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. 2025 Sep;9(9):1585-1598.
doi: 10.1038/s41559-025-02786-5. Epub 2025 Jul 9.

Human contributions to global soundscapes are less predictable than the acoustic rhythms of wildlife

Panu Somervuo  1 Tomas Roslin  2   3 Brian L Fisher  4   5 Bess Hardwick  1 Deirdre Kerdraon  2 Dimby Raharinjanahary  4 Eric Tsiriniaina Rajoelison  4 Patrik Lauha  1 Lukas Griem  6 Petteri Lehikoinen  7 Pekka Niittynen  8 Esko Piirainen  7 Markus Lumme  7 Ville-Matti Riihikoski  7 Orlando Acevedo-Charry  9   10 Solny A Adalsteinsson  11 Maaz Ahmad  12 Sandra Alcobia  13   14 Jón Aldará  15 Nigel R Andrew  16 Sten Anslan  17   18 Alexandre Antonelli  19   20   21 Julieta Soledad Arena  22 Santiago Arroyo Almeida  23 Ines Aster  24 Hannu Autto  25 Anahi Aviles Gamboa  11 Joaquín Baixeras  26 Mario Baldauf  24 Rosario Balestrieri  27 Gaia Giedre Banelyte  2 Adrian Barrett  28 Pedro Beja  29   30   31 Thomas Olof Berg  32 Benjamin Bergerot  33 Elizabeth G Biro  11 Pedro G Blendinger  34 Loïc Bollache  35   36 Magda Bou Dagher Kharrat  37   38 Stephane Boyer  39 Erika Bridell  40 Martyn Brotherson  41 Leslie Robert Brown  42 Hannah L Buckley  43 Erika Buscardo  44 Nokuphila Buthelezi  45 Luciano Cagnolo  22 Alice Calvente  46 Giovanni Capobianco  47 Laura Carreón-Palau  48 Suzanne Carriere  49 Bradley S Case  43 Jenyu Chang  50 Juan Matías Chaparro  51 Chi-Ling Chen  50 Christine Chicoine  52   53 Madeleine Christensson  54 Francisco Collado Rosique  55 William Colom Montero  40 Ricardo do Sacramento da Fonseca  56 Luís P Da Silva  29   30 Anamaria Dal Molin  57 Tad Dallas  58 Maria Carla de Francesco  59 Jorge Arturo Del Ángel-Rodríguez  60 Ricardo Díaz-Delgado  61 Thomas Dirnböck  62 Ika Djukic  62 Philile Dladla  45 Jeremías Domínguez Masciale  22 Thiago Dorigo  32   63 Errol Douwes  45   64 Torbjørn Ekrem  65 Helena Enderskog  66 Charlotta Erefur  67 Muhammad Fahad  68 Mohsen Falahati-Anbaran  65 Arielle Farrell  2 Gabriel Ferland  69 Emanuele Ferrari  70 Axa Figueiredo  71 Fernando Forero  72 Inga Freiberga  73 Andrea Frosch-Radivo  74 Luis Alberto Ganchozo Intriago  23 Laura Garzoli  75 Paola Giacomotti  75 Andros T Gianuca  76 Olivier Gilg  35   36 Vladimir Gilg  36 Fanney Gísladóttir  77 Ryan Glowacki  41 Brigitte Gottsberger  74 Jocelyn Gregoire  78 Elli Groner  79   80 Patrícia Guedes  29   30 Aimee Michelle Guile  81 Peter Haase  82   83 Fazal Hadi  84 Magdalena Haidegger  85 Leivur Janus Hansen  15 Lars Holst Hansen  86 Reid Harrop  87 Harald Havnås  88 David Herrera Báez  55 Chris C Y Ho  89 Denise Hohenbühel  74 Marketa Houska Tahadlova  73   90 Jari Hänninen  91 Linda Höglund  54 Kolbrún Í Haraldsstovu  15 Elise Imbeau  69 Jasmin Inkinen  91 Masae Iwamoto Ishihara  92 Abigail C Jackson  93   94 Gunnar Jansson  54 Rohit Jha  95 Gerald Kager  96 Rhea Kahale  38 Oula Kalttopää  25 Elizabeth Wanjiru Karai  97 Dave Karlsson  88 Andrea Kaus-Thiel  98 Asghar Khan  99 Qaisar Khan  100 Keishi Kimoto  92   101 Shadrack Chumo Kipngetich  97 Clemens Klante  102   103   104 Leif Klemedtsson  105 Mårten Klinth  88 Janne Koskinen  106 Matti Kotakorpi  107 Agnes-Katharina Kreiling  15 Irmgard Krisai-Greilhuber  74 Erik Kristensen  108 Sebastian König  109   110 Silke Langenheder  40 Kalevi Laurila  25 Pascaline Le Gouar  33 Nicolas Lecomte  52   111   112 Erin Lecomte  52   112 Paula Moraes Leitman  32   113   114 Jorge L León-Cortés  115 Daijiang Li  95 John Loehr  107 Carlos Lopez-Vaamonde  39   116 Mehsen Makari  38 Gabriela Giselle Mangini  34 Michael Maroschek  109   110 Vanessa A Mata  29   30 Shunsuke Matsuoka  92 Thais Mazzafera  117 Paul G McDonald  118 Laura Meinert  81 Mayra Meléndez-González  93   94 Angela M Mendoza-Henao  10 Sebastien Moreau  39 Jérôme Moreau  36   119   120 Jesper Mosbacher  121 Esteban Moyer  39 Anna Mrazova  73   90 Samantha Mteshane  122 Nancy Wangari Mungai  97 Gema Muñoz Herraiz  123 Andrea Murillo-Vázquez  115 Simona Musazzi  75 Marko Mutanen  124 Jörg Müller  125   126   127 Rebeca Navarro Canales  55 Monica Ndlovu  45 Annegret Nicolai  33   128 Armin Niessner  129 Jenni Nordén  130 Paweł Nowak  131 Erin O'Connell  11 Arianna Orru  75 Thomas Pagnon  35   36 Yurani Nayive Pantoja-Diaz  10   132 Mikko Pentinsaari  133   134 Sebastian Pilloni  85 Adrian Pinder  28 Thiago A Pinheiro  135   136 Sergei Põlme  17 Luke L Powell  29   30   137 Gisela Pröll  62 Paola Pulido-Santacruz  138   139 Enrique Queralt  140 Mark Tristan Quilantang  89 Kirsty Quinlan  141 Ricardo Ramirez  142 Juha Rankinen  102   103 Micaela Del Valle Rasino  59 Rui Rebelo  14 Wolfram Remmers  143 Franziska Retz  125 Evelin Reyes  95 Gonzalo Rivas Torres  23 Hanna M K Rogers  2 Inês T Rosário  14 Sidney Rosário Da Rosàrio da Costa  144 Tobias Rütting  105 Johannes Sahlstén  91 Carole Saliba  38 Teppo Salmirinne  145 Katerina Sam  73   90 Douglas Santos  44 Margarida Santos-Reis  14 Michel Sawan  146 Benjamin Schattanek-Wiesmair  24 Pauliina Schiestl-Aalto  147 Niels Martin Schmidt  86   148 Sebastian Seibold  109   110   149 Rupert Seidl  109   110 Linda Seifert  127 Malibongwe Sithole  42 Elise Sivault  73   90 Jessica Smart  150 Ireneusz Smerczyński  131 Ayaka Soda  151 Renata S Sousa-Lima  135 Angela Stanisci  59 Margaret C Stanley  152 Daleen Steenkamp  42 Elisa Stengel  125 Stefan Stoll  83   143 Willem Maartin Strauss  42 Elisabeth Stur  65 Maija Sujala  25 Janne Sundell  107 Jónína Svavarsdóttir  77 Leho Tedersoo  17   153 Saana Tepsa  106 Maor Tiko Tikochinsky  79 Esa-Pekka Tuominen  107 Stefanie Tweraser  154 Catalina Ulloa Espinosa  23   155 Joni Uusitalo  107 Mikko Vallinmäki  124 Fabrice Vannier  39 Abigail Varela  156 Emma Vatka  124 Silja Veikkolainen  25 Karl Vernes  118 Phillip C Watts  18 Per Weslien  105 Ciara Wirth  23 Jana Helga Wisniewski  87 Amanda B Young  93   94 Robyn Övergaard  40 Otso Ovaskainen  157   158
Affiliations

Human contributions to global soundscapes are less predictable than the acoustic rhythms of wildlife

Panu Somervuo et al. Nat Ecol Evol. 2025 Sep.

Abstract

Across the world, human (anthropophonic) sounds add to sounds of biological (biophonic) and geophysical (geophonic) origin, with human contributions including both speech and technophony (sounds of technological devices). To characterize society's contribution to the global soundscapes, we used passive acoustic recorders at 139 sites across 6 continents, sampling both urban green spaces and nearby pristine sites continuously for 3 years in a paired design. Recordings were characterized by bird species richness and by 14 complementary acoustic indices. By relating each index to seasonal, diurnal, climatic and anthropogenic factors, we show here that latitude, time of day and day of year each predict a substantial proportion of variation in key metrics of biophony-whereas anthropophony (speech and traffic) show less predictable patterns. Compared to pristine sites, the soundscape of urban green spaces is more dominated by technophony and less diverse in terms of acoustic energy across frequencies and time steps, with less instances of quiet. We conclude that the global soundscape is formed from a highly predictable rhythm in biophony, with added noise from geophony and anthropophony. At urban sites, animals experience an increasingly noisy background of sound, which poses challenges to efficient communication.

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Conflict of interest statement

Competing interests: The authors declare no competing interests.

Figures

Fig. 1
Fig. 1. Acoustic indices used to track the rhythms in the global soundscape.
Top: two example spectrograms with the signatures of different sound sources highlighted and identified. Bottom: table lists and briefly defines 15 acoustic indices of the soundscape. In the table and in all subsequent figures, we sort indices by their type (how they are calculated), whereas letters clarify how they are assigned: B, biophony; G, geophony; A, anthropophony; or NA, no clear classification. The values of each index for the example audio clips are given in the last two columns. sp, species.
Fig. 2
Fig. 2. Sampling design and coverage.
a, Across the world, we used up to five AudioMoth samplers to record the local soundscape at each of 139 sites. To characterize differences between natural sites (filled green circles) and urban green spaces (open black squares), 83 of the sites were part of a paired design, with each habitat type sampled for a year within a distance of 4–50 km. To avoid the effects of specific years, the starting habitat (natural or urban green space) was randomized between sites. For part of the material (violet symbols), the habitat was fixed to natural sites alone. b, This resulted in multi-annual time series for individual sites (y axis), with the coverage of individual weeks shown by squares across time on the x axis. Habitats are coloured green for natural and black for urban green space.
Fig. 3
Fig. 3. Seasonal and diurnal variation in different acoustic indices.
Predictions for the hour of the day (left) and day of the year (right) for 30° S, 0°, 30° N and 60° N. The predictions shown are based on the global model fitted to all data and shown for those eight indices for which the seasonal and diurnal patterns explained a substantial part of the variation (Fig. 4). Here time is represented by local absolute time; for patterns with respect to time relative to sun time, see Supplementary Fig. 57. Site-specific results for all acoustic indices are shown in Supplementary Information 1. For definitions of each index, see Fig. 1.
Fig. 4
Fig. 4. Predictability of 15 acoustic indices in space and time and differences across pairs of natural versus urban sites.
a, Predictability of 15 acoustic indices in space and time. The total height of each bar shows the proportion of variance explained (R2) by site-specific models. The blue section shows variation explained by the latitude of the site using a global model (gm). The significance of latitude was determined by a permutation test (two-sided; 139 sites; 1,000 permutations; no adjustment for multiple comparisons), with index-specific P values as follows: 0.733, 0.001, 0.001, 0.693, 0.003, 0.001, 0.001, 0.359, 0.001, 0.106, 0.001, 0.001, 0.018, 0.001 and 0.001. Significance levels are *P ≤ 0.05, **P ≤ 0.01 and ***P 0.001. Black (positive effect, POS) and green (negative effect, NEG) sections show the increase in R2 with the addition of the site-specific human footprint index (hfi) to the global model. The yellow sections indicate the increase in R2 when climatic conditions (elevation, mean annual temperature and precipitation) are added to a model including hfi. b, Differences observed across pairs of natural versus urban sites. Each box shows the distribution of empirically observed pairwise differences between the two sites within a pair—with a box for the interquartile range (50% of data), a vertical line for the median; whiskers for the minimum and maximum up to 1.5× interquartile range from the box; and individual data points for outliers beyond this range. Since the difference is calculated as urban minus natural values, a positive value indicates higher values for urban sites (significant differences shown by black boxes) whereas a negative value indicates higher values at natural sites (significant differences shown by green boxes). Index-specific P values from two-sided t-tests across 36 paired values (without adjustments for multiple comparisons): 1.06 × 10−5, 7.91 × 10−4, 1.46 × 10−1, 8.60 × 10−1, 1.89 × 10−7, 3.06 × 10−3, 2.45 × 10−5, 5.71 × 10−4, 9.51 × 10−9, 3.46 × 10−8, 5.41 × 10−6, 2.65 × 10−2, 3.27 × 10−1, 1.10 × 10−6 and 6.07 × 10−2 (with asterisks as in a). Index letters as in Fig. 1. Diel variation was modelled by local absolute time; for patterns with respect to sun time, see Supplementary Fig. 58.
Fig. 5
Fig. 5. Species richness for 36 site pairs composed of natural and urban sites.
a,b, Species richness for individual urban and natural sites addressing whether urban or natural sites have more species (a) and whether urban and natural sites have different species (b). c,d, Species richness as a function of the number of bird detections sampled separately for each site after which we averaged the resulting curves (c) and in samples from pooled natural and pooled urban sites (d). Green curves emanate from natural sites and black curves from urban green spaces. Light-blue curves are based on data combined across the natural site and its paired urban green space, and thereby represent sampling of recordings irrespective of the environment of origin. The data include bird detections (BirdNET confidence threshold 0.8) for which recordings were available for both urban and natural sites at the same day of the year and the same time of the day within each pair. The resulting data have been sampled with replacement. In a and b, species richness S is defined as the number of distinct species in 1,000 detections, whereas c and d show the accumulation of species richness detected up to 2,000 detections. All results are averages across 50 replicates. LAT, latitude.

References

    1. Pijanowski, B. C. Principles of Soundscape Ecology—Discovering Our Sonic World (Univ. Chicago Press, 2024).
    1. Pijanowski, B. C. et al. Soundscape ecology: the science of sound in the landscape. Bioscience61, 203–216 (2011). - DOI
    1. Daniel, J. C. & Blumstein, D. T. A test of the acoustic adaptation hypothesis in four species of marmots. Anim. Behav.56, 1517–1528 (1998). - DOI - PubMed
    1. Bennet-Clark, H. C. Size and scale effects as constraints in insect sound communication. Philos. Trans. R. Soc. Lond. B353, 407–419 (1998). - DOI
    1. Farina, A. & Belgrano, A. The eco-field hypothesis: toward a cognitive landscape. Landsc. Ecol.21, 5–17 (2006). - DOI

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