weapon to deconstruct the oppressive sound imperialism as well as construct the affective community of African Americans. This study not only adds to the research on Komunyakaa's poetry by offering a renewed viewpoint of excavating this poet and his political proposition of equality and equity, but also attracts academic attention to the role of literary soundscape in Afro-American literature in revealing the long-standing societal problems in the US.