Divergent responses of plant growth forms to climate and urban expansion

Divergent responses of plant growth forms to climate and urban expansion | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Divergent responses of plant growth forms to climate and urban expansion Zhiwen Gao, Ellen Cieraad, Yingji Pan, Yanyi Yang, Xinyi Luo, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7058899/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted You are reading this latest preprint version Abstract Urbanization and climate change are rapidly altering large-scale plant distributions and local community compositions, profoundly impacting ecosystem functions and services. However, it remains unclear how life form compositions, one of the key functional biodiversity components, respond jointly to urbanization and climate gradients. Here we investigated the life form compositions of 2,864 naturally regenerated spontaneous plant species across 129 cities in Yunnan province of China, a global biodiversity hotspot with diverse environmental condition. Our results showed perennial herbs (45.0%) predominated in urban ecosystem, followed by annual herbs (29.2%) and woody plants (25.8%). Bayesian hierarchical models revealed that as urban expansion, the proportions of annual herbs rise, while the proportions of both perennial herbs and woody plants decline, indicating urban expansion favors short-lived plants but is detrimental to long-lived plants. Increasing mean annual temperature with a decline in perennial herbs and a concurrent increase in woody plants, suggesting divergent adaptive responses to thermal stress. Our results highlight the complex, divergent responses of plant life forms to urbanization and climate change, emphasizing the need for targeted conservation strategies that consider both the resilience of short-lived species and the vulnerability of long-lived plants. Biological sciences/Ecology/Urban ecology Biological sciences/Ecology/Biodiversity Biological sciences/Ecology/Ecosystem ecology Biodiversity hotspots plant life forms urban spontaneous plants urban ecosystems Figures Figure 1 Figure 2 Figure 3 Introduction Urbanization has far-reaching consequences for biodiversity and ecosystem functioning as a result of land use change, habitat fragmentation and alterations in hydrothermal conditions 1 . As urban landscapes continue to expand, the ways in which they influence ecological processes become increasingly complex and multifaceted. Traditionally, urban areas are often perceived as biological deserts devoid of biodiversity 2 , 3 . However, this perception neglects the complexity of urban ecosystems and their significant role in supporting diverse forms of life. In fact, urban areas can be biodiversity hotspots 4 , 5 and serve as vital refuges for endemic and endangered species through providing essential resources such as shelter for their colonization and settlement in to other areas 3 , 6 , 7 . Investigating how urbanization shifts distribution patterns and functional structure of spontaneous plant communities is crucial for understanding the mechanisms that sustain biodiversity in human dominated ecosystems, and for optimizing urban planning and conservation efforts. Urban spontaneous plants comprise plants that have self-established without human intervention, yet are distinct from remaining natural vegetation 8 . The diversity patterns of spontaneous plants are influenced not only by natural factors but also by anthropogenic factors. Known for their rapid response to disturbances, spontaneous plants serve as valuable indicators of urbanization dynamics 9 – 11 . With the emerging concepts such as urban near-naturalization, rewilding, and nature-based solutions, spontaneous plants are increasingly being seen as having great potential as contributors to future urban greening 12 . Life form represents a key functional strategy of plants in response to their environment. Different life forms (e.g., woody vs herbaceous species) underlie distinct functional traits, including life span, morphology, and physiology, which influences their adaptation to environmental conditions 13 – 15 . Examining the distributional patterns of plant life forms provides important insights into ecological constraints acting on biodiversity 16 . For example, numerous studies have found that the proportion of woody plants decreases gradually with increasing latitude 13 , 16 – 19 . Herbaceous plants tend to be less sensitive to lower temperature, precipitation and anthropogenic disturbance than woody plants 20 – 23 . A pronounced divergence in environmental adaptability of different life spans of the herbaceous life form is also apparent: compared to perennials, annuals exhibit superior flexibility to xeric and warm conditions and higher anthropogenic disturbance, which contributes to their increased probability to become invasive species when introduced to new locations 14 , 24 , 25 . The correlations between climatic factors (in particular temperature and precipitation) and the abundance of different life forms are often so strong that plant growth form data have been used to complement the delineation of the bioregions in Africa 26 and the New World 15 . Despite these advancements, the diversity patterns and of plant life forms and their driving factors along urbanization gradients at the regional scale, beyond the influence of natural environmental factors, remain unclear. Understanding these variations and their ecological drivers could improve predictions of terrestrial ecosystem changes under future climate scenarios 16 , 27 – 29 . Here, we surveyed spontaneous plants inhabiting 129 cities covering a wide range of macroclimatic conditions and urbanization intensities in Yunnan province, the most biodiverse province in China and one of the world’s biodiversity hotspots 30 (Fig. 1 ). Our study aims to reveal the distribution patterns of different life-forms of spontaneous plants along the urbanization and climate gradient by testing two hypotheses: 1) In highly urbanized areas, the proportion of shorter-lived spontaneous plant species (such as annuals) will increase due to their greater adaptability to frequent anthropogenic disturbances, resulting in a relatively lower prevalence of perennials and woody plants, which are more dominant in less urbanized zones; 2) In cities experiencing more extreme hydrothermal conditions, such as higher or lower temperatures and drought, the proportion of shorter-lived spontaneous plant species will increase, while the prevalence of perennials and woody plants will decrease, as these life-forms are generally more dominant in cities with milder and more stable climates. Results Across the 129 cities surveyed in Yunnan province, we recorded 2,864 spontaneous plant species of 1,261 genera from 222 families, including 477 annual herbaceous species, 1,222 perennial herbs, and 1,165 woody species. Perennial herbs dominated urban plant communities (mean proportion = 0.45), followed by annual herbs (mean = 0.29), and woody plants (mean = 0.26). Pairwise comparisons revealed statistically significant differences among all life form pairs (all comparisons p < 0.001) ( Data 1 and Fig. 1 ). The polynomial regression results revealed the proportions of life-forms fluctuate across both latitude and longitude (Fig. 1 B, C). The proportion of perennial herbs had a significant increased trend with latitude ( p < 0.001), while annual herbs and woody plants showed no significant trend with latitude ( p = 0.156 and p = 0.169, respectively), all three life-forms exhibited marked variation near 25° N. Conversely, the proportions of annual herbs showed decrease trend and woody plants showed increase trend with longitude ( p < 0.001 and p = 0.003), whereas perennial herbs showed no significant trend with longitude ( p = 0.516). (Fig. 1 B and C ). The optimal Bayesians regression analysis included mean annual temperature (MAT), city size, real gross domestic product per capita (RGDP), and the proportion of sealed surface in each city (Sealed. city ) as predictors (Fig. 2 ). Consistent with our first hypothesis, we found that city size had a significant positive effect on the proportion of annual herbs ( β = 0.34, 95% CI: 0.18 to 0.50), but negative effect on the proportion of both perennial herbs ( β = -0.04, 95% CI: -0.07 to -0.01) and woody plants ( β = -0.3, 95% CI: -0.41 to -0.19). In relation to our second hypothesis, we found that higher MAT was significantly correlated with a lower proportion of perennial herbs ( β = -0.07, 95% CI: -0.1 to -0.05). In contrast, MAT was positively associated with the proportion of woody plants ( β = 0.09, 95% CI: 0.01 to 0.17), suggesting that warmer cities tend to support a higher relative abundance of woody life forms (Fig. 3 ). Discussion Traditionally perceived as biodiversity deserts, our study of spontaneous plant richness across 129 cities in Yunnan province supports the notion that urban ecosystems are important reservoirs of biodiversity 4 , 7 . Our study found that, despite urban areas encompassing less than 1% of the total area, spontaneous plants accounted for more than 15% (n = 2,864) of the approximately 19,000 plant species found in Yunnan Province 31 . Spontaneous plants, in particular, play a vital role in maintaining urban biodiversity by providing habitats for pollinators and other wildlife, enhancing ecological resilience 32 , 33 . Protecting and managing these plants in urban areas can contribute to broader biodiversity conservation goals, offering a unique opportunity to integrate ecological and societal benefits in rapidly urbanizing regions 34 – 36 . Our findings reveal striking deviations in life form proportions compared to global and regional baselines. The mean proportion of annual herbs across the cities in our study of 29.2% far exceeds the global average of 6% reported by Poppenwimer et al. (2023), and even the maximum values observed in desert ecosystems (14%) 25 . Additionally, woody plants in our study (mean 25.8% across cities) showed a comparatively lower proportion than that at global scales (≥ 42.7%) 13,37 , China (51.6%) 19 and Yunnan natural ecosystems (> 40.0%) 38 . Therefore, compared to natural ecosystems, we may conclude that short-lived species are significantly more prevalent, while long-lived species are proportionally reduced in urban ecosystems. Latitudinal and longitudinal gradients in plant life form composition encompass composite geographic gradients, capturing not only temperature (particularly latitude) but also other covarying environmental and socioeconomic factors, such as precipitation, urban form, and historical land use. Our Bayesian hierarchical model results provide further insights into the urbanization drivers shaping the composition of urban spontaneous vegetation. Compared to natural ecosystems, we hypothesized that the frequent anthropogenic disturbances in urban areas make it easier for some short-lived plants to colonize urban environments, while long-lived plants are more prone to local or regional extinction under frequent disturbances 39 , 40 . Consistent with our first hypothesis, city size was found to have a significant positive effect on the proportion of annual herbs and a negative effect on the proportions of both perennial herbs and woody plants. This suggests that urban expansion may directly promote the persistence of short-lived plants while constrain that of long-lived plant forms. Larger cities tend to have higher levels of land sealing, fragmentation of green space, more intensive anthropogenic disturbance, and longer process of urbanization 41 , 42 , all of which may contribute to reduced habitat suitability for perennials and woody species. This pattern aligns with the notion that urban environments act as powerful ecological filters, favoring opportunistic annual herbs with rapid life cycles while suppressing species with long juvenile phases and high resource demands 43 . As highlighted by Uchida et al. (2021) 44 , urbanization not only alters species richness but also drives functional homogenization, with expanding cities increasingly dominated by disturbance-tolerant herbaceous plants. Compare to annual plant forms, perennials and woody species typically require stable habitats, deeper soils, and longer establishment periods, which are increasingly rare in highly urbanized environments 1 , 45 . The much stronger effect size for woody plants ( β = -0.30) compared to perennials ( β = -0.04) also reflects the greater sensitivity of trees and shrubs to long-term land-use change and habitat degradation. Therefore, urban ecosystems may be converging, under the influence of urban expansion and disturbance, towards a functional homogenization characterized by the dominance of opportunistic herbaceous plants with short life cycles 46 . Consequently, effective urban biodiversity management should consider scale-dependent strategies, such as prioritizing land-sparing approaches and innovative green infrastructure in large cities, to mitigate the loss of perennial and woody species and preserve ecosystem multifunctionality in the face of ongoing urban expansion 44 . The increase of annual herbs in urban ecosystems is not only a reflection of their rapid colonization of disturbed habitats, but also a result of the increased presence of invasive species. In our study, 57% (86 out of 151) of the identified invasive plants were annuals. Many annual plants, especially those that thrive in urbanized environments, belong to invasive species that are adept at exploiting the altered conditions created by urbanization 47 . These species often outcompete native plants due to their fast reproductive cycles, adaptability to disturbed habitats, and lack of natural predators or competitors 48 . As urban areas expand, the prevalence of these invasive annuals is likely to increase, further altering plant communities and threatening local biodiversity. Given these trends, we propose that more research should be conducted to better understand the mechanisms driving the success of invasive annuals in urban environments and to develop effective management strategies to mitigate their impacts. Climate conditions are the primary environmental filter for plants and are closely related to the life form compositions of urban spontaneous plants. The high explanatory power of MAT in shaping the diversity of spontaneous plant life forms, aligns with the notion that temperature is the primary driver of plant distribution 49 . Notably, perennial herbs and woody plants display contrasting responses to climatic gradients. Numerous studies have confirmed that the proportion of woody plants increases significantly with rising temperatures 13 , 49 . Warmer conditions often extend the growing season and reduce the frequency of frost events, which benefits woody species by allowing greater investment in long-lived structures and deeper root systems 50 , 51 . In temperate forests and grasslands, experimental warming treatments have consistently led to an increase in woody plant recruitment and a decline in herbaceous cover 52 . Meta-analyses across biomes indicate that woody plants are generally more resilient to temperature increases due to their physiological and morphological adaptations, such as thicker bark, higher wood density, and deeper roots 53 . Conversely, perennial herbs, especially in warmer climates, may face increased evapotranspiration and water stress, which can limit their persistence and competitiveness 54 . Elevated temperatures can accelerate soil moisture loss and increase the frequency and intensity of drought events, further exacerbating the challenges for perennial herbs 55 . These findings suggest that the observed correlations in our study are part of a broader ecological phenomenon, where rising temperatures shift plant community composition toward woody dominance at the expense of herbaceous perennials. Further research should focus on disentangling the roles of temperature, water availability, disturbance, and biotic interactions in shaping these patterns across different ecological contexts. Overall, our study highlights the critical role of spontaneous plants in urban ecosystems, underscoring the potential of cities as biodiversity reservoirs. It reveals that urbanization and climate jointly shape the composition of spontaneous plant communities, driving a functional shift towards short-lived, disturbance-adapted life forms. As cities expand, the proportion of short-lived plants may increase, leading to a shift in urban ecosystems towards a dominance of annual herbs, while perennial herbs and woody species, become increasingly rare. The decline of perennial and woody life forms in larger cities highlights the need for integrative urban planning that supports a range of plant strategies and balances urban development with biodiversity conservation. Furthermore, the potential impacts of future climate warming on different plant life forms of spontaneous plants should also raise further concern. Given their substantial contribution to plant species diversity and their role in providing critical habitats for wildlife, including pollinators and birds 56 , 57 , the ongoing loss of perennial herbs and woody plants in urban should be curbed and reversed. Promoting their persistence will help cities move beyond simply accommodating biodiversity toward actively sustaining it in the face of accelerating environmental change. Materials and Methods Study area Our study was carried out in Yunnan province, China (N 21°8'32'' - N 29°15'8'', E 97°31'39'' - E 106°11'47''), a biodiversity hotspots with complex topography with significant variation in altitude (77 m − 6740 m), temperature (average annual temperature 5.0℃ − 23.8℃) and precipitation (total annual precipitation 580 mm − 2700 mm) across its territory 58 . Despite occupying only 4.1% of the total territory area of the country, the diverse natural environmental conditions make the province accommodate more than 51.6% (≥ 18,000 species) of all higher plants recorded in China 30 , 31 . Additionally, the distinct urbanization processes and diverse environmental gradients of between cities in Yunnan province present an ideal place to study urban ecology. Data collection Field surveys of spontaneous plant species were conducted during the growing season (April-October) in 2017–2023, following the sampling protocol described in detail in our previous studies 32 , 33 , 59 . In short, spontaneous plants were sampled across all 129 county-level cities, which are widely distributed along natural and urbanization gradients. In each city, sampling sites with a 500 m radius were established at about 2 km intervals from the city center to the city outskirts. Within each sampling site, at least three accessible green patches were randomly selected for a species richness survey. The life forms of species were categorized into three groups: woody plants, annual herbs and perennial herbs, according to published literature 25 and the Flora of China ( http://www.iplant.cn/ ). The proportions of the three life forms spontaneous plants were treated as composite dependent variables in this study. We examined ten explanatory variables potentially associated with the long-term persistence of trees, representing two major categories: climate factors and anthropogenic factors (see details in Table 1 ). Climate factors including mean annual temperature (MAT), Mean annual total precipitation (MAP), Evaporation and relative humidity (RH). Anthropogenic factors primarily reflect the intensity and rate of urbanization across different cities. These include factors such as city size, the human footprint (HFP), night light intensity in each site (Light. site ), real gross domestic product per capita (RGDP), the proportion of sealed surface in each city (Sealed. city ), and sealed surface expansion rate of each city from 1990 to 2019 (i.e., urbanization rate, UR. city ). As urban areas rapidly expand (i.e., city size increasing), human activity and habitat disturbance intensify, often leading to greater environmental pressures and altering the balance of local ecosystems 33 . HFP is used to monitor changing anthropogenic pressures on a yearly cadence based on land cover change, population density, nighttime lights, roads, railways, and navigable rivers 60 . Light. site and RGDP reflect the level of human development and economic activity within a city, which in turn influences the intensity of urbanization and its effects on plant colonization 61 . Sealed. city directly impacts the availability of habitats for plant species and their ability to establish in the city environment 62 . UR. city representing the historical dynamics of urban expansion, captures how the rate of urbanization has evolved over time and the cumulative effect on species' dispersal and survival across urban landscapes 32 . Table 1 The description of explanatory variables in Bayesian Dirichlet regression models. Explanatory variables Description Source Natural factors MAT Mean annual temperature National Earth System Science Data Center (mean value of 1960–2021, resolution = 1 km, www.geodata.cn ) MAP Mean annual total precipitation Evaporation - RH Relative humidity Anthropogenic factors City size - City size was calculated by moving windows (1 km × 1 km, threshold = 50%, 2020) HFP Human Footprint Global 100m Terrestrial Human Footprint, 2020 (HFP-100, resolution = 100 m, https://datadryad.org/stash/dataset/doi: 10.5061/dryad.ttdz08m1f ) 60 Light. site Night light intensity in each site resolution = 1 km 61 , 2020 RGDP Real gross domestic product per capita, \(\:RGDP=GDP/population\) Chinese population census yearbook 2020 Sealed. city The proportion of sealed surface in each city resolution = 30 m 63 , 2020 UR. city Sealed surface expansion rate of each city (i.e., urbanization rate) from 1990 to 2019 Data analysis To assess differences in proportional representation among plant life forms (annual herbs, perennial herbs, and woody plants), we conducted pairwise two-sided t-tests among the three life form types and reported exact p-values. We used the ggplot2 package to plot the trends of life form proportions along latitude and longitude gradients, and applied the geom_smooth function with the locally weighted regression (LOESS) method to fit smooth trend lines, thereby revealing the variation patterns of life form proportions along geographic gradients. To evaluate the relationship of environmental variables, while accounting for the interdependencies of the three compositional proportions (annual herbs, perennial herbs, and woody plants always sum to 100%), we employed Bayesian Dirichlet regression models (logit-link) using the brms package 64 , 65 . As predictor variables, we used all climate and anthropogenic factors described Table 1 . All continuous predictors were standardized (mean = 0, SD = 1). To comprehensively explore potential model structures, we generated all possible combinations of candidate predictors. Each model included a nested random effect structure (1|cityid/siteid) to account for the spatial hierarchy in the study design. All models were fitted in parallel using the cmdstanr backend, with 4 chains, 4000 iterations per chain (2000 warm-up), and 5 threads per chain. To ensure numerical stability, we set adapt delta = 0.99 and max treedepth = 15. Model performance was compared using leave-one-out cross-validation via the loo criterion 65 . Models with high collinearity (i.e., any predictor VIF ≥ 5, checked using check_collinearity from the performance package) were excluded, yielding 511 valid models from 1,023 models 66 – 68 . The model with the highest expected log predictive density was selected as the best-supported model and presented. We ran all analyses using the R Software 3.5.1 69 , and used ggplot2 and ggpubr packages 70 , 71 for visualizations. Declarations Data and code availability The data and code for the analysis will be made available once the manuscript is accepted. Acknowledgement This research was funded by Major Program for Basic Research Project of Yunnan Province (202101BC070002), the Ministry of Science and Technology of China (2015FY210200), ECNU Academic Innovation Promotion Program for Excellent Doctoral Students (YBNLTS2019). Yingji Pan 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). Competing Interest Statement: The authors declare no conflict of interest. References Hou, Y., Li, J., Li, G. & Qi, W. Negative effects of urbanization on plants: A global meta‐analysis. Ecol. Evol. 13 , 1-9 (2023). Hall, D. M. et al. The city as a refuge for insect pollinators. Conserv. Biol. 31 , 24-29 (2017). Kantsa, A., Tscheulin, T., Junker, R. 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Yang, J. & Huang, X. The 30 m annual land cover dataset and its dynamics in China from 1990 to 2019. Earth System Science Data . 13 , 3907-3925 (2021). Douma, J. C. & Weedon, J. T. Analysing continuous proportions in ecology and evolution: A practical introduction to beta and Dirichlet regression. Methods Ecol. Evol. 10 , 1412-1430 (2019). Bürkner, P. brms: An R package for Bayesian multilevel models using Stan. J. Stat. Softw. 80 , 1-28 (2017). Gareth, J., Daniela, W., Trevor, H. & Robert, T. An introduction to statistical learning: with applications in R . (Spinger, 2013). Menard, S. Applied logistic regression analysis . (Sage, 2002). Vittinghoff, E., Glidden, D. V., Shiboski, S. C. & McCulloch, C. E. Regression methods in biostatistics: linear, logistic, survival, and repeated measures models., (2006). R Core Team. R version 3.5. 1.; 2015. Kassambara, A. ggpubr:'ggplot2'based publication ready plots. R Package Version , 2 (2018). Wickham, H. & Sievert, C. ggplot2: elegant graphics for data analysis , vol. 10. (springer New York, 2009). Additional Declarations There is NO Competing Interest. Supplementary Files suplymentaryinformation.docx Supplementary information Table S1 Model summary of the Bayesian Dirichlet regression models with life forms of spontaneous plant species. Table S2 Model compare of the top five Bayesian Dirichlet regression models with life forms of spontaneous plant species. Cite Share Download PDF Status: Under Review Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7058899","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":490549537,"identity":"4eb93b2c-e433-4202-8026-d9df00193245","order_by":0,"name":"Zhiwen Gao","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA50lEQVRIiWNgGAWjYNCCCmYkzgGitJwhWQtjGyla5GekX/zwcZ61nHwD88HPhW0Mcnw3Ehg/F+CzYEZOseTMbenGBgfYkqVntjEYS95IYJaegUcLs3ROgjTvtsOJGxh4zJh52xgSN9xIYGPmwaOFTTon+TfvnMP18xv4v4G01BPUwiOdfkyat+FwAsMBHjaQlgQDQlok5N+wWc44lm644TCbsTTPOQnDmWceNkvj0yLfc/zxjQ811vLy7c0PP/OU2cjzHU8++BmfFqDTDCA0JGokgJixAa8GBgb2BwQUjIJRMApGwYgHAGRORDAWS6+NAAAAAElFTkSuQmCC","orcid":"https://orcid.org/0000-0003-0800-5968","institution":"Yunnan Normal University","correspondingAuthor":true,"prefix":"","firstName":"Zhiwen","middleName":"","lastName":"Gao","suffix":""},{"id":490549538,"identity":"e2de76f7-4d62-4b11-9998-286ec5e170a1","order_by":1,"name":"Ellen Cieraad","email":"","orcid":"https://orcid.org/0000-0002-9813-9590","institution":"Nelson Marlborough Institute of Technology","correspondingAuthor":false,"prefix":"","firstName":"Ellen","middleName":"","lastName":"Cieraad","suffix":""},{"id":490549541,"identity":"9d23a443-280b-47ac-85fa-2703b1848003","order_by":2,"name":"Yingji Pan","email":"","orcid":"https://orcid.org/0000-0002-8203-3943","institution":"Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences","correspondingAuthor":false,"prefix":"","firstName":"Yingji","middleName":"","lastName":"Pan","suffix":""},{"id":490549542,"identity":"c8eb78d0-cb61-4252-857f-96c47a42607d","order_by":3,"name":"Yanyi Yang","email":"","orcid":"","institution":"East China Normal University","correspondingAuthor":false,"prefix":"","firstName":"Yanyi","middleName":"","lastName":"Yang","suffix":""},{"id":490549544,"identity":"32e5ac53-319c-4a2d-a350-0f69fe3752b6","order_by":4,"name":"Xinyi Luo","email":"","orcid":"","institution":"East China Normal University","correspondingAuthor":false,"prefix":"","firstName":"Xinyi","middleName":"","lastName":"Luo","suffix":""},{"id":490549547,"identity":"1183dc98-59f4-42e9-843d-2ce6bf54e981","order_by":5,"name":"Hong Liang","email":"","orcid":"","institution":"Qingdao Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Hong","middleName":"","lastName":"Liang","suffix":""},{"id":490549549,"identity":"b0588599-f32f-4669-92ea-5f17c35189ea","order_by":6,"name":"Xiushan Leng","email":"","orcid":"","institution":"Beijing Forestry University","correspondingAuthor":false,"prefix":"","firstName":"Xiushan","middleName":"","lastName":"Leng","suffix":""},{"id":490549551,"identity":"0d710a8e-db60-4166-8e51-8982c434d30b","order_by":7,"name":"Yuandong Hu","email":"","orcid":"","institution":"School of Landscape Architecture, Northeast Forestry University","correspondingAuthor":false,"prefix":"","firstName":"Yuandong","middleName":"","lastName":"Hu","suffix":""},{"id":490549554,"identity":"bf320c0f-0d52-4184-a43a-08fde3847a88","order_by":8,"name":"Enrong Yan","email":"","orcid":"","institution":"East China Normal University","correspondingAuthor":false,"prefix":"","firstName":"Enrong","middleName":"","lastName":"Yan","suffix":""},{"id":490549555,"identity":"e3481783-de96-4e46-9d3a-1f08f3f2b955","order_by":9,"name":"Kun Song","email":"","orcid":"https://orcid.org/0000-0001-8019-9707","institution":"East China Normal University","correspondingAuthor":false,"prefix":"","firstName":"Kun","middleName":"","lastName":"Song","suffix":""},{"id":490549556,"identity":"71f8e1f2-8999-4b07-9ce5-cc0f4459243b","order_by":10,"name":"Liangjun Da","email":"","orcid":"","institution":"Xi’an University of Architecture and Technology","correspondingAuthor":false,"prefix":"","firstName":"Liangjun","middleName":"","lastName":"Da","suffix":""}],"badges":[],"createdAt":"2025-07-06 15:55:25","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7058899/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7058899/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":91122916,"identity":"aca3a9b6-87d0-4712-b2c2-5157aa1bd62c","added_by":"auto","created_at":"2025-09-11 19:23:59","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":334420,"visible":true,"origin":"","legend":"\u003cp\u003eComposition and geographical patterns of spontaneous plant life forms in Yunnan Province, China. A: Pie charts show the richness of spontaneous plant life forms in each city, with chart size indicating total richness of city; B and C Scatterplots display the latitudinal and longitudinal trends in life form composition, with fitted local polynomial regression lines and 95% confidence intervals (shaded areas); D: Violin plots depict the distribution of life form proportions across cities. The shape of each violin represents the mirrored frequency distribution, with mean and interquartile ranges indicated by embedded boxplots.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7058899/v1/0d5ecb0b39ec280dec2bb20e.png"},{"id":91123168,"identity":"d20fb70c-1528-4e55-bb34-7349e0a7b701","added_by":"auto","created_at":"2025-09-11 19:31:59","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":66902,"visible":true,"origin":"","legend":"\u003cp\u003eThe relationship between the proportion of spontaneous plants with different life forms and MAT (A), City size, RGDP (C) and Sealed\u003csub\u003e.city\u003c/sub\u003e (D), as per the optimal model fitted by Bayesian Dirichlet regression analysis. MAT-mean annual temperature; RGDP-real gross domestic product per capita; Sealed\u003csub\u003e.city\u003c/sub\u003e- the proportion of sealed surface in each city.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7058899/v1/ae8285b32a1448484973abad.png"},{"id":91123570,"identity":"7de5fe1b-4950-44c6-b1e1-07debe3fee41","added_by":"auto","created_at":"2025-09-11 19:39:59","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":302715,"visible":true,"origin":"","legend":"\u003cp\u003eThe relationship between the proportion of spontaneous plants with different life forms and MAT (A), City size, RGDP (C) and Sealed\u003csub\u003e.city\u003c/sub\u003e (D), as per the optimal model fitted by Bayesian Dirichlet regression analysis. MAT-mean annual temperature; RGDP-real gross domestic product per capita; Sealed.\u003csub\u003ecity\u003c/sub\u003e- the proportion of sealed surface in each city.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-7058899/v1/9acce924c17ddf59f1d4ce4b.png"},{"id":91123738,"identity":"1b0fc055-b554-4c0d-bf17-9930bd7237e4","added_by":"auto","created_at":"2025-09-11 19:48:00","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1210969,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7058899/v1/da2822e6-31e3-4a5d-a94f-ed7f6904a0df.pdf"},{"id":91123571,"identity":"8b13e25e-f777-4b9d-a263-1715349145bf","added_by":"auto","created_at":"2025-09-11 19:39:59","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":19636,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable S1 \u003c/strong\u003eModel summary of the Bayesian Dirichlet regression models with life forms of spontaneous plant species.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable S2 \u003c/strong\u003eModel compare of the top five Bayesian Dirichlet regression models with life forms of spontaneous plant species.\u003c/p\u003e","description":"","filename":"suplymentaryinformation.docx","url":"https://assets-eu.researchsquare.com/files/rs-7058899/v1/d1e3f897ec72423509fa6d4e.docx"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"Divergent responses of plant growth forms to climate and urban expansion","fulltext":[{"header":"Introduction","content":"\u003cp\u003eUrbanization has far-reaching consequences for biodiversity and ecosystem functioning as a result of land use change, habitat fragmentation and alterations in hydrothermal conditions\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. As urban landscapes continue to expand, the ways in which they influence ecological processes become increasingly complex and multifaceted. Traditionally, urban areas are often perceived as biological deserts devoid of biodiversity\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e,\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. However, this perception neglects the complexity of urban ecosystems and their significant role in supporting diverse forms of life. In fact, urban areas can be biodiversity hotspots \u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e and serve as vital refuges for endemic and endangered species through providing essential resources such as shelter for their colonization and settlement in to other areas\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. Investigating how urbanization shifts distribution patterns and functional structure of spontaneous plant communities is crucial for understanding the mechanisms that sustain biodiversity in human dominated ecosystems, and for optimizing urban planning and conservation efforts.\u003c/p\u003e\u003cp\u003eUrban spontaneous plants comprise plants that have self-established without human intervention, yet are distinct from remaining natural vegetation\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. The diversity patterns of spontaneous plants are influenced not only by natural factors but also by anthropogenic factors. Known for their rapid response to disturbances, spontaneous plants serve as valuable indicators of urbanization dynamics\u003csup\u003e\u003cspan additionalcitationids=\"CR10\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. With the emerging concepts such as urban near-naturalization, rewilding, and nature-based solutions, spontaneous plants are increasingly being seen as having great potential as contributors to future urban greening\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eLife form represents a key functional strategy of plants in response to their environment. Different life forms (e.g., woody \u003cem\u003evs\u003c/em\u003e herbaceous species) underlie distinct functional traits, including life span, morphology, and physiology, which influences their adaptation to environmental conditions\u003csup\u003e\u003cspan additionalcitationids=\"CR14\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. Examining the distributional patterns of plant life forms provides important insights into ecological constraints acting on biodiversity\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. For example, numerous studies have found that the proportion of woody plants decreases gradually with increasing latitude\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e,\u003cspan additionalcitationids=\"CR17 CR18\" citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. Herbaceous plants tend to be less sensitive to lower temperature, precipitation and anthropogenic disturbance than woody plants\u003csup\u003e\u003cspan additionalcitationids=\"CR21 CR22\" citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e. A pronounced divergence in environmental adaptability of different life spans of the herbaceous life form is also apparent: compared to perennials, annuals exhibit superior flexibility to xeric and warm conditions and higher anthropogenic disturbance, which contributes to their increased probability to become invasive species when introduced to new locations\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e,\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e,\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. The correlations between climatic factors (in particular temperature and precipitation) and the abundance of different life forms are often so strong that plant growth form data have been used to complement the delineation of the bioregions in Africa\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e and the New World\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. Despite these advancements, the diversity patterns and of plant life forms and their driving factors along urbanization gradients at the regional scale, beyond the influence of natural environmental factors, remain unclear. Understanding these variations and their ecological drivers could improve predictions of terrestrial ecosystem changes under future climate scenarios\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e,\u003cspan additionalcitationids=\"CR28\" citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eHere, we surveyed spontaneous plants inhabiting 129 cities covering a wide range of macroclimatic conditions and urbanization intensities in Yunnan province, the most biodiverse province in China and one of the world\u0026rsquo;s biodiversity hotspots\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Our study aims to reveal the distribution patterns of different life-forms of spontaneous plants along the urbanization and climate gradient by testing two hypotheses: 1) In highly urbanized areas, the proportion of shorter-lived spontaneous plant species (such as annuals) will increase due to their greater adaptability to frequent anthropogenic disturbances, resulting in a relatively lower prevalence of perennials and woody plants, which are more dominant in less urbanized zones; 2) In cities experiencing more extreme hydrothermal conditions, such as higher or lower temperatures and drought, the proportion of shorter-lived spontaneous plant species will increase, while the prevalence of perennials and woody plants will decrease, as these life-forms are generally more dominant in cities with milder and more stable climates.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eAcross the 129 cities surveyed in Yunnan province, we recorded 2,864 spontaneous plant species of 1,261 genera from 222 families, including 477 annual herbaceous species, 1,222 perennial herbs, and 1,165 woody species. Perennial herbs dominated urban plant communities (mean proportion\u0026thinsp;=\u0026thinsp;0.45), followed by annual herbs (mean\u0026thinsp;=\u0026thinsp;0.29), and woody plants (mean\u0026thinsp;=\u0026thinsp;0.26). Pairwise comparisons revealed statistically significant differences among all life form pairs (all comparisons p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (\u003cb\u003eData 1\u003c/b\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe polynomial regression results revealed the proportions of life-forms fluctuate across both latitude and longitude (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB, C). The proportion of perennial herbs had a significant increased trend with latitude (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), while annual herbs and woody plants showed no significant trend with latitude (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.156 and \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.169, respectively), all three life-forms exhibited marked variation near 25\u0026deg; N. Conversely, the proportions of annual herbs showed decrease trend and woody plants showed increase trend with longitude (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001 and \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.003), whereas perennial herbs showed no significant trend with longitude (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.516). (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB and \u003cb\u003eC\u003c/b\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe optimal Bayesians regression analysis included mean annual temperature (MAT), city size, real gross domestic product per capita (RGDP), and the proportion of sealed surface in each city (Sealed.\u003csub\u003ecity\u003c/sub\u003e) as predictors (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Consistent with our first hypothesis, we found that city size had a significant positive effect on the proportion of annual herbs (\u003cem\u003eβ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.34, 95% CI: 0.18 to 0.50), but negative effect on the proportion of both perennial herbs (\u003cem\u003eβ\u003c/em\u003e = -0.04, 95% CI: -0.07 to -0.01) and woody plants (\u003cem\u003eβ\u003c/em\u003e = -0.3, 95% CI: -0.41 to -0.19). In relation to our second hypothesis, we found that higher MAT was significantly correlated with a lower proportion of perennial herbs (\u003cem\u003eβ\u003c/em\u003e = -0.07, 95% CI: -0.1 to -0.05). In contrast, MAT was positively associated with the proportion of woody plants (\u003cem\u003eβ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.09, 95% CI: 0.01 to 0.17), suggesting that warmer cities tend to support a higher relative abundance of woody life forms (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eTraditionally perceived as biodiversity deserts, our study of spontaneous plant richness across 129 cities in Yunnan province supports the notion that urban ecosystems are important reservoirs of biodiversity\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. Our study found that, despite urban areas encompassing less than 1% of the total area, spontaneous plants accounted for more than 15% (n\u0026thinsp;=\u0026thinsp;2,864) of the approximately 19,000 plant species found in Yunnan Province\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e. Spontaneous plants, in particular, play a vital role in maintaining urban biodiversity by providing habitats for pollinators and other wildlife, enhancing ecological resilience\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e,\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e. Protecting and managing these plants in urban areas can contribute to broader biodiversity conservation goals, offering a unique opportunity to integrate ecological and societal benefits in rapidly urbanizing regions\u003csup\u003e\u003cspan additionalcitationids=\"CR35\" citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eOur findings reveal striking deviations in life form proportions compared to global and regional baselines. The mean proportion of annual herbs across the cities in our study of 29.2% far exceeds the global average of 6% reported by Poppenwimer et al. (2023), and even the maximum values observed in desert ecosystems (14%)\u003csup\u003e25\u003c/sup\u003e. Additionally, woody plants in our study (mean 25.8% across cities) showed a comparatively lower proportion than that at global scales (\u0026ge;\u0026thinsp;42.7%)\u003csup\u003e13,37\u003c/sup\u003e, China (51.6%)\u003csup\u003e19\u003c/sup\u003e and Yunnan natural ecosystems (\u0026gt;\u0026thinsp;40.0%)\u003csup\u003e38\u003c/sup\u003e. Therefore, compared to natural ecosystems, we may conclude that short-lived species are significantly more prevalent, while long-lived species are proportionally reduced in urban ecosystems.\u003c/p\u003e\u003cp\u003eLatitudinal and longitudinal gradients in plant life form composition encompass composite geographic gradients, capturing not only temperature (particularly latitude) but also other covarying environmental and socioeconomic factors, such as precipitation, urban form, and historical land use. Our Bayesian hierarchical model results provide further insights into the urbanization drivers shaping the composition of urban spontaneous vegetation.\u003c/p\u003e\u003cp\u003eCompared to natural ecosystems, we hypothesized that the frequent anthropogenic disturbances in urban areas make it easier for some short-lived plants to colonize urban environments, while long-lived plants are more prone to local or regional extinction under frequent disturbances\u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e,\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e. Consistent with our first hypothesis, city size was found to have a significant positive effect on the proportion of annual herbs and a negative effect on the proportions of both perennial herbs and woody plants. This suggests that urban expansion may directly promote the persistence of short-lived plants while constrain that of long-lived plant forms.\u003c/p\u003e\u003cp\u003eLarger cities tend to have higher levels of land sealing, fragmentation of green space, more intensive anthropogenic disturbance, and longer process of urbanization\u003csup\u003e\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e,\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e, all of which may contribute to reduced habitat suitability for perennials and woody species. This pattern aligns with the notion that urban environments act as powerful ecological filters, favoring opportunistic annual herbs with rapid life cycles while suppressing species with long juvenile phases and high resource demands\u003csup\u003e\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e. As highlighted by Uchida et al. (2021)\u003csup\u003e\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e, urbanization not only alters species richness but also drives functional homogenization, with expanding cities increasingly dominated by disturbance-tolerant herbaceous plants. Compare to annual plant forms, perennials and woody species typically require stable habitats, deeper soils, and longer establishment periods, which are increasingly rare in highly urbanized environments\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e. The much stronger effect size for woody plants (\u003cem\u003eβ\u003c/em\u003e = -0.30) compared to perennials (\u003cem\u003eβ\u003c/em\u003e = -0.04) also reflects the greater sensitivity of trees and shrubs to long-term land-use change and habitat degradation. Therefore, urban ecosystems may be converging, under the influence of urban expansion and disturbance, towards a functional homogenization characterized by the dominance of opportunistic herbaceous plants with short life cycles\u003csup\u003e\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e. Consequently, effective urban biodiversity management should consider scale-dependent strategies, such as prioritizing land-sparing approaches and innovative green infrastructure in large cities, to mitigate the loss of perennial and woody species and preserve ecosystem multifunctionality in the face of ongoing urban expansion\u003csup\u003e\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eThe increase of annual herbs in urban ecosystems is not only a reflection of their rapid colonization of disturbed habitats, but also a result of the increased presence of invasive species. In our study, 57% (86 out of 151) of the identified invasive plants were annuals. Many annual plants, especially those that thrive in urbanized environments, belong to invasive species that are adept at exploiting the altered conditions created by urbanization\u003csup\u003e\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u003c/sup\u003e. These species often outcompete native plants due to their fast reproductive cycles, adaptability to disturbed habitats, and lack of natural predators or competitors\u003csup\u003e\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e. As urban areas expand, the prevalence of these invasive annuals is likely to increase, further altering plant communities and threatening local biodiversity. Given these trends, we propose that more research should be conducted to better understand the mechanisms driving the success of invasive annuals in urban environments and to develop effective management strategies to mitigate their impacts.\u003c/p\u003e\u003cp\u003eClimate conditions are the primary environmental filter for plants and are closely related to the life form compositions of urban spontaneous plants. The high explanatory power of MAT in shaping the diversity of spontaneous plant life forms, aligns with the notion that temperature is the primary driver of plant distribution\u003csup\u003e\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u003c/sup\u003e. Notably, perennial herbs and woody plants display contrasting responses to climatic gradients. Numerous studies have confirmed that the proportion of woody plants increases significantly with rising temperatures\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e,\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u003c/sup\u003e. Warmer conditions often extend the growing season and reduce the frequency of frost events, which benefits woody species by allowing greater investment in long-lived structures and deeper root systems\u003csup\u003e\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e,\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e\u003c/sup\u003e. In temperate forests and grasslands, experimental warming treatments have consistently led to an increase in woody plant recruitment and a decline in herbaceous cover\u003csup\u003e\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e\u003c/sup\u003e. Meta-analyses across biomes indicate that woody plants are generally more resilient to temperature increases due to their physiological and morphological adaptations, such as thicker bark, higher wood density, and deeper roots\u003csup\u003e\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e\u003c/sup\u003e. Conversely, perennial herbs, especially in warmer climates, may face increased evapotranspiration and water stress, which can limit their persistence and competitiveness\u003csup\u003e\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e\u003c/sup\u003e. Elevated temperatures can accelerate soil moisture loss and increase the frequency and intensity of drought events, further exacerbating the challenges for perennial herbs\u003csup\u003e\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e\u003c/sup\u003e. These findings suggest that the observed correlations in our study are part of a broader ecological phenomenon, where rising temperatures shift plant community composition toward woody dominance at the expense of herbaceous perennials. Further research should focus on disentangling the roles of temperature, water availability, disturbance, and biotic interactions in shaping these patterns across different ecological contexts.\u003c/p\u003e\u003cp\u003eOverall, our study highlights the critical role of spontaneous plants in urban ecosystems, underscoring the potential of cities as biodiversity reservoirs. It reveals that urbanization and climate jointly shape the composition of spontaneous plant communities, driving a functional shift towards short-lived, disturbance-adapted life forms. As cities expand, the proportion of short-lived plants may increase, leading to a shift in urban ecosystems towards a dominance of annual herbs, while perennial herbs and woody species, become increasingly rare. The decline of perennial and woody life forms in larger cities highlights the need for integrative urban planning that supports a range of plant strategies and balances urban development with biodiversity conservation. Furthermore, the potential impacts of future climate warming on different plant life forms of spontaneous plants should also raise further concern. Given their substantial contribution to plant species diversity and their role in providing critical habitats for wildlife, including pollinators and birds\u003csup\u003e\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e,\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e\u003c/sup\u003e, the ongoing loss of perennial herbs and woody plants in urban should be curbed and reversed. Promoting their persistence will help cities move beyond simply accommodating biodiversity toward actively sustaining it in the face of accelerating environmental change.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003e\u003cstrong\u003eStudy area\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOur study was carried out in Yunnan province, China (N 21\u0026deg;8\u0026apos;32\u0026apos;\u0026apos; - N 29\u0026deg;15\u0026apos;8\u0026apos;\u0026apos;, E 97\u0026deg;31\u0026apos;39\u0026apos;\u0026apos; - E 106\u0026deg;11\u0026apos;47\u0026apos;\u0026apos;), a biodiversity hotspots with complex topography with significant variation in altitude (77 m \u0026minus;\u0026thinsp;6740 m), temperature (average annual temperature 5.0℃ \u0026minus;\u0026thinsp;23.8℃) and precipitation (total annual precipitation 580 mm \u0026minus;\u0026thinsp;2700 mm) across its territory\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e58\u003c/span\u003e\u003c/sup\u003e. Despite occupying only 4.1% of the total territory area of the country, the diverse natural environmental conditions make the province accommodate more than 51.6% (\u0026ge;\u0026thinsp;18,000 species) of all higher plants recorded in China\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e30\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e. Additionally, the distinct urbanization processes and diverse environmental gradients of between cities in Yunnan province present an ideal place to study urban ecology.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData collection\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eField surveys of spontaneous plant species were conducted during the growing season (April-October) in 2017\u0026ndash;2023, following the sampling protocol described in detail in our previous studies\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e32\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e33\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e59\u003c/span\u003e\u003c/sup\u003e. In short, spontaneous plants were sampled across all 129 county-level cities, which are widely distributed along natural and urbanization gradients. In each city, sampling sites with a 500 m radius were established at about 2 km intervals from the city center to the city outskirts. Within each sampling site, at least three accessible green patches were randomly selected for a species richness survey.\u003c/p\u003e\n\u003cp\u003eThe life forms of species were categorized into three groups: woody plants, annual herbs and perennial herbs, according to published literature\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e and the Flora of China (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.iplant.cn/\u003c/span\u003e\u003c/span\u003e). The proportions of the three life forms spontaneous plants were treated as composite dependent variables in this study. We examined ten explanatory variables potentially associated with the long-term persistence of trees, representing two major categories: climate factors and anthropogenic factors (see details in Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). Climate factors including mean annual temperature (MAT), Mean annual total precipitation (MAP), Evaporation and relative humidity (RH). Anthropogenic factors primarily reflect the intensity and rate of urbanization across different cities. These include factors such as city size, the human footprint (HFP), night light intensity in each site (Light.\u003csub\u003esite\u003c/sub\u003e), real gross domestic product per capita (RGDP), the proportion of sealed surface in each city (Sealed.\u003csub\u003ecity\u003c/sub\u003e), and sealed surface expansion rate of each city from 1990 to 2019 (i.e., urbanization rate, UR.\u003csub\u003ecity\u003c/sub\u003e). As urban areas rapidly expand (i.e., city size increasing), human activity and habitat disturbance intensify, often leading to greater environmental pressures and altering the balance of local ecosystems\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e. HFP is used to monitor changing anthropogenic pressures on a yearly cadence based on land cover change, population density, nighttime lights, roads, railways, and navigable rivers\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e60\u003c/span\u003e\u003c/sup\u003e. Light.\u003csub\u003esite\u003c/sub\u003e and RGDP reflect the level of human development and economic activity within a city, which in turn influences the intensity of urbanization and its effects on plant colonization\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e61\u003c/span\u003e\u003c/sup\u003e. Sealed.\u003csub\u003ecity\u003c/sub\u003e directly impacts the availability of habitats for plant species and their ability to establish in the city environment\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e62\u003c/span\u003e\u003c/sup\u003e. UR.\u003csub\u003ecity\u003c/sub\u003e representing the historical dynamics of urban expansion, captures how the rate of urbanization has evolved over time and the cumulative effect on species\u0026apos; dispersal and survival across urban landscapes\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eThe description of explanatory variables in Bayesian Dirichlet regression models.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eExplanatory variables\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eDescription\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSource\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003eNatural factors\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMAT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMean annual temperature\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003eNational Earth System Science Data Center (mean value of 1960\u0026ndash;2021, resolution\u0026thinsp;=\u0026thinsp;1 km, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ewww.geodata.cn\u003c/span\u003e\u003c/span\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMAP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMean annual total precipitation\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEvaporation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRelative humidity\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"6\"\u003e\n \u003cp\u003eAnthropogenic factors\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCity size\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCity size was calculated\u003c/p\u003e\n \u003cp\u003eby moving windows (1 km \u0026times; 1 km, threshold\u0026thinsp;=\u0026thinsp;50%, 2020)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHFP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHuman Footprint\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGlobal 100m Terrestrial Human Footprint, 2020 (HFP-100, resolution\u0026thinsp;=\u0026thinsp;100 m, https://datadryad.org/stash/dataset/doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.5061/dryad.ttdz08m1f\u003c/span\u003e\u003c/span\u003e)\u003csup\u003e60\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLight.\u003csub\u003esite\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNight light intensity in each site\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eresolution\u0026thinsp;=\u0026thinsp;1 km\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e61\u003c/span\u003e\u003c/sup\u003e, 2020\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRGDP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eReal gross domestic product per capita, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:RGDP=GDP/population\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eChinese population census yearbook 2020\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSealed.\u003csub\u003ecity\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eThe proportion of sealed surface in each city\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eresolution\u0026thinsp;=\u0026thinsp;30 m\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e63\u003c/span\u003e\u003c/sup\u003e, 2020\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUR.\u003csub\u003ecity\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSealed surface expansion rate of each city (i.e., urbanization rate) from 1990 to 2019\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\n \u003ch2\u003eData analysis\u003c/h2\u003e\n \u003cp\u003eTo assess differences in proportional representation among plant life forms (annual herbs, perennial herbs, and woody plants), we conducted pairwise two-sided t-tests among the three life form types and reported exact p-values. We used the ggplot2 package to plot the trends of life form proportions along latitude and longitude gradients, and applied the geom_smooth function with the locally weighted regression (LOESS) method to fit smooth trend lines, thereby revealing the variation patterns of life form proportions along geographic gradients.\u003c/p\u003e\n \u003cp\u003eTo evaluate the relationship of environmental variables, while accounting for the interdependencies of the three compositional proportions (annual herbs, perennial herbs, and woody plants always sum to 100%), we employed Bayesian Dirichlet regression models (logit-link) using the brms package\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e64\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e65\u003c/span\u003e\u003c/sup\u003e. As predictor variables, we used all climate and anthropogenic factors described Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e. All continuous predictors were standardized (mean\u0026thinsp;=\u0026thinsp;0, SD\u0026thinsp;=\u0026thinsp;1). To comprehensively explore potential model structures, we generated all possible combinations of candidate predictors. Each model included a nested random effect structure (1|cityid/siteid) to account for the spatial hierarchy in the study design. All models were fitted in parallel using the \u003cem\u003ecmdstanr\u003c/em\u003e backend, with 4 chains, 4000 iterations per chain (2000 warm-up), and 5 threads per chain. To ensure numerical stability, we set adapt delta\u0026thinsp;=\u0026thinsp;0.99 and max treedepth\u0026thinsp;=\u0026thinsp;15. Model performance was compared using leave-one-out cross-validation via the loo criterion\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e65\u003c/span\u003e\u003c/sup\u003e. Models with high collinearity (i.e., any predictor VIF\u0026thinsp;\u0026ge;\u0026thinsp;5, checked using check_collinearity from the performance package) were excluded, yielding 511 valid models from 1,023 models\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e66\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e68\u003c/span\u003e\u003c/sup\u003e. The model with the highest expected log predictive density was selected as the best-supported model and presented. We ran all analyses using the R Software 3.5.1\u003csup\u003e69\u003c/sup\u003e, and used ggplot2 and ggpubr packages\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e70\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e71\u003c/span\u003e\u003c/sup\u003e for visualizations.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData and code availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data and code for the analysis will be made available once the manuscript is accepted.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was funded by Major Program for Basic Research Project of Yunnan Province (202101BC070002), the Ministry of Science and Technology of China (2015FY210200), ECNU Academic Innovation Promotion Program for Excellent Doctoral Students (YBNLTS2019). Yingji Pan 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).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interest Statement:\u0026nbsp;\u003c/strong\u003eThe authors declare no conflict of interest.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eHou, Y., Li, J., Li, G. \u0026amp; Qi, W. Negative effects of urbanization on plants: A global meta‐analysis. \u003cem\u003eEcol. Evol.\u003c/em\u003e \u003cstrong\u003e13\u003c/strong\u003e, 1-9 (2023).\u003c/li\u003e\n\u003cli\u003eHall, D. M. et al. The city as a refuge for insect pollinators. \u003cem\u003eConserv. Biol.\u003c/em\u003e \u003cstrong\u003e31\u003c/strong\u003e, 24-29 (2017).\u003c/li\u003e\n\u003cli\u003eKantsa, A., Tscheulin, T., Junker, R. R., Petanidou, T. \u0026amp; Kokkini, S. 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(springer New York, 2009).\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"nature-portfolio","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"","title":"Nature Portfolio","twitterHandle":"","acdcEnabled":false,"dfaEnabled":false,"editorialSystem":"ejp","reportingPortfolio":"","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Biodiversity hotspots, plant life forms, urban spontaneous plants, urban ecosystems","lastPublishedDoi":"10.21203/rs.3.rs-7058899/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7058899/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eUrbanization and climate change are rapidly altering large-scale plant distributions and local community compositions, profoundly impacting ecosystem functions and services. However, it remains unclear how life form compositions, one of the key functional biodiversity components, respond jointly to urbanization and climate gradients. Here we investigated the life form compositions of 2,864 naturally regenerated spontaneous plant species across 129 cities in Yunnan province of China, a global biodiversity hotspot with diverse environmental condition. Our results showed perennial herbs (45.0%) predominated in urban ecosystem, followed by annual herbs (29.2%) and woody plants (25.8%). Bayesian hierarchical models revealed that as urban expansion, the proportions of annual herbs rise, while the proportions of both perennial herbs and woody plants decline, indicating urban expansion favors short-lived plants but is detrimental to long-lived plants. Increasing mean annual temperature with a decline in perennial herbs and a concurrent increase in woody plants, suggesting divergent adaptive responses to thermal stress. Our results highlight the complex, divergent responses of plant life forms to urbanization and climate change, emphasizing the need for targeted conservation strategies that consider both the resilience of short-lived species and the vulnerability of long-lived plants.\u003c/p\u003e","manuscriptTitle":"Divergent responses of plant growth forms to climate and urban expansion","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-11 19:23:54","doi":"10.21203/rs.3.rs-7058899/v1","editorialEvents":[],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"nature-communications","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"NCOMMS","sideBox":"Learn more about [Nature Communications](http://www.nature.com/ncomms/)","snPcode":"","submissionUrl":"https://mts-ncomms.nature.com/","title":"Nature Communications","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature Communications","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"894284c0-f708-49de-b48f-6d315b840003","owner":[],"postedDate":"September 11th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":52086984,"name":"Biological sciences/Ecology/Urban ecology"},{"id":52086985,"name":"Biological sciences/Ecology/Biodiversity"},{"id":52086986,"name":"Biological sciences/Ecology/Ecosystem ecology"}],"tags":[],"updatedAt":"2025-09-11T19:23:54+00:00","versionOfRecord":[],"versionCreatedAt":"2025-09-11 19:23:54","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7058899","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7058899","identity":"rs-7058899","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}