Urbanization correlates with genetic and plastic variation of the spotted jewelweed flower morphology
Bibliographic record
Abstract
Abstract The spectacular diversity of flowers is largely driven by pollinator-mediated selection that favors attractive flowers and effective pollen transfer. Urbanization has the potential to affect floral trait evolution by altering pollinator communities through environmental changes. Additionally, abiotic changes in urban habitats can induce phenotypic plasticity, further shaping evolutionary trajectories. We investigated how urbanization affects the genetic and plastic components of flower morphology of Impatiens capensis across four Canadian cities. We found that urbanization influenced the pollinator community composition and the body size of bumblebees, the species’ main pollinator, although the magnitude of the size effect varied among cities. Using a combination of field surveys and a common garden experiment, our results suggest that urbanization affects sepal size – a tubular floral organ in which pollinators enter to access the nectar – through both genetic and plastic responses. While plasticity sometimes masked the genetic determination of sepal size in the field, we observed a positive correlation between the genetic component of the sepal size and bumblebee body size. These results suggest that urban habitats may drive evolutionary changes in floral traits by modifying pollinator communities.
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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 | 0.000 |
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 source (direct Gemma or distilled Codex), 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".