Liu, X. et al. High-spatiotemporal-resolution mapping of global urban change from 1985 to 2015. Nat. Sustain. 3, 564–570 (2020).
Google Scholar
Chace, J. F. & Walsh, J. J. Urban effects on native avifauna: A review. Landsc. Urban Plan. 74, 46–69 (2006).
Google Scholar
Rosenberg, K. V. et al. Decline of the North American avifauna. Science (1979) 366, 120–124 (2019).
Google Scholar
Isaksson, C. Impact of Urbanization on Birds https://doi.org/10.1007/978-3-319-91689-7_13 (2018).
Google Scholar
Grimm, N. B. et al. Global change and the ecology of cities. Science 319, 756–760. https://doi.org/10.1126/science.1150195 (2008).
Google Scholar
Pipoly, I. et al. Extreme hot weather has stronger impacts on Avian reproduction in forests than in cities. Front. Ecol. Evol. 10, 1 (2022).
Google Scholar
Newberry, G. N., O’Connor, R. S. & Swanson, D. L. Urban rooftop-nesting Common Nighthawk chicks tolerate high temperatures by hyperthermia with relatively low rates of evaporative water loss. Condor 123, 016 (2021).
Google Scholar
da Silva, A., Valcu, M. & Kempenaers, B. Light pollution alters the phenology of dawn and dusk singing in common European songbirds. Philos. Trans. R. Soc. B: Biol. Sci. 370, 126 (2015).
Google Scholar
Welbers, A. A. M. H. et al. Artificial light at night reduces daily energy expenditure in breeding great tits (Parus major). Front. Ecol. Evol. 5, 55 (2017).
Google Scholar
van Doren, B. M. et al. High-intensity urban light installation dramatically alters nocturnal bird migration. Proc. Natl. Acad. Sci. USA. 114, 11175–11180 (2017).
Google Scholar
Miller, M. W. Apparent effects of light pollution on singing behavior of American Robins. Condor 108, 130–139 (2006).
Google Scholar
Nemeth, E. & Brumm, H. Birds and anthropogenic noise: Are urban songs adaptive?. Am. Nat. 176, 465 (2010).
Google Scholar
Nemeth, E. et al. Bird song and anthropogenic noise: Vocal constraints may explain why birds sing higher-frequency songs in cities. Proc. R. Soc. B: Biol. Sci. 280, 20122798 (2013).
Google Scholar
Senzaki, M., Yamaura, Y., Francis, C. D. & Nakamura, F. Traffic noise reduces foraging efficiency in wild owls. Sci. Rep. 6, 1–7 (2016).
Google Scholar
Ortega, C. P. Effects of noise pollution on birds: A brief review of our knowledge. Ornithol. Monogr. 74, 6–22 (2012).
Google Scholar
Sanderfoot, O. V. & Holloway, T. Air pollution impacts on avian species via inhalation exposure and associated outcomes. Environ. Res. Lett. 12, 832. https://doi.org/10.1088/1748-9326/aa8051 (2017).
Google Scholar
Eeva, T. & Lehikoinen, E. Egg shell quality, clutch size and hatching success of the great tit (Parus major) and the pied flycatcher (Ficedula hypoleuca) in an air pollution gradient. Oecologia 102, 312–323 (1995).
Google Scholar
Tablado, Z. et al. Effect of human disturbance on bird telomere length: An experimental approach. Front. Ecol. Evol. 9, 1 (2022).
Google Scholar
Kang, W., Minor, E. S., Park, C. R. & Lee, D. Effects of habitat structure, human disturbance, and habitat connectivity on urban forest bird communities. Urban Ecosyst. 18, 857–870 (2015).
Google Scholar
Blair, R. B. Land use and avian species diversity along an urban gradient. Ecol. Appl. 6, 506–519 (1996).
Google Scholar
Estela, F. A. et al. Changes in the nocturnal activity of birds during the covid–19 pandemic lockdown in a neotropical city. Anim. Biodivers. Conserv. 44, 1 (2021).
Bates, A. E., Primack, R. B., Moraga, P. & Duarte, C. M. COVID-19 pandemic and associated lockdown as a “Global Human Confinement Experiment” to investigate biodiversity conservation. Biol. Conserv. 248, 108665. https://doi.org/10.1016/j.biocon.2020.108665 (2020).
Google Scholar
Rutz, C. et al. COVID-19 lockdown allows researchers to quantify the effects of human activity on wildlife. Nat. Ecol. Evol. 4, 1156–1159. https://doi.org/10.1038/s41559-020-1237-z (2020).
Google Scholar
Czech, K., Davy, A. & Wielechowski, M. Does the covid-19 pandemic change human mobility equally worldwide? Cross-country cluster analysis. Economies 9, 182 (2021).
Google Scholar
Galeazzi, A. et al. Human mobility in response to COVID-19 in France, Italy and UK. Sci. Rep. 11, 1 (2021).
Google Scholar
Joshi, Y. V. & Musalem, A. Lockdowns lose one third of their impact on mobility in a month. Sci. Rep. 11, 1 (2021).
Google Scholar
Dobbie, L. J., Hydes, T. J., Alam, U., Tahrani, A. & Cuthbertson, D. J. The impact of the COVID-19 pandemic on mobility trends and the associated rise in population-level physical inactivity: Insights From International Mobile Phone and National Survey Data. Front. Sports Active Living 4, 80 (2022).
Google Scholar
Basu, B. et al. Investigating changes in noise pollution due to the COVID-19 lockdown: The case of Dublin, Ireland. Sustain. Cities Soc. 65, 102597 (2021).
Google Scholar
Lecocq, T. et al. Global quieting of high-frequency seismic noise due to COVID-19 pandemic lockdown measures. Science (1979) 369, 1338 (2020).
Terry, C., Rothendler, M., Zipf, L., Dietze, M. C. & Primack, R. B. Effects of the COVID-19 pandemic on noise pollution in three protected areas in metropolitan Boston (USA). Biol. Cons. 256, 109039 (2021).
Google Scholar
Venter, Z. S., Aunan, K., Chowdhury, S. & Lelieveld, J. COVID-19 lockdowns cause global air pollution declines. Proc Natl Acad Sci U S A 117, 18984 (2020).
Google Scholar
Archer, C. L., Cervone, G. & Golbazi, M. Changes in air quality and human mobility in the US during the COVID-19 pandemic. Bull. Atmosp. Sci. Technol. 1, 491–541. https://doi.org/10.1007/s42865-020-00019-0 (2020).
Google Scholar
Jiang, Z. et al. Modeling the impact of COVID-19 on air quality in Southern California: Implications for future control policies. Atmosp. Chem. Phys. Discuss. https://doi.org/10.5194/acp-2020-1197 (2020).
Shi, Z. et al. Abrupt but smaller than expected changes in surface air quality attributable to COVID-19 lockdowns. Sci. Adv. 7, 6696 (2021).
Google Scholar
Hentati-Sundberg, J., Berglund, P. A., Hejdström, A. & Olsson, O. COVID-19 lockdown reveals tourists as seabird guardians. Biol. Conserv. 254, 108950 (2021).
Google Scholar
Derryberry, E. P., Phillips, J. N., Derryberry, G. E., Blum, M. J. & Luther, D. Singing in a silent spring: Birds respond to a half-century soundscape reversion during the COVID-19 shutdown. Science (1979) 370, 575 (2020).
Google Scholar
Schrimpf, M. B. et al. Reduced human activity during COVID-19 alters avian land use across North America. Sci. Adv. 7, 5073 (2021).
Google Scholar
MacKenzie, D. I. et al. Estimating site occupancy rates when detection probabilities are less than one. Ecology 83, 2248–2252 (2002).
Google Scholar
Gordo, O., Brotons, L., Herrando, S. & Gargallo, G. Rapid behavioural response of urban birds to COVID-19 lockdown. Proc. R. Soc. B: Biol. Sci. 288, 20202513 (2021).
Google Scholar
Johnson, D. H. In defense of indices: The Case of Bird Surveys. J. Wildl. Manag. 72, 857–868 (2008).
Google Scholar
Sanderfoot, O. V. & & Gardner, B.,. Wildfire smoke affects detection of birds in Washington State. Ornithol. Appl. 123, 28 (2021).
Sumasgutner, P. et al. Raptor research during the COVID-19 pandemic provides invaluable opportunities for conservation biology. Biol. Conserv. 260, 109149 (2021).
Google Scholar
Crimmins, T. M., Posthumus, E., Schaffer, S. & Prudic, K. L. COVID-19 impacts on participation in large scale biodiversity-themed community science projects in the United States. Biol. Conserv. 256, 109017 (2021).
Google Scholar
Basile, M., Russo, L. F., Russo, V. G., Senese, A. & Bernardo, N. Birds seen and not seen during the COVID-19 pandemic: The impact of lockdown measures on citizen science bird observations. Biol. Conserv. 256, 109079 (2021).
Google Scholar
Kishimoto, K. & Kobori, H. COVID-19 pandemic drives changes in participation in citizen science project “City Nature Challenge” in Tokyo. Biol. Conserv. 255, 109001 (2021).
Google Scholar
Sullivan, B. L. et al. eBird: A citizen-based bird observation network in the biological sciences. Biol. Conserv. 142, 2282 (2009).
Google Scholar
Pacifici, K., Simons, T. R. & Pollock, K. H. Effects of vegetation and background noise on the detection process in auditory avian point-count surveys. Auk 125, 600–607 (2008).
Google Scholar
Mitchell, M. S. et al. Testing a priori hypotheses improves the reliability of wildlife research. J. Wildl. Manag. 82, 1568. https://doi.org/10.1002/jwmg.21568 (2018).
Google Scholar
Sells, S. N. et al. Increased scientific rigor will improve reliability of research and effectiveness of management. J. Wildl. Manag. 82, 485. https://doi.org/10.1002/jwmg.21413 (2018).
Google Scholar
Strimas-Mackey, M., E. Miller, and W. Hochachka. auk: eBird Data Extraction and Processing with AWK. R package version 0.3.0. (2018) https://cornelllabofornithology.github.io/auk/
R Core Team. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria (2020). https://www.R-project.org/.
U.S. Environmental Protection Agency (EPA). Air Quality System Data Mart (2020). https://www.epa.gov/airdata
Karagulian, F. et al. Contributions to cities’ ambient particulate matter (PM): A systematic review of local source contributions at global level. Atmos. Environ. 120, 475. https://doi.org/10.1016/j.atmosenv.2015.08.087 (2015).
Google Scholar
Ito, K., Thurston, G. D. & Silverman, R. A. Characterization of PM25, gaseous pollutants, and meteorological interactions in the context of time-series health effects models. J. Exposure Sci. Environ. Epidemiol. 17, S45–S60 (2007).
Google Scholar
Google LLC “Google COVID-19 Community Mobility Reports”. https://www.google.com/covid19/mobility/ Accessed: November 1, 2020.
Waze “Global Mobility Report”. https://www.waze.com Accessed: May 22, 2020.
Pierce, D. ncdf4: Interface to Unidata netCDF (Version 4 or Earlier) Format Data Files. R package version 1.17 (2019). https://CRAN.R-project.org/package=ncdf4
Esri “USA NLCD Land Cover” [imagery layer]. Esri Inc (2019). https://www.arcgis.com/home/item.html?id=3ccf118ed80748909eb85c6d262b426f.
Esri Inc. ArcMap (Version 10.8.1). Esri Inc. Redlands, California, USA (2020). https://desktop.arcgis.com/en/arcmap/.
Fiske, I. & Chandler, R. unmarked: An R package for fitting hierarchical models of wildlife occurrence and abundance. J. Stat. Softw. 43(10), 1–23 (2011).
Google Scholar
Efford, M. G. & Dawson, D. K. Occupancy in continuous habitat. Ecosphere 3, 1 (2012).
Google Scholar
Lee, B. P. Y. H., Davies, Z. G. & Struebig, M. J. Smoke pollution disrupted biodiversity during the 2015 El Niño fires in Southeast Asia. Environ. Res. Lett. 12, 094022 (2017).
Google Scholar
Leonard, R. J. & Hochuli, D. F. Exhausting all avenues: why impacts of air pollution should be part of road ecology. Front. Ecol. Environ. 15, 443. https://doi.org/10.1002/fee.1521 (2017).
Google Scholar
Plummer, K. E., Risely, K., Toms, M. P. & Siriwardena, G. M. The composition of British bird communities is associated with long-term garden bird feeding. Nat. Commun. 10, 1 (2019).
Google Scholar
Cleary, G. P. et al. Avian assemblages at bird baths: A comparison of urban and rural bird baths in Australia. PLoS ONE 11, e0150899 (2016).
Google Scholar
Bailey, L. L., Mackenzie, D. I. & Nichols, J. D. Advances and applications of occupancy models. Methods Ecol. Evol. 5, 1269 (2014).
Google Scholar
Leong, M., Dunn, R. R. & Trautwein, M. D. Biodiversity and socioeconomics in the city: a review of the luxury effect. Biol. Lett. 14, 1. https://doi.org/10.1098/rsbl.2018.0082 (2018).
Google Scholar
Source: Ecology - nature.com
