Understanding park visitors' soundscape perception using subjective and objective measurement.

Environmental noise knows no boundaries, affecting even protected areas. Noise pollution, originating from both external and internal sources, imposes costs on these areas. It is associated with adverse health effects, while natural sounds contribute to cognitive and emotional improvements as ecosystem services. When it comes to parks, individual visitors hold unique perceptions of soundscapes, which can be shaped by various factors such as their motivations for visiting, personal norms, attitudes towards specific sounds, and expectations. In this study, we utilized linear models and geospatial data to evaluate how visitors' personal norms and attitudes, the park's acoustic environment, visitor counts, and the acoustic environment of visitors' neighborhoods influenced their perception of soundscapes at Muir Woods National Monument. Our findings indicate that visitors' subjective experiences had a greater impact on their perception of the park's soundscape compared to purely acoustic factors like sound level of the park itself. Specifically, we found that motivations to hear natural sounds, interference caused by noise, sensitivity to noise, and the sound levels of visitors' home neighborhoods influenced visitors' perception of the park's soundscape. Understanding how personal factors shape visitors' soundscape perception can assist urban and non-urban park planners in effectively managing visitor experiences and expectations.

Sensory pollutants alter bird phenology and fitness across a continent.

Expansion of anthropogenic noise and night lighting across our planet1,2 is of increasing conservation concern3-6. Despite growing knowledge of physiological and behavioural responses to these stimuli from single-species and local-scale studies, whether these pollutants affect fitness is less clear, as is how and why species vary in their sensitivity to these anthropic stressors. Here we leverage a large citizen science dataset paired with high-resolution noise and light data from across the contiguous United States to assess how these stimuli affect reproductive success in 142 bird species. We find responses to both sensory pollutants linked to the functional traits and habitat affiliations of species. For example, overall nest success was negatively correlated with noise among birds in closed environments. Species-specific changes in reproductive timing and hatching success in response to noise exposure were explained by vocalization frequency, nesting location and diet. Additionally, increased light-gathering ability of species' eyes was associated with stronger advancements in reproductive timing in response to light exposure, potentially creating phenological mismatches7. Unexpectedly, better light-gathering ability was linked to reduced clutch failure and increased overall nest success in response to light exposure, raising important questions about how responses to sensory pollutants counteract or exacerbate responses to other aspects of global change, such as climate warming. These findings demonstrate that anthropogenic noise and light can substantially affect breeding bird phenology and fitness, and underscore the need to consider sensory pollutants alongside traditional dimensions of the environment that typically inform biodiversity conservation.

Association of Outdoor Artificial Light at Night With Mental Disorders and Sleep Patterns Among US Adolescents.

Importance: Indoor nighttime light exposure influences sleep and circadian rhythms and is known to affect mood-associated brain circuits in animals. However, little is known about the association between levels of nighttime outdoor light and sleep and mental health in the population, especially among adolescents. Objective: To estimate associations of outdoor artificial light at night (ALAN) with sleep patterns and past-year mental disorder among US adolescents. Design, Setting, and Participants: This population-based, cross-sectional study of US adolescents used the National Comorbidity Survey-Adolescent Supplement, a nationally representative cross-sectional survey conducted from February 2001 through January 2004. A probability sample of adolescents aged 13 to 18 years was included. Analyses were conducted between February 2019 and April 2020. Exposures: Levels of outdoor ALAN, measured by satellite, with means calculated within census block groups. ALAN values were transformed into units of radiance (nW/cm2/sr). Main Outcomes and Measures: Self-reported habitual sleep patterns (weeknight bedtime, weeknight sleep duration, weekend bedtime delay, and weekend oversleep) and past-year mood, anxiety, behavior, and substance use disorders, measured via an in-person structured diagnostic interview. Parent-reported information was included in behavior disorder diagnoses. Results: Among 10 123 adolescents (4953 boys [51.3%]; mean [SE] age, 15.2 [0.06] years [weighted]; 6483 for behavior disorder outcomes), ALAN was positively associated with indicators of social disadvantage, such as racial/ethnic minority status (median [IQR] ALAN: white adolescents, 12.96 [30.51] nW/cm2/sr; Hispanic adolescents: 38.54 [47.84] nW/cm2/sr; non-Hispanic black adolescents: 37.39 [51.88] nW/cm2/sr; adolescents of other races/ethnicities: 30.94 [49.93] nW/cm2/sr; P < .001) and lower family income (median [IQR] ALAN by family income-to-poverty ratio ≤1.5: 26.76 [52.48] nW/cm2/sr; >6: 21.46 [34.38] nW/cm2/sr; P = .005). After adjustment for several sociodemographic characteristics, as well as area-level population density and socioeconomic status, this study found that higher ALAN levels were associated with later weeknight bedtime, and those in the lowest quartile of ALAN reported the longest weeknight sleep duration. Those in the highest quartile of ALAN went to bed 29 (95% CI, 15-43) minutes later and reported 11 (95% CI, 19-2) fewer minutes of sleep than those in the lowest quartile. ALAN was also positively associated with prevalence of past-year mood and anxiety disorder: each median absolute deviation increase in ALAN was associated with 1.07 (95% CI, 1.00-1.14) times the odds of mood disorder and 1.10 (95% CI, 1.05-1.16) times the odds of anxiety disorder. Further analyses revealed associations with bipolar disorder (odds ratio [OR], 1.19 [95% CI, 1.05-1.35]), specific phobias (OR, 1.18 [95% CI, 1.11-1.26]), and major depressive disorder or dysthymia (OR, 1.07 [95% CI, 1.00-1.15]). Among adolescent girls, differences in weeknight bedtime by ALAN (third and fourth quartiles vs first quartile) were greater with increasing years since menarche (F3, 8.15; P < .001). Conclusions and Relevance: In this study, area-level outdoor ALAN was associated with less favorable sleep patterns and mood and anxiety disorder in adolescents. Future studies should elucidate whether interventions to reduce exposure to ALAN may positively affect mental and sleep health.

Why conservation biology can benefit from sensory ecology.

Global expansion of human activities is associated with the introduction of novel stimuli, such as anthropogenic noise, artificial lights and chemical agents. Progress in documenting the ecological effects of sensory pollutants is weakened by sparse knowledge of the mechanisms underlying these effects. This severely limits our capacity to devise mitigation measures. Here, we integrate knowledge of animal sensory ecology, physiology and life history to articulate three perceptual mechanisms-masking, distracting and misleading-that clearly explain how and why anthropogenic sensory pollutants impact organisms. We then link these three mechanisms to ecological consequences and discuss their implications for conservation. We argue that this framework can reveal the presence of 'sensory danger zones', hotspots of conservation concern where sensory pollutants overlap in space and time with an organism's activity, and foster development of strategic interventions to mitigate the impact of sensory pollutants. Future research that applies this framework will provide critical insight to preserve the natural sensory world.

Environmental noise and sleep and mental health outcomes in a nationally representative sample of urban US adolescents.

BACKGROUND: Environmental noise has been linked to negative health outcomes, like poor sleep, poor mental health, and cardiovascular disease, and likely accounts for more than 1 million disability-adjusted life years annually in Western Europe. Adolescence may be a particularly sensitive period for noise exposure due to an increased need for sleep, failure to meet sleep guidelines, and increased risk for first onset of some mental health disorders. However, the potential health effects of living in high-noise environments have not been studied in US adolescents, rarely in European adolescents, and mental health outcomes studied have not corresponded to diagnoses from the Diagnostic and Statistical Manual of Mental Disorders (DSM). METHODS: Using a US-based nationally representative survey of urban adolescents (N = 4,508), we estimated associations of day-night average sound levels exceeding the US Environmental Protection Agency's 55 decibel limit with sleep outcomes and lifetime mental health DSM diagnoses. We implemented doubly robust targeted minimum loss-based estimation coupled with propensity score matching to account for numerous potential adolescent, household, and environmental confounders. RESULTS: Living in a high- versus low-noise Census block group was associated with later bedtimes on weeknights (0.48 hours, 95% confidence interval [CI] = -0.15, 1.12) and weekend nights (0.65 hours, 95% CI = 0.37, 0.93), but not with total hours slept. Associations between living in a high- versus low-noise Census block group and mental disorders were mixed, with wide CIs, and not robust to sensitivity analyses. CONCLUSIONS: We find evidence for an association between residence in a high-noise area and later bedtimes among urban adolescents but no consistent evidence of such an association with mental health disorders.

Characterization of gain and directivity of exponential horn receivers.

It is difficult and expensive to match the sensitivity of the most sensitive vertebrate ears with off-the-shelf microphones due to the self-noise of the sensor. The extremely small apertures of microelectromechanical microphones create options to use horn waveguides to amplify sound prior to transduction without resulting in an unacceptably narrow directivity. Substantial gain can be achieved at wavelengths larger than the horn. An analytical model of an exponential horn embedded in a rigid spherical housing was formulated to describe the gain relative to a free-field receiver as a function of frequency and angle of arrival. For waves incident on-axis, the analytical model provided an accurate estimate of gain at high frequencies as validated by experimental measurement. Numerical models, using the equivalent source method, can account for higher order modes and comprehensively describe the acoustic scattering within and around the horn for waves arriving from any direction. Results show the directivity of horn receivers were adequately described by the analytical model up to a critical wavelength, and the mechanisms of deviation in gain at high frequencies and large angles of arrival were identified.

Acoustic environments matter: Synergistic benefits to humans and ecological communities.

Protected areas are critical locations worldwide for biodiversity preservation and offer important opportunities for increasingly urbanized humans to experience nature. However, biodiversity preservation and visitor access are often at odds and creative solutions are needed to safeguard protected area natural resources in the face of high visitor use. Managing human impacts to natural soundscapes could serve as a powerful tool for resolving these conflicting objectives. Here, we review emerging research that demonstrates that the acoustic environment is critical to wildlife and that sounds shape the quality of nature-based experiences for humans. Human-made noise is known to affect animal behavior, distributions and reproductive success, and the organization of ecological communities. Additionally, new research suggests that interactions with nature, including natural sounds, confer benefits to human welfare termed psychological ecosystem services. In areas influenced by noise, elevated human-made noise not only limits the variety and abundance of organisms accessible to outdoor recreationists, but also impairs their capacity to perceive the wildlife that remains. Thus soundscape changes can degrade, and potentially limit the benefits derived from experiences with nature via indirect and direct mechanisms. We discuss the effects of noise on wildlife and visitors through the concept of listening area and demonstrate how the perceptual worlds of both birds and humans are reduced by noise. Finally, we discuss how management of soundscapes in protected areas may be an innovative solution to safeguarding both and recommend several key questions and research directions to stimulate new research.

Race/Ethnicity, Socioeconomic Status, Residential Segregation, and Spatial Variation in Noise Exposure in the Contiguous United States.

BACKGROUND: Prior research has reported disparities in environmental exposures in the United States, but, to our knowledge, no nationwide studies have assessed inequality in noise pollution. OBJECTIVES: We aimed to a) assess racial/ethnic and socioeconomic inequalities in noise pollution in the contiguous United States; and b) consider the modifying role of metropolitan level racial residential segregation. METHODS: We used a geospatial sound model to estimate census block group­level median (L50) nighttime and daytime noise exposure and 90th percentile (L10) daytime noise exposure. Block group variables from the 2006­2010 American Community Survey (ACS) included race/ethnicity, education, income, poverty, unemployment, homeownership, and linguistic isolation. We estimated associations using polynomial terms in spatial error models adjusted for total population and population density. We also evaluated the relationship between race/ethnicity and noise, stratified by levels of metropolitan area racial residential segregation, classified using a multigroup dissimilarity index. RESULTS: Generally, estimated nighttime and daytime noise levels were higher for census block groups with higher proportions of nonwhite and lower-socioeconomic status (SES) residents. For example, estimated nighttime noise levels in urban block groups with 75% vs. 0% black residents were 46.3 A-weighted decibels (dBA) [interquartile range (IQR): 44.3­47.8 dBA] and 42.3 dBA (IQR: 40.4­45.5 dBA), respectively. In urban block groups with 50% vs. 0% of residents living below poverty, estimated nighttime noise levels were 46.9 dBA (IQR: 44.7­48.5 dBA) and 44.0 dBA (IQR: 42.2­45.5 dBA), respectively. Block groups with the highest metropolitan area segregation had the highest estimated noise exposures, regardless of racial composition. Results were generally consistent between urban and suburban/rural census block groups, and for daytime and nighttime noise and robust to different spatial weight and neighbor definitions. CONCLUSIONS: We found evidence of racial/ethnic and socioeconomic differences in model-based estimates of noise exposure throughout the United States. Additional research is needed to determine if differences in noise exposure may contribute to health disparities in the United States. https://doi.org/10.1289/EHP898

Noise pollution is pervasive in U.S. protected areas.

Anthropogenic noise threatens ecological systems, including the cultural and biodiversity resources in protected areas. Using continental-scale sound models, we found that anthropogenic noise doubled background sound levels in 63% of U.S. protected area units and caused a 10-fold or greater increase in 21%, surpassing levels known to interfere with human visitor experience and disrupt wildlife behavior, fitness, and community composition. Elevated noise was also found in critical habitats of endangered species, with 14% experiencing a 10-fold increase in sound levels. However, protected areas with more stringent regulations had less anthropogenic noise. Our analysis indicates that noise pollution in protected areas is closely linked with transportation, development, and extractive land use, providing insight into where mitigation efforts can be most effective.

A geospatial model of ambient sound pressure levels in the contiguous United States.

This paper presents a model that predicts measured sound pressure levels using geospatial features such as topography, climate, hydrology, and anthropogenic activity. The model utilizes random forest, a tree-based machine learning algorithm, which does not incorporate a priori knowledge of source characteristics or propagation mechanics. The response data encompasses 270 000 h of acoustical measurements from 190 sites located in National Parks across the contiguous United States. The explanatory variables were derived from national geospatial data layers and cross validation procedures were used to evaluate model performance and identify variables with predictive power. Using the model, the effects of individual explanatory variables on sound pressure level were isolated and quantified to reveal systematic trends across environmental gradients. Model performance varies by the acoustical metric of interest; the seasonal L50 can be predicted with a median absolute deviation of approximately 3 dB. The primary application for this model is to generalize point measurements to maps expressing spatial variation in ambient sound levels. An example of this mapping capability is presented for Zion National Park and Cedar Breaks National Monument in southwestern Utah.

Multiple-array passive acoustic source localization in urban environments.

In many situations of interest, obstacles to acoustic wave propagation such as terrain or buildings exist that provide unique challenges to localization. These obstacles introduce multiple propagation paths, reflections, and diffraction into the propagation. In this paper, matched field processing is proposed as an effective method of acoustic localization in a two dimensional scattering environment. Numerical techniques can be used to model complex propagation in a space where analytical solutions are not feasible. Realistically, there is always some uncertainty in model parameters that in turn can adversely affect localization ability. In particular, uncertainty in array location, sound speed, and various parameters affecting inter-array coherence only are investigated. A spatially distributed, multiarray network is shown to mitigate the effects of uncertainty. Multiarray inverse filter processing techniques are evaluated through perturbation of uncertain model parameters. These techniques are more accurate and flexible to implement than other matched field processing methods such as time reversal.