DOI: 10.5061/dryad.s4mw6m998
title: Inequalities in noise will affect urban wildlife

description: Understanding the extent to which systemic biases influence local
 ecological communities is essential for developing just and equitable
 environmental practices. With over 270 million people across the United
 States living in urban areas, understanding the socio-ecological
 consequences of racially-targeted zoning, such as redlining, provides
 crucial information for urban planning. There is a growing body of
 literature documenting the relationships between redlining and disparities
 in the distribution of environmental harms and goods, including inequities
 in green space cover and pollutant exposure. Yet, it remains unknown
 whether noise pollution is also inequitably distributed, and whether
 inequitable noise is an important driver of ecological change in urban
 environments. We conducted 1) a spatial analysis of urban noise to
 determine the extent to which noise overlaps with the distribution of
 redlining categories and 2) a systematic literature review to summarize
 the effects of noise on wildlife in urban landscapes. We found strong
 evidence that noise is inequitably distributed in cities across the United
 States, and that inequitable noise may drive complex biological responses
 across diverse urban wildlife. These findings lay a foundation for future
 research that advances acoustic and urban ecology by centering equity and
 challenging systems of oppression.
description: Spatial Analysis of Urban Noise Pollution To
 evaluate noise exposure across HOLC redlining grades for 83 U.S. cities in
 our study, we acquired spatial data on the distribution of HOLC grades
 across U.S. cities from the Mapping Inequality Project. We also acquired
 data on road, rail, and aircraft noise (hereafter transportation noise
 models), from the U.S. Department of Transportation, National
 Transportation Noise Map 2018. The transportation noise models represent
 potential exposure to transportation noise reported on a decibel scale in
 a 30m x 30m pixel resolution. Here noise represents the average noise
 energy produced by road, rail, and aviation networks over a 24-hour
 period, measured in A-weighted decibels (dBA) (LAeq, 24h) at sampling
 locations deployed across a uniform grid in each city at an elevation of
 1.5 m above ground level. Noise levels below 35 dBA are assumed to have
 minimal negative impacts to humans and the environment and thus are
 represented with null values in the transportation noise
 models.  For each HOLC grade and each city, we used
 zonal statistics in ArcGIS Desktop v. 10.7 to calculate descriptive
 statistics (median, minimum, maximum, area) for the 30m x 30m pixels in
 the transportation noise models with non-null noise values (i.e., values
 &gt; 35 dBA). We used the resulting zonal statistics estimates to
 calculate an area-corrected measure of excess noise: N = (r * Md)/a
 where N is excess noise in each HOLC grade (with units of dBA/900
 m<sup>2</sup>); r is the area covered by the 30m x 30m pixels
 with noise values &gt;35 dBA across all polygons of the same HOLC
 grade in each city; Md is the median transportation noise value (in dBA)
 for those same pixels; and a is the total area of all polygons of the same
 HOLC grade in each city.  Literature Review
 Methodology To assess the effects of noise on wildlife
 in urban environments, we conducted a literature review using Thompson’s
 ISI Web of Science and adapting the methods of Shannon et al. (2016). We
 adjusted Shannon et al. (2016) search criteria to include urban phrases,
 resulting in the following search terms (TS=(WILDLIFE OR ANIMAL OR MAMMAL
 OR REPTILE OR AMPHIBIAN OR BIRD OR FISH OR INVERTEBRATE) AND TS=(NOISE OR
 SONAR) AND TS=(CITY OR *URBAN OR METROPOLITAN)). We only selected papers
 published between 1990 and 23 June 2021 (i.e., the date we conducted our
 search) within the ISI Web of Science categories of ‘Acoustics’,
 ‘Zoology’, ‘Ecology’, ‘Environmental Sciences’, ‘Ornithology’,
 ‘Biodiversity Conservation’, ‘Evolutionary Biology’, and ‘Marine
 Freshwater Biology’. This returned 691 peer-reviewed papers, which we
 filtered so only empirical studies focused on documenting the effects of
 anthropogenic noise on wildlife in urban or suburban ecosystems or the
 effects of urban noise on wildlife in rural environments were included in
 the final data set. We excluded reviews, meta-analyses, methods papers,
 and research that took place outside of urban or suburban areas where the
 noise was not explicitly denoted as urban (e.g., omitted studies that
 measured traffic noise by parks and reserves in rural areas). 
 For the 241 articles previously analyzed in Shannon et al.
 (2016), one of our authors reviewed each paper to determine which studies
 were focused on urban noise. We also verified the noise levels that caused
 a significant biological response, noting each noise level if multiple
 responses were recorded. For any new articles published since the Shannon
 et al. (2016) dataset or those published between 1990 and 2013 but not
 reviewed by Shannon et al. (2016) (n = 96), two of our authors reviewed
 each paper to first determine which studies met our criteria and then
 compiled data on a number of variables of interest, including the noise
 levels and their resulting biological responses that were statistically
 significant. For this subset of papers, one author was randomly assigned a
 list of papers and then a second author was randomly assigned to assess
 the accuracy of the data collected by the first author. Any discrepancies
 were discussed as a group until an agreement was reached. 
 Noise categories (environmental, transportation, industrial,
 multiple, other) were chosen for each paper by noting the explicitly
 stated source or description of urban noise described in the methodology.
 Noise levels and their units were reported for each paper, with only noise
 levels reported in decibels (dB) being used in data analysis. We recorded
 the sound metric used (i.e., SPL, SPL Max, Leq) for each paper and also
 recorded the weightings for each noise level.
description: Data can be viewed using any software that can open a .csv file.
 Code can be viewed using any software that can open a .txt file.
description: # Inequalities in noise will affect urban wildlife
 [https://doi.org/10.5061/dryad.s4mw6m998](https://doi.org/10.5061/dryad.s4mw6m998) Part I: Spatial Analysis of Noise Distribution across 83 U.S. cities File name: HOLC\_Noise\_City\_Results.csv Date completed: 15 December 2021 Spatial dataset: U.S. Department of Transportation, National Transportation Noise Map 2018 Software used in analysis: ArcGIS Desktop v. 10.7 Part II: Literature review of papers published between 1990 and 23 June 2021 that focus on the impacts of noise pollution to urban wildlife. File name: Urban\_noise\_wildlife\_literature\_review.csv Date compiled: 23 June 2021 Search engine: Thompson’s ISI Web of Science Search terms (TS=(WILDLIFE OR ANIMAL OR MAMMAL OR REPTILE OR AMPHIBIAN OR BIRD OR FISH OR INVERTEBRATE) AND TS=(NOISE OR SONAR) AND TS=(CITY OR \*URBAN OR METROPOLITAN)). Data collection procedure: To assess the effects of noise on wildlife in urban environments, we conducted a literature review using Thompson’s ISI Web of Science and adapting the methods of Shannon et al. (2016). We adjusted Shannon et al. (2016) search criteria to include urban phrases, resulting in the following search terms (TS=(WILDLIFE OR ANIMAL OR MAMMAL OR REPTILE OR AMPHIBIAN OR BIRD OR FISH OR INVERTEBRATE) AND TS=(NOISE OR SONAR) AND TS=(CITY OR \*URBAN OR METROPOLITAN)). We only selected papers published between 1990 and 23 June 2021 (i.e., the date we conducted our search) within the ISI Web of Science categories of ‘Acoustics’, ‘Zoology’, ‘Ecology’, ‘Environmental Sciences’, ‘Ornithology’, ‘Biodiversity Conservation’, ‘Evolutionary Biology’, and ‘Marine Freshwater Biology’. This returned 691 peer-reviewed papers, which we filtered so only empirical studies focused on documenting the effects of anthropogenic noise on wildlife in urban or suburban ecosystems or the effects of urban noise on wildlife in rural environments were included in the final data set. We excluded reviews, meta-analyses, methods papers, and research that took place outside of urban or suburban areas where the noise was not explicitly denoted as urban (e.g., omitted studies that measured traffic noise by parks and reserves in rural areas). For the 241 articles previously analyzed in Shannon et al. (2016), one of our authors reviewed each paper to determine which studies were focused on urban noise. We also verified the noise levels that caused a significant biological response, noting each noise level if multiple responses were recorded. For any new articles published since the Shannon et al. (2016) dataset or those published between 1990 and 2013 but not reviewed by Shannon et al. (2016) (n = 96), two of our authors reviewed each paper to first determine which studies met our criteria and then compiled data on a number of variables of interest, including the noise levels and their resulting biological responses that were statistically significant. For this subset of papers, one author was randomly assigned a list of papers and then a second author was randomly assigned to assess the accuracy of the data collected by the first author. Any discrepancies were discussed as a group until an agreement was reached. Noise categories (environmental, transportation, industrial, multiple, other) were chosen for each paper by noting the explicitly stated source or description of urban noise described in the methodology. Noise levels and their units were reported for each paper, with only noise levels reported in decibels (dB) being used in data analysis. We recorded the sound metric used (i.e., SPL, SPL Max, Leq) for each paper and also recorded the weightings for each noise level. ## Description of the data and file structure Part I: Spatial Analysis of Noise Dataset Variables and Definitions Spreadsheet name: HOLC\_Noise\_City\_Results HOLC\_GRADE: HOLC redlining grade (grades A, B, C, D) COUNT: Count of pixels with non zero noise values for a given HOLC grade and city AREA: Area covered by pixels with non zero noise values for a given HOLC grade and city MIN: Minimum pixel noise value for a given HOLC grade and city MAX: Maximum pixel noise value for a given HOLC grade and city RANGE: Pixel noise value range for a given HOLC grade and city MEAN: Mean of pixel noise values for a given HOLC grade and city STD: Standard Deviation of pixel noise values for a given HOLC grade and city SUM: Sum of pixel noise values for a given HOLC grade and city VARIETY: The number of unique values for a given HOLC grade and city MAJORITY: The most frequently occurring value for a given HOLC grade and city MINORITY: The least frequently occurring value for a given HOLC grade and city MEDIAN: Median of pixel noise values for a given HOLC grade and city TOT\_HOLC\_AREA\_SQM: total area in square meters covered by the HOLC grade in given city N\_median: N measure of excess noise where N = (grade area with noise pixels \* median noise per grade)/total area in grade city: city where analysis was performed state: state that the city was in Proportion HOLC with noise over 35 dB: the proportion of a HOLC grade in the target city with noise over 35 dB, calculated as (area of HOLC grade per city covered by noise above 35 dB/total area of HOLC grade per city) Part II: Literature Review Dataset Variables and Definitions Spreadsheet name: Urban\_noise\_wildlife\_literature\_review\_Dryad Paper Origin: dataset (Shannon et. al 2016 or New Review) Full citation: Full citation of paper Meets Criteria: whether or not the paper met our inclusion criteria Study type: Natural experiment, playback, theoretical, combination Notes for study type: notes describing study type Location of Experiment: lab, field, both, or theoretical Geographic region: The general geographic region in which the study took place: Africa, Antartica, Asia, Atlantic Ocean, Australia, Baltic Sea, Europe, Global, Indian Ocean, Mediterranean, North America, Pacific Ocean, South America, Biological response measured: The response of the study organism(s), specifically the response to anthropogenic noise: ecosystem, foraging behavior, life history/reproduction, mating behavior, movement behavior, physiological, population, vigilance behavior, vocal behavior 2nd Biological response measured: same as above Measured response? Whether the study collected a metric measuring the biological response Group type: Birds, fish, herpetofauna, invertebrates, mammals, multiple Trophic level: Carnivore, herbivore, omnivore, multiple Habitat: Aquatic, terrestrial Noise stimulus category: industrial, transportation, environmental, military, recreation, other Frequency of Noise: Whether the frequency range of the received noise was reported in the paper 1st Background Level Mean Value: The range or point estimate for background (ambient) noise level(s) if it was reported 2nd Background Level Mean Value: The range or point estimate for background (ambient) noise level(s) if it was reported Background Level Units: units of noise metric, e.g. dB(A) Mitigation: Whether or not the study tested mitigation to address impacts of noise Explain Mitigation (if applicable): a description of what the mitigation study did if applicable First noise level that caused a response: The noise level at which the study organism responded (measured biological response) to the sound/noise stimulus. Noise Level Units: Report associated unit for the first response (dB, Hz, etc.) Noise Level Minimum Value: The value of noise that caused a response when the reported value was a minimum level (for the first response) Noise Level Maximum Value: The value of noise that caused a response when the reported value was a maximum level (for the first response) Noise Level Mean Value: The value of noise that caused a response when the reported value was a mean level (for the first response) Noise Level Standard Deviation: The standard deviation associated with the noise value, when reported (for the first response) Notes on Response Level 1: Additional notes are details describing the first biological response data collected What was the SPECIFIC biological response(s) from the organism from Response Level 1?: How did the biological response change? E.g., Minimum frequency, number of songs, or duration of calls increased or decreased, species richness increased or decreased, etc. (for the first response) Second noise level that caused a response: The noise level at which the study organism responded (measured biological response) to the sound/noise stimulus. Second Noise Level Units: Report associated unit for the second response (dB, Hz, etc.) Second Noise Level Minimum Value: The value of noise that caused a response when the reported value was a minimum level (for the second response) Second Noise Level Maximum Value: The value of noise that caused a response when the reported value was a maximum level (for the second response) Second Noise Level Mean Value: The value of noise that caused a response when the reported value was a mean level (for the second response) Second Noise Level Standard Deviation: The standard deviation associated with the noise value, when reported (for the second response) Notes on Response Level 2: Additional notes are details describing the second biological response data collected What was the SPECIFIC biological response(s) from the organism from Response Level 2?: How did the biological response change? E.g., Minimum frequency, number of songs, or duration of calls increased or decreased, species richness increased or decreased, etc. (for the second response) Notes on Other Significant Responses: Notes describing any other significant responses reported in the study Non-significant biological responses: List of any non-significant biological responses to noise described in the paper Time period: When the study took place NA values in the data indicate instances where data were not collected because they did not meet the study criteria. ## Sharing/Access information Links to other publicly accessible locations of the redlining boundaries and the transportation noise datasets. * https://dsl.richmond.edu/panorama/redlining/#loc=5/39.1/-94.58&text=downloads * https://geodata.bts.gov/ Data was derived from the following sources: * Robert K. Nelson, LaDale Winling, Richard Marciano, Nathan Connolly, et al., “Mapping Inequality,” American Panorama, ed. Robert K. Nelson and Edward L. Ayers, accessed October 7, 2023, https://dsl.richmond.edu/panorama/redlining/[YOUR VIEW]. * BUREAU OF TRANSPORTATION STATISTICS, U.S. Department of Transportation. ## Code Information R coding script for regression models used to evaluate relationships between the N\_median variable and the HOLC grade and population predictor variables.