Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

Multidecadal legacy of uneven urbanization on divergent prospects for bird biodiversity

Nature Cities volume 3, pages 176–188 (2026)Cite this article

Subjects

Abstract

Urbanization constitutes a primary driver of the global biodiversity crisis, yet how historical urban legacy effects shape contemporary biodiversity remains unclear. Neglecting lagged ecological consequences such as extinction debts and colonization credits could obscure both the risks of future urban biodiversity loss and the effectiveness of conservation efforts. Here, by integrating equilibrium and non-equilibrium models, we quantified 31-year legacy effects of urbanization on bird communities and species in China. We found that China’s uneven urbanization has generated widespread extinction debts and colonization credits across the taxonomic, functional and phylogenetic dimensions of bird communities. The lag durations of various urban environmental characteristics differed, with historical vegetation cover and anthropogenic activities having long-lasting impacts on existing bird distributions. In particular, species-specific lagged responses were identified, which were correlated with each species’ capacity to adapt to urban environment (urban tolerance). These findings underscore the necessity of integrating long-term biodiversity considerations into urban governance through forward-looking approaches as well as providing critical insights for biodiversity-friendly urban planning.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on SpringerLink
  • Instant access to the full article PDF.

USD 39.95

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Conceptual framework of the study.
Fig. 2: Extinction debts and colonization credits at the community level.
Fig. 3: Extinction debts and colonization credits across the three urbanization patterns.
Fig. 4: Lag durations of the responses of species to urban landscape structure, climate and socioeconomic changes.
Fig. 5: Modulation of lagged responses by life-history traits.
Fig. 6: Conceptual framework for urban habitat restoration and species conservation.

Similar content being viewed by others

Data availability

The data generated in this study are available via figshare at https://doi.org/10.6084/m9.figshare.29850275 (ref. 77). The normalized difference vegetation index data (1990–2020) are available at https://doi.org/10.1038/s41597-024-03364-3. Land cover datasets (1990–2020) are available at https://doi.org/10.5194/essd-13-3907-2021. Climate data, including temperature and precipitation (1990–2020), are available at https://cstr.cn/18406.11.Meteoro.tpdc.270961 and https://doi.org/10.5281/zenodo.3114194. Population data (1990–2020) are available at https://doi.org/10.1038/s41597-024-02913-0, whereas nighttime light data (1990–2020) are accessible at https://doi.org/10.1038/s41597-024-03223-1. The species’ life-history traits are available at https://doi.org/10.1111/ele.13898, https://doi.org/10.1038/s41597-025-05615-3 and https://avibase.bsc-eoc.org/avibase.jsp. The phylogenetic tree is available at https://doi.org/10.1073/pnas.2409658122.

Code availability

The code that supports the findings of this study is available via figshare at https://doi.org/10.6084/m9.figshare.29850275 (ref. 77).

References

  1. Ives, C. D. et al. Cities are hotspots for threatened species. Glob. Ecol. Biogeogr. 25, 117–126 (2016).

    Google Scholar 

  2. Soanes, K. et al. Conserving urban biodiversity: current practice, barriers, and enablers. Conserv. Lett. 16, e12946 (2023).

    Google Scholar 

  3. Simkin, R. D., Seto, K. C., McDonald, R. I. & Jetz, W. Biodiversity impacts and conservation implications of urban land expansion projected to 2050. Proc. Natl Acad. Sci. USA 119, e2117297119 (2022).

    Google Scholar 

  4. Chakraborty, T. et al. Large disagreements in estimates of urban land across scales and their implications. Nat. Commun. 15, 9165 (2024).

    Google Scholar 

  5. Gao, J. & O’Neill, B. C. Mapping global urban land for the 21st century with data-driven simulations and Shared Socioeconomic Pathways. Nat. Commun. 11, 2302 (2020).

    Google Scholar 

  6. McDonald, R. I. et al. Research gaps in knowledge of the impact of urban growth on biodiversity. Nat. Sustain. 3, 16–24 (2019).

    Google Scholar 

  7. Liu, Q. et al. Identifying the combined impact of human activities and natural factors on China’s avian species richness using interpretable machine learning methods. J. Environ. Manag. 376, 124479 (2025).

    Google Scholar 

  8. Wilson, A. A. et al. Artificial night light and anthropogenic noise interact to influence bird abundance over a continental scale. Glob. Change Biol. 27, 3987–4004 (2021).

    Google Scholar 

  9. Roberts, P. et al. Using urban pasts to speak to urban presents in the Anthropocene. Nat. Cities 1, 30–41 (2024).

    Google Scholar 

  10. Jackson, S. T. & Sax, D. F. Balancing biodiversity in a changing environment: extinction debt, immigration credit and species turnover. Trends Ecol. Evol. 25, 153–160 (2010).

    Google Scholar 

  11. Nomoto, H. A. & Alexander, J. M. Drivers of local extinction risk in alpine plants under warming climate. Ecol. Lett. 24, 1157–1166 (2021).

    Google Scholar 

  12. Tilman, D., May, R. M., Lehman, C. L. & Nowak, M. A. Habitat destruction and the extinction debt. Nature 371, 65–66 (1994).

    Google Scholar 

  13. Ancillotto, L. et al. Past present: extinction debt of forest mammals from urban areas. Biol. Conserv. 306, 111143 (2025).

    Google Scholar 

  14. Newmark, W. D., Jenkins, C. N., Pimm, S. L., McNeally, P. B. & Halley, J. M. Targeted habitat restoration can reduce extinction rates in fragmented forests. Proc. Natl Acad. Sci. USA 114, 9635–9640 (2017).

    Google Scholar 

  15. Sandström, U. G., Angelstam, P. & Mikusiński, G. Ecological diversity of birds in relation to the structure of urban green space. Landsc. Urban Plan. 77, 39–53 (2006).

    Google Scholar 

  16. Fisher, J. C. et al. Spatio-temporal variability in forest biodiversity associated with human well-being across socio-economic deprivation gradients. Nat. Ecol. Evol. 9, 1382–1392 (2025).

    Google Scholar 

  17. Kuussaari, M. et al. Extinction debt: a challenge for biodiversity conservation. Trends Ecol. Evol. 24, 564–571 (2009).

    Google Scholar 

  18. Semper-Pascual, A. et al. Mapping extinction debt highlights conservation opportunities for birds and mammals in the South American Chaco. J. Appl. Ecol. 55, 1218–1229 (2018).

    Google Scholar 

  19. Culbert, P. D. et al. Legacy effects of past land use on current biodiversity in a low-intensity farming landscape in Transylvania (Romania). Landsc. Ecol. 32, 429–444 (2017).

    Google Scholar 

  20. Lira, P. K., Ewers, R. M., Banks-Leite, C., Pardini, R. & Metzger, J. P. Evaluating the legacy of landscape history: extinction debt and species credit in bird and small mammal assemblages in the Brazilian Atlantic Forest. J. Appl. Ecol. 49, 1325–1333 (2012).

    Google Scholar 

  21. Cohen, J. M. & Jetz, W. Geographic redistributions are insufficient to mitigate exposure to climate change in North American birds. Nat. Ecol. Evol. 9, 1234–1244 (2025).

    Google Scholar 

  22. Silvetti, L. E., Gavier Pizarro, G., Arcamone, J. R. & Bellis, L. M. Delayed responses and extinction debt: an opportunity for the conservation of Chaco Serrano forest birds. Anim. Conserv. 28, 277–290 (2025).

    Google Scholar 

  23. Epps, C. W. & Keyghobadi, N. Landscape genetics in a changing world: disentangling historical and contemporary influences and inferring change. Mol. Ecol. 24, 6021–6040 (2015).

    Google Scholar 

  24. Hahs, A. K. et al. Urbanisation generates multiple trait syndromes for terrestrial animal taxa worldwide. Nat. Commun. 14, 4751 (2023).

    Google Scholar 

  25. Watts, K. et al. Ecological time lags and the journey towards conservation success. Nat. Ecol. Evol. 4, 304–311 (2020).

    Google Scholar 

  26. Zhang, X. & Han, H. Characteristics and factors influencing the expansion of urban construction land in China. Sci. Rep. 14, 16040 (2024).

    Google Scholar 

  27. Haddou, Y., Mancy, R., Matthiopoulos, J., Spatharis, S. & Dominoni, D. M. Widespread extinction debts and colonization credits in United States breeding bird communities. Nat. Ecol. Evol. 6, 324–331 (2022).

    Google Scholar 

  28. Chanachai, J. et al. What remains to be discovered: a global assessment of tree species inventory completeness. Divers. Distrib. 30, e13862 (2024).

    Google Scholar 

  29. Blois, J. L., Williams, J. W., Fitzpatrick, M. C., Jackson, S. T. & Ferrier, S. Space can substitute for time in predicting climate-change effects on biodiversity. Proc. Natl Acad. Sci. USA 110, 9374–9379 (2013).

    Google Scholar 

  30. Almeida-Gomes, M., Lira, P. K., Severo-Neto, F., Souza, F. L. D. & Valente-Neto, F. Evidence of taxonomic but not functional diversity extinction debt in bird assemblages in an urban area in the Cerrado hotspot. Landsc. Urban Plan. 253, 105219 (2025).

    Google Scholar 

  31. Valiente-Banuet, A. et al. Beyond species loss: the extinction of ecological interactions in a changing world. Funct. Ecol. 29, 299–307 (2015).

    Google Scholar 

  32. Sol, D., Bartomeus, I., González-Lagos, C. & Pavoine, S. Urbanisation and the loss of phylogenetic diversity in birds. Ecol. Lett. 20, 721–729 (2017).

    Google Scholar 

  33. Chamberlain, D. E., Henry, D. A. W., Reynolds, C., Caprio, E. & Amar, A. The relationship between wealth and biodiversity: a test of the luxury effect on bird species richness in the developing world. Glob. Change Biol. 25, 3045–3055 (2019).

    Google Scholar 

  34. Lu, Y. et al. Spatial variation in biodiversity loss across China under multiple environmental stressors. Sci. Adv. 6, eabd0952 (2020).

    Google Scholar 

  35. Beninde, J., Veith, M. & Hochkirch, A. Biodiversity in cities needs space: a meta-analysis of factors determining intra-urban biodiversity variation. Ecol. Lett. 18, 581–592 (2015).

    Google Scholar 

  36. Liao, Z., Peng, S. & Chen, Y. Half-millennium evidence suggests that extinction debts of global vertebrates started in the Second Industrial Revolution. Commun. Biol. 5, 1311 (2022).

    Google Scholar 

  37. Wolfe, J. D. et al. Climate change aggravates bird mortality in pristine tropical forests. Sci. Adv. 11, eadq8086 (2025).

    Google Scholar 

  38. Viana, D. S. & Chase, J. M. Increasing climatic decoupling of bird abundances and distributions. Nat. Ecol. Evol. 6, 1299–1306 (2022).

    Google Scholar 

  39. Neate-Clegg, M. H. C., Tonelli, B. A. & Tingley, M. W. Advances in breeding phenology outpace latitudinal and elevational shifts for North American birds tracking temperature. Nat. Ecol. Evol. 8, 2027–2036 (2024).

    Google Scholar 

  40. Taheri, S., García-Callejas, D. & Araújo, M. B. Discriminating climate, land-cover and random effects on species range dynamics. Glob. Change Biol. 27, 1309–1317 (2021).

    Google Scholar 

  41. Virkkala, R. et al. Birds in boreal protected areas shift northwards in the warming climate but show different rates of population decline. Biol. Conserv. 226, 271–279 (2018).

    Google Scholar 

  42. Blair, R. B. Land use and avian species diversity along an urban gradient. Ecol. Appl. 6, 506–519 (1996).

    Google Scholar 

  43. Callaghan, C. T., Palacio, F. X., Benedetti, Y., Morelli, F. & Bowler, D. E. Large-scale spatial variability in urban tolerance of birds. J. Anim. Ecol. 92, 403–416 (2023).

    Google Scholar 

  44. Sol, D., González-Lagos, C., Moreira, D., Maspons, J. & Lapiedra, O. Urbanisation tolerance and the loss of avian diversity. Ecol. Lett. 17, 942–950 (2014).

    Google Scholar 

  45. Chen, L. & Khanna, M. Heterogeneous and long-term effects of a changing climate on bird biodiversity. Glob. Environ. Change Adv. 2, 100008 (2024).

    Google Scholar 

  46. Zizka, A. et al. CoordinateCleaner: standardized cleaning of occurrence records from biological collection databases. Methods Ecol. Evol. 10, 744–751 (2019).

    Google Scholar 

  47. Wang, Y. et al. A dataset on the life-history and ecological traits of Chinese birds. Biodivers. Sci. 29, 1149–1153 (2021).

    Google Scholar 

  48. Cordier, J. M. et al. Niche structure explains amphibians’ responses to habitat alteration. Glob. Ecol. Biogeogr. 34, e70045 (2025).

    Google Scholar 

  49. Jin, M., Sun, R., Yang, X., Yan, M. & Chen, L. Remote sensing-based morphological analysis of core city growth across the globe. Cities 131, 103982 (2022).

    Google Scholar 

  50. Hsieh, T. C., Ma, K. H. & Chao, A. iNEXT: an R package for rarefaction and extrapolation of species diversity (Hill numbers). Methods Ecol. Evol. 7, 1451–1456 (2016).

    Google Scholar 

  51. Li, H. et al. A daily gap-free normalized difference vegetation index dataset from 1981 to 2023 in China. Sci. Data 11, 527 (2024).

    Google Scholar 

  52. Yang, J. & Huang, X. The 30 m annual land cover dataset and its dynamics in China from 1990 to 2019. Earth Syst. Sci. Data 13, 3907–3925 (2021).

    Google Scholar 

  53. FRAGSTATS v. 4 (University of Massachusetts, Amherst, 2023).

  54. Peng, S. 1-km monthly mean temperature dataset for China (1901–2024). National Tibetan Plateau Data Center https://doi.org/10.11888/Meteoro.tpdc.270961 (2025).

  55. Peng, S. High-spatial-resolution monthly temperatures dataset over China during 1901–2017. Zenodo https://doi.org/10.5281/zenodo.3185722 (2020).

  56. Liu, L., Cao, X., Li, S. & Jie, N. A 31-year (1990–2020) global gridded population dataset generated by cluster analysis and statistical learning. Sci. Data 11, 124 (2024).

    Google Scholar 

  57. Zhang, L. et al. A prolonged artificial nighttime-light dataset of China (1984-2020). Sci. Data 11, 414 (2024).

    Google Scholar 

  58. Pohlert, T. trend: non-parametric trend tests and change-point detection. CRAN https://doi.org/10.32614/CRAN.package.trend (2015).

  59. Maechler, M. Cluster: finding groups in data—cluster analysis extended Rousseeuw et al. CRAN https://doi.org/10.32614/CRAN.package.cluster (1999).

  60. Tobias, J. A. et al. AVONET: morphological, ecological and geographical data for all birds. Ecol. Lett. 25, 581–597 (2022).

    Google Scholar 

  61. Şekercioğlu, ÇH. et al. BIRDBASE: a global dataset of avian biogeography, conservation, ecology and life history traits. Sci. Data 12, 1558 (2025).

    Google Scholar 

  62. Callaghan, C. T., Cornwell, W. K., Poore, A. G. B., Benedetti, Y. & Morelli, F. Urban tolerance of birds changes throughout the full annual cycle. J. Biogeogr. 48, 1503–1517 (2021).

    Google Scholar 

  63. Neate-Clegg, M. H. C. et al. Traits shaping urban tolerance in birds differ around the world. Curr. Biol. 33, 1677–1688.e6 (2023).

    Google Scholar 

  64. Fanelli, R. E., Martin, P. R., Robinson, O. J. & Bonier, F. Estimates of species-level tolerance of urban habitat in North American birds. Ecology 103, e3821 (2022).

    Google Scholar 

  65. Mazzariello, J. & Gassert, F. Global 100 m terrestrial human footprint (HFP-100). Dryad https://doi.org/10.5061/DRYAD.TTDZ08M1F (2023).

  66. Broekman, M. J. E. et al. Time-lagged effects of habitat fragmentation on terrestrial mammals in Madagascar. Conserv. Biol. 36, e13942 (2022).

    Google Scholar 

  67. Lalechère, E., Marrec, R. & Lenoir, J. A non-equilibrium species distribution model reveals unprecedented depth of time lag responses to past environmental change trajectories. Ecol. Lett. 28, e70040 (2025).

    Google Scholar 

  68. Lowe, E. B., Iuliano, B., Gratton, C. & Ives, A. R. ‘Scalescape’: an R package for estimating distance-weighted landscape effects on an environmental response. Landsc. Ecol. 37, 1771–1785 (2022).

    Google Scholar 

  69. Talluto, L., Boulangeat, I., Vissault, S., Thuiller, W. & Gravel, D. Extinction debt and colonization credit delay range shifts of eastern North American trees. Nat. Ecol. Evol. 1, 0182 (2017).

    Google Scholar 

  70. Magneville, C. et al. mFD: an R package to compute and illustrate the multiple facets of functional diversity. Ecography 2022, ecog.05904 (2022).

    Google Scholar 

  71. McTavish, E. J. et al. A complete and dynamic tree of birds. Proc. Natl Acad. Sci. USA 122, e2409658122 (2025).

    Google Scholar 

  72. Schliep, K., Potts, A. J., Morrison, D. A. & Grimm, G. W. Intertwining phylogenetic trees and networks. Methods Ecol. Evol. 8, 1212–1220 (2017).

    Google Scholar 

  73. Kembel, S. W. et al. Picante: R tools for integrating phylogenies and ecology. Bioinformatics 26, 1463–1464 (2010).

    Google Scholar 

  74. Oksanen, J. et al. vegan: community ecology package. R package version 2.6-4 https://doi.org/10.32614/CRAN.package.vegan (2022).

  75. Lai, J., Zou, Y., Zhang, J. & Peres-Neto, P. R. Generalizing hierarchical and variation partitioning in multiple regression and canonical analyses using the rdacca.hp R package. Methods Ecol. Evol. 13, 782–788 (2022).

    Google Scholar 

  76. Bürkner, P.-C. Bayesian item response modeling in R with brms and Stan. J. Stat. Softw. 100, 1–54 (2021).

    Google Scholar 

  77. Lu, X. et al. Multidecadal legacy of uneven urbanization on divergent prospects for bird biodiversity. figshare https://doi.org/10.6084/M9.FIGSHARE.29850275 (2025).

  78. National Platform for Common GeoSpatial Information Services (MapWorld); https://image.tianditu.gov.cn/multidate

Download references

Acknowledgements

We are grateful to numerous participants from various regions for their efforts in collecting and sharing species distribution records. We thank the biodiversity monitoring platforms for their sustained support in organizing species observation projects. We are grateful to R. Sun (Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences) and his team for generously providing the urban boundary data. We also appreciate C. Xu for her assistance with data compilation. This work was supported by the Key Project of the National Natural Science Foundation of China under grant number 52238003 to C. Du and Y.W.

Author information

Authors and Affiliations

  1. Department of Landscape Architecture, College of Architecture and Urban Planning, Tongji University, Shanghai, China

    Xinghao Lu, Yuwei Guo, Jiake Shen, Gaoyue Ling, Xinyu Tian, Yifei Jia & Yuncai Wang

  2. School of Geography, Faculty of Social Science, University of Nottingham, Nottingham, UK

    Jiaxiang Liu

  3. School of Ecological and Environmental Sciences, Institute of Eco-Chongming (IEC), East China Normal University, Shanghai, China

    Yue Che

  4. College of Landscape Architecture, Nanjing Forestry University, Nanjing, China

    Hui Wang

  5. Center of Ecological Planning and Environment Effects Research, Shanghai Joint Laboratory of Ecological Urban Design, Tongji University, Shanghai, China

    Yuncai Wang

Authors
  1. Xinghao Lu
    View author publications

    Search author on:PubMed Google Scholar

  2. Yuwei Guo
    View author publications

    Search author on:PubMed Google Scholar

  3. Jiake Shen
    View author publications

    Search author on:PubMed Google Scholar

  4. Jiaxiang Liu
    View author publications

    Search author on:PubMed Google Scholar

  5. Gaoyue Ling
    View author publications

    Search author on:PubMed Google Scholar

  6. Xinyu Tian
    View author publications

    Search author on:PubMed Google Scholar

  7. Yifei Jia
    View author publications

    Search author on:PubMed Google Scholar

  8. Yue Che
    View author publications

    Search author on:PubMed Google Scholar

  9. Hui Wang
    View author publications

    Search author on:PubMed Google Scholar

  10. Yuncai Wang
    View author publications

    Search author on:PubMed Google Scholar

Contributions

X.L., Y.C. and Y.W. jointly conceived this research. X.L., Y.G. and Y.J. developed the methodology. X.L., Y.G., G.L. and X.T. performed the data analyses and prepared the figures. X.L., Y.G., J.L. and Y.W. wrote the original draft. X.L., Y.W., J.S., Y.C. and H.W. reviewed and edited the draft. All authors contributed to the manuscript.

Corresponding authors

Correspondence to Yue Che or Yuncai Wang.

Ethics declarations

Competing interests

The authors declare no competing interests.

Peer review

Peer review information

Nature Cities thanks Fabio Angeoletto, Juan Hernández-Agüero and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Supplementary Information

Supplementary Notes 1 and 2, Figs. 1–19 and Tables 1–12.

Reporting Summary

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Lu, X., Guo, Y., Shen, J. et al. Multidecadal legacy of uneven urbanization on divergent prospects for bird biodiversity. Nat Cities 3, 176–188 (2026). https://doi.org/10.1038/s44284-025-00381-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • Version of record:

  • Issue date:

  • DOI: https://doi.org/10.1038/s44284-025-00381-0

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing