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:

Response and sensitivity of urban plants with different seed dispersal modes

Nature Cities volume 2, pages 28–37 (2025)Cite this article

Subjects

Abstract

Spontaneous plants, those not planted by people or remaining from before urbanization, are vital to urban biodiversity. Their distribution in urban systems is affected by seed dispersal mode and environmental factors such as natural dispersal limitation and habitat quality factors. We assessed four seed dispersal modes in 16 cities in Yunnan province, the most biodiverse province in China. Autochory, in which plants eject seeds or otherwise power their seeds’ dispersal, was the dominant seed dispersal mode of urban spontaneous plants in most cities (13 out of 16), whereas hydrochory, or passive seed dispersal by water, was the least frequent. Our research showed spontaneous plants in urban ecosystems adopt convergent strategies to address environmental stressors. The number of urban plants was significantly higher in colder and more-humid climates but decreased with increased dispersal limitations and reduced habitat quality. Sensitivities to these factors varied, with autochory especially sensitive to dispersal limitation and hydrochory sensitive to habitat quality and climate. Findings suggest improving habitat quality and creating green corridors would enhance conservation efforts for urban biodiversity.

Access through your institution
Buy or subscribe

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

Access options

Access through your institution

Buy this article

  • Purchase on SpringerLink
  • Instant access to full article PDF
Buy now

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

Fig. 1: The conceptual framework of urban spontaneous plants with different seed dispersal modes and corresponding drivers of species richness.
Fig. 2: The sampling sites and patches in the 16 prefecture-level cities in Yunnan province, China.
Fig. 3: Sankey chart of species composition in 16 cities surveyed in Yunnan province, China.
Fig. 4: Contrast interactions estimate between different seed dispersal modes.
Fig. 5: Averaged models for each seed dispersal mode.

Similar content being viewed by others

Data availability

The data and codes that support the findings of this study are publicly available via figshare at https://doi.org/10.6084/m9.figshare.27292317.v1 (ref. 67). Original photographs, collection numbers and scanned images of the herbarium specimens created during our study (currently housed at Kunming Institute of Botany) can also be obtained from the corresponding author upon request.

Code availability

The code that supports the findings of this study is available via figshare at https://doi.org/10.6084/m9.figshare.27292317.v1 (ref. 67).

References

  1. Howe, H. F. & Smallwood, J. Ecology of seed dispersal. Annu. Rev. Ecol. Syst. 13, 201–228 (1982).

    Article  Google Scholar 

  2. Dhiman, S. (ed.) Sustainable Development and Environmental Stewardship: Global Initiatives Towards Engaged Sustainability (Springer, 2023).

  3. Niemelä, J., et al. Urban Ecology: Patterns, Processes, and Applications (OUP Oxford, 2011).

  4. Zhang, M. et al. How urban riparian corridors affect the diversity of spontaneous herbaceous plants as pollination and dispersal routes - a case of the Wenyu River- North Canal in Beijing, China. Ecol. Indic. 146, 109869 (2023).

    Article  Google Scholar 

  5. Garrard, G. E., McCarthy, M. A., Vesk, P. A., Radford, J. Q. & Bennett, A. F. A predictive model of avian natal dispersal distance provides prior information for investigating response to landscape change. J. Anim. Ecol. 81, 14–23 (2012).

    Article  Google Scholar 

  6. Damschen, E. I. et al. How fragmentation and corridors affect wind dynamics and seed dispersal in open habitats. Proc. Natl Acad. Sci. 111, 3484–3489 (2014).

    Article  Google Scholar 

  7. Niu, H. et al. Regeneration of urban forests as influenced by fragmentation, seed dispersal mode and the legacy effect of reforestation interventions. Landsc. Urban Plan. 233, 104712 (2023).

    Article  Google Scholar 

  8. Soomers, H. et al. Wind and water dispersal of wetland plants across fragmented landscapes. Ecosystems 16, 434–451 (2013).

    Article  Google Scholar 

  9. Farwig, N., Schabo, D. G. & Albrecht, J. Trait‐associated loss of frugivores in fragmented forest does not affect seed removal rates. J. Ecol. 105, 20–28 (2017).

    Article  Google Scholar 

  10. Niu, H. et al. Granivorous rodent loss poses greater threats to oak trees with large acorns than those with small ones in urban forests. Urban For. Urban Green. 62, 127185 (2021).

    Article  Google Scholar 

  11. Bowler, D. E. & Benton, T. G. Causes and consequences of animal dispersal strategies: relating individual behaviour to spatial dynamics. Biol. Rev. Camb. Philos. Soc. 80, 205–225 (2005).

    Article  Google Scholar 

  12. Gorton, A. J. & Shaw, A. K. Using theoretical models to explore dispersal variation and fragmentation in urban environments. Popul. Ecol. 65, 17–24 (2023).

    Article  Google Scholar 

  13. Piano, E., Bonte, D., De Meester, L. & Hendrickx, F. Dispersal capacity underlies scale‐dependent changes in species richness patterns under human disturbance. Ecology 104, e3946 (2023).

    Article  Google Scholar 

  14. Arrhenius, O. Species and area. J. Ecol. 9, 95–99 (1921).

    Article  Google Scholar 

  15. de Candolle, A. Géographie Botanique Raisonnée ou Exposition des faits Principaux et des lois Concernant la Distribution Géographique des Plantes de l'époque Actuelle, Vol. 2 (V. Masson, 1855).

  16. MacArthur, R. H. & Wilson, E. O. The Theory of Island Biogeography (Princeton University Press, 1967).

  17. Hanski, I. & Gilpin, M. Metapopulation dynamics: brief history and conceptual domain. Biol. J. Linn. Soc. 42, 3–16 (1991).

    Article  Google Scholar 

  18. McDonnell, M. J. & Pickett, S. T. Ecosystem structure and function along urban–rural gradients: an unexploited opportunity for ecology. Ecology 71, 1232–1237 (1990).

    Article  Google Scholar 

  19. Laurance, W. F. Theory meets reality: how habitat fragmentation research has transcended island biogeographic theory. Biol. Conserv. 141, 1731–1744 (2008).

    Article  Google Scholar 

  20. Essl, F. et al. Socioeconomic legacy yields an invasion debt. Proc. Natl Acad. Sci. USA 108, 203–207 (2011).

    Article  Google Scholar 

  21. Hahs, A. K. & McDonnell, M. J. Extinction debt of cities and ways to minimise their realisation: a focus on Melbourne. Ecolog. Manag. Restor. 15, 102–110 (2014).

    Article  Google Scholar 

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

    Article  Google Scholar 

  23. Gao, Z. et al. Beta diversity of urban spontaneous plants and its drivers in 9 major cities of Yunnan province, China. Landsc. Urban Plan. 234, 104741 (2023).

    Article  Google Scholar 

  24. Di Musciano, M. et al. Elevational patterns of plant dispersal ability in Southern Europe. Plant Biosyst 157, 71–79 (2023).

    Article  Google Scholar 

  25. Prach, K. et al. The role of spontaneous vegetation succession in ecosystem restoration: a perspective. Appl. Veg. Sci. 4, 111–114 (2001).

    Article  Google Scholar 

  26. Qian, S. et al. Urban growth and topographical factors shape patterns of spontaneous plant community diversity in a mountainous city in southwest China. Urban For. Urban Green. 55, 126814 (2020).

    Article  Google Scholar 

  27. Hu, S. et al. Characterizing composition profile and diversity patterns of spontaneous urban plants across China’s major cities. J. Environ. Manage. 317, 115445 (2022).

    Article  Google Scholar 

  28. Huang, L. et al. Masonry walls as sieve of urban plant assemblages and refugia of native species in Chongqing, China. Landsc. Urban Plan. 191, 103620 (2019).

    Article  Google Scholar 

  29. Chang, M. et al. Land-use diversity can better predict urban spontaneous plant richness than impervious surface coverage at finer spatial scales. J. Environ. Manage. 323, 116205 (2022).

    Article  Google Scholar 

  30. Cote, J. et al. Evolution of dispersal strategies and dispersal syndromes in fragmented landscapes. Ecography 40, 56–73 (2017).

    Article  Google Scholar 

  31. Matthies, S. A., Rüter, S., Prasse, R. & Schaarschmidt, F. Factors driving the vascular plant species richness in urban green spaces: using a multivariable approach. Landsc. Urban Plan. 134, 177–187 (2015).

    Article  Google Scholar 

  32. van der Pijl, L. Principles of Dispersal in Higher Plants (Springer, 1982).

  33. Ceplová, N., Kalusová, V. & Lososová, Z. Effects of settlement size, urban heat island and habitat type on urban plant biodiversity. Landsc. Urban Plan. 159, 15–22 (2017).

    Article  Google Scholar 

  34. Cruz, J. C., Ramos, J. A., Da Silva, L. P., Tenreiro, P. Q. & Heleno, R. H. Seed dispersal networks in an urban novel ecosystem. Eur. J. For. Res. 132, 887–897 (2013).

    Article  Google Scholar 

  35. Wilson, M. C. et al. Assessing habitat fragmentation’s hierarchical effects on species diversity at multiple scales: the case of Thousand Island Lake, China. Landsc. Ecol. 35, 501–512 (2020).

    Article  Google Scholar 

  36. Lososová, Z. et al. Seed dispersal distance classes and dispersal modes for the European flora. Glob. Ecol. Biogeogr. 32, 1485–1494 (2023).

    Article  Google Scholar 

  37. García-Palacios, P., Gross, N., Gaitán, J. & Maestre, F. T. Climate mediates the biodiversity–ecosystem stability relationship globally. Proc. Natl Acad. Sci. USA 115, 8400–8405 (2018).

    Article  Google Scholar 

  38. Wheeler, M. M. et al. Continental-scale homogenization of residential lawn plant communities. Landsc. Urban Plan. 165, 54–63 (2017).

    Article  Google Scholar 

  39. Vakhlamova, T., Wagner, V., Padullés Cubino, J., Chytrý, M. & Lososová, Z. Urban plant diversity in Kazakhstan: effects of habitat type, city size and macroclimate. Appl. Veg. Sci. 25, e12679 (2022).

    Article  Google Scholar 

  40. Ouyang, Y. et al. Homogenization of trees in urban green spaces along the moisture gradient in China. Urban For. Urban Green. 83, 127892 (2023).

    Article  Google Scholar 

  41. Padullés Cubino, J. et al. Drivers of plant species richness and phylogenetic composition in urban yards at the continental scale. Landsc. Ecol. 34, 63–77 (2019).

    Article  Google Scholar 

  42. Aronson, M. F. J. et al. A global analysis of the impacts of urbanization on bird and plant diversity reveals key anthropogenic drivers. Proc. R. Soc. B 281, 20133330 (2014).

    Article  Google Scholar 

  43. Gao, Z. et al. Drivers of spontaneous plant richness patterns in urban green space within a biodiversity hotspot. Urban For. Urban Green. 61, 127098 (2021).

    Article  Google Scholar 

  44. Kalusová, V. et al. Similar responses of native and alien floras in European cities to climate. J. Biogeogr. 46, 1406–1418 (2019).

    Article  Google Scholar 

  45. Clark, J. S. Statistical Computation for Environmental Sciences in R: An Introduction (Princeton University Press, 2007).

  46. Yunnan Yearbook Editorial Committee (ed.) Yunnan Yearbook (Yunnan Yearbook Editorial Press, 2019).

  47. Zomer, R. J., Xu, J., Wang, M., Trabucco, A. & Li, Z. Projected impact of climate change on the effectiveness of the existing protected area network for biodiversity conservation within Yunnan Province, China. Biol. Conserv. 184, 335–345 (2015).

    Article  Google Scholar 

  48. Zhu, H. & Tan, Y. Flora and vegetation of Yunnan, Southwestern China: diversity, origin and evolution. Diversity 14, 340–358 (2022).

    Article  Google Scholar 

  49. Myers, N., Mittermeier, R. A., Mittermeier, C. G., Da Fonseca, G. A. & Kent, J. Biodiversity hotspots for conservation priorities. Nature 403, 853–858 (2000).

    Article  Google Scholar 

  50. Grande, T. O., Aguiar, L. M. & Machado, R. B. Heating a biodiversity hotspot: connectivity is more important than remaining habitat. Landsc. Ecol. 35, 639–657 (2020).

    Article  Google Scholar 

  51. Qian, L., Chen, J., Deng, T. & Sun, H. Plant diversity in Yunnan: current status and future directions. Plant Divers 42, 281–291 (2020).

    Article  Google Scholar 

  52. Guo, Z. & Zheng, J. Predicting modes of seed dispersal using plant life history traits. Biodivers. Sci. 25, 966–971 (2017).

    Article  Google Scholar 

  53. Yu, X., Li, Y. & Yang, G. Fruit types and seed dispersal modes of plants in different communities in Shilin Geopark, Yunnan, China. Chin. J. Plant Ecol. 42, 663–671 (2018).

    Article  Google Scholar 

  54. ArcGIS 10.3.1 (Esri, 2015).

  55. Zhong, X. Y., Yan, Q. W. & Li, G. E. Development of time series of nighttime light dataset of China (2000–2020). J. Glob. Change Data Discov. 3, 416–424 (2022).

    Google Scholar 

  56. Zhao, N., Liu, Y., Cao, G., Samson, E. L. & Zhang, J. Forecasting China’s GDP at the pixel level using nighttime lights time series and population images. GISci. Remote Sens. 54, 407–425 (2017).

    Article  Google Scholar 

  57. 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).

    Article  Google Scholar 

  58. Bates, D. et al. lme4: mixed-effects models in R. R package version 1.1-35.1. GitHub https://github.com/lme4/lme4/ (2009).

  59. Menard, S. Applied Logistic Regression Analysis (Sage, 2002).

  60. Vittinghoff, E., Glidden, D. V., Shiboski, S. C. & McCulloch, C. E. Regression Methods in Biostatistics: Linear, Logistic, Survival, and Repeated Measures Models (Springer, 2012).

  61. James, G., Witten, D., Hastie, T. & Tibshirani, R. An Introduction to Statistical Learning: with Applications in R (Springer, 2013).

  62. Hartig, F. DHARMa: residual diagnostics for hierarchical (multi-level/mixed) regression models. R package version 0.4.6. GitHub http://florianhartig.github.io/DHARMa/ (2020).

  63. Lenth, R., Singmann, H., Love, J., Buerkner, P. & Herve, M. Package ‘emmeans’. R package version 1.10.1. GitHub https://rvlenth.github.io/emmeans/ (2019).

  64. Anderson, D. & Burnham, K. Model Selection and Multimodel Inference (Springer, 2004).

  65. Gross, N. et al. Functional trait diversity maximizes ecosystem multifunctionality. Nat. Ecol. Evol. 1, 0132 (2017).

    Article  Google Scholar 

  66. R Core Team. R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2023).

  67. Gao, Z. Response and sensitivity of urban plants with different seed dispersal modes. figshare https://doi.org/10.6084/m9.figshare.27292317.v1 (2024).

Download references

Acknowledgements

We thank X. Yu from Qiannan Normal University for Nationalities for helping with the species identification. This research was funded by Major Program for Basic Research Project of Yunnan Province (L.D., 202101BC070002), the Ministry of Science and Technology of China (L.D., 2015FY210200), ECNU Academic Innovation Promotion Program for Excellent Doctoral Students (Z.G., YBNLTS2019), and the National Key Research and Development Program of China (Y.P., 2023YFF1305800). Y.P. acknowledges the funds from the Chinese Academy of Sciences (E429S10101) and the Innovation Team Project of Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences (2023CXTD03).

Author information

Author notes

  1. These authors contributed equally: Zhiwen Gao, Yingji Pan.

Authors and Affiliations

  1. Global Institute for Urban and Regional Sustainability, Tiantong National Forest Ecosystem Observation and Research Station, School of Ecological and Environmental Sciences, East China Normal University, Shanghai, China

    Zhiwen Gao, Kun Song & Yanyi Yang

  2. Institute of Eco-Chongming, Shanghai, China

    Zhiwen Gao & Kun Song

  3. Key Laboratory of Wetland Ecology and Environment, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun, China

    Yingji Pan

  4. State Key Laboratory of Black Soils Conservation and Utilization, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun, China

    Yingji Pan

  5. School of Landscape Architecture, Northeast Forestry University, Harbin, China

    Mingming Zhuge & Yuandong Hu

  6. College of Agriculture and Life Sciences, Kunming University, Kunming, China

    Tian Wu & Tiyuan Xia

  7. Institute of Science and Engineering of Ecology in Arid and Semi-arid Areas, Xi’an University of Architecture and Technology, Xi’an, China

    Yuandong Hu & Liangjun Da

  8. Nelson Marlborough Institute of Technology, Nelson, New Zealand

    Ellen Cieraad

  9. Institute of Environmental Sciences, Leiden University, Leiden, the Netherlands

    Ellen Cieraad

Authors
  1. Zhiwen Gao
    View author publications

    Search author on:PubMed Google Scholar

  2. Yingji Pan
    View author publications

    Search author on:PubMed Google Scholar

  3. Kun Song
    View author publications

    Search author on:PubMed Google Scholar

  4. Yanyi Yang
    View author publications

    Search author on:PubMed Google Scholar

  5. Mingming Zhuge
    View author publications

    Search author on:PubMed Google Scholar

  6. Tian Wu
    View author publications

    Search author on:PubMed Google Scholar

  7. Tiyuan Xia
    View author publications

    Search author on:PubMed Google Scholar

  8. Yuandong Hu
    View author publications

    Search author on:PubMed Google Scholar

  9. Liangjun Da
    View author publications

    Search author on:PubMed Google Scholar

  10. Ellen Cieraad
    View author publications

    Search author on:PubMed Google Scholar

Contributions

Z.G.: field survey, data collection, analysis, interpretation and drafting the manuscript; Y.Y., T.W., M.Z., T.X., Y.H.: field survey, collecting data and revising the manuscript; E.C., K.S. and Y.P.: data analysis, interpretation of data, conception and revising the manuscript critically; K.S. and L.D.: funding, conception, revising the manuscript and final approval of the manuscript. All authors have read and agreed to the published version of the manuscript.

Corresponding author

Correspondence to Kun Song.

Ethics declarations

Competing interests

The authors declare no competing interests.

Peer review

Peer review information

Nature Cities thanks Ádám Lovas-Kiss, Rafael Zenni 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 Tables 1 and 2.

Reporting Summary

Supplementary Code 1

Supplementary code.

Supplementary Data 1

Data for Sankey diagram.

Supplementary Data 2

Data for interaction model.

Supplementary Data 3

Data for separate models.

Supplementary Data 4

Data of species list.

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

Gao, Z., Pan, Y., Song, K. et al. Response and sensitivity of urban plants with different seed dispersal modes. Nat Cities 2, 28–37 (2025). https://doi.org/10.1038/s44284-024-00169-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue date:

  • DOI: https://doi.org/10.1038/s44284-024-00169-8

This article is cited by

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