Abstract
Urban plant assemblages comprise mixtures of native and non-native species distributed across a variety of urban green space (UGS) types, yet we lack an integrated understanding of how plant diversity and composition varies across UGS that differ in the degree to which communities arise through self-assembly versus human facilitation. Here, we address the gap based on a comprehensive dataset of 180 plant communities sampled across three Swiss cities (Zurich, Geneva, and Lugano) and five UGS types— allotments, private gardens, parks, residential estates, and ruderal areas— to quantify α- and β-diversity patterns and their underlying social-ecological drivers. To identify drivers of plant diversity and composition, we used landscape predictors, such as climatic conditions and built environment, and local predictors, such as maintenance and conservation management performed by UGS managers, and habitat design. We found that plant community composition does partially differentiate among UGS types. While private gardens, parks, and real estate showed greater overlap, ruderal sites and allotments exhibited distinct species communities. Yet, these two UGS types are also the ones most threatened by urban densification, highlighting potential conflicts between urban densification and biodiversity conservation. Moreover, although the non-native plant richness increased along a human investment gradient, native plant richness remained stable. Lastly, by jointly analyzing alpha and beta diversity, our study shows that urban social-ecological conditions can simultaneously constrain local species richness, while promoting compositional differentiation among sites. By integrating ecological and social dimensions, this study provides a unique greenspace-wide perspective that can inform biodiversity-oriented urban planning and management.
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Urban plant assemblages comprise mixtures of native and non-native species distributed across a variety of urban green space (UGS) types, yet we lack an integrated understanding of how plant diversity and composition varies across UGS that differ in the degree to which communities arise through self-assembly versus human facilitation. Here, we address the gap based on a comprehensive dataset of 180 plant communities sampled across three Swiss cities (Zurich, Geneva, and Lugano) and five UGS types— allotments, private gardens, parks, residential estates, and ruderal areas— to quantify α- and β-diversity patterns and their underlying social-ecological drivers. To identify drivers of plant diversity and composition, we used landscape predictors, such as climatic conditions and built environment, and local predictors, such as maintenance and conservation management performed by UGS managers, and habitat design. We found that plant community composition does partially differentiate among UGS types. While private gardens, parks, and real estate showed greater overlap, ruderal sites and allotments exhibited distinct species communities. Yet, these two UGS types are also the ones most threatened by urban densification, highlighting potential conflicts between urban densification and biodiversity conservation. Moreover, although the non-native plant richness increased along a human investment gradient, native plant richness remained stable. Lastly, by jointly analyzing alpha and beta diversity, our study shows that urban social-ecological conditions can simultaneously constrain local species richness, while promoting compositional differentiation among sites. By integrating ecological and social dimensions, this study provides a unique greenspace-wide perspective that can inform biodiversity-oriented urban planning and management.
https://doi.org/10.32942/X2CQ21
Life Sciences
Urban biodiversity, Native and non-native plants, Meta community, Alpha and Beta diversity, Gardening, Urban green spaces, Plant assemblages, Urban vegetation
Published: 2026-04-24 10:06
Last Updated: 2026-04-24 10:06
CC BY Attribution 4.0 International
Conflict of interest statement:
None
Data and Code Availability Statement:
Open data/code are not available.
Language:
English
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