Spatiotemporal land use dynamics filter life history strategies to shape urban spontaneous plant assemblages
Bibliographic record
Abstract
Spontaneous plants, such as weeds, are a key component of urban flora that can provide significant ecological benefits like nutrient cycling and soil pollutant removal. Our ability to fully harness these species in urban restoration efforts is hindered, however, due to a lack of understanding of their functional ecology under urban stressors. Here, we analyzed the effects of spatiotemporal urban land dynamics on the functional diversity of spontaneous plants from three life history strategies: colonization, establishment, and nutrient acquisition. Specifically, we measured 11 functional traits of 54 spontaneous plants across 79 sampling sites in Chongqing, a rapidly growing megacity in southwestern China with a population exceeding 16 million. We found that colonization-related traits of spontaneous plants were uncorrelated with nutrient-acquisition traits. When controlled for species richness, functional α- and β-diversity showed clearer responses to urbanization that varied by life history strategy and urban development stage. Spontaneous plant assemblages became more functionally homogeneous in their colonization and nutrient-acquisition strategies within newly urbanized areas than in historically developed areas. Yet, establishment strategies exhibited a neutral response to urbanization. Our findings reveal both challenges and opportunities of utilizing spontaneous plants in urban landscapes, highlighting the need to consider temporal dynamics in urban growth and plant functional diversity across life history strategies. Effective management should focus on controlling high-dispersal spontaneous plants in historically developed areas while retaining those with diverse nutrient acquisition strategies in newly urbanized areas to maximize ecological benefits for sustainable urban development.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".