The impact of urbanization on outcrossing rate and population genetic variation in the native wildflower, <i>Impatiens capensis</i>
Bibliographic record
Abstract
Abstract Cities are one of the fastest growing ecosystems on the planet, and conserving urban biodiversity is of primary importance. Urbanization increases habitat fragmentation and may be particularly problematic for native plant species which often exist in small, remnant populations in cities. We studied the effects of urbanization on Impatiens capensis, a self-compatible native wildflower, which is an important nectar and pollen source for native bees and hummingbirds. We sampled I. capensis from six populations located in urban and rural habitats in Toronto, Ontario, Canada. We sequenced the DNA of 43 families (N = 86 individuals) using genotype-by-sequencing to obtain 5627 single nucleotide polymorphisms. From each parent and offspring, we estimated individual outcrossing rates, population-level genetic diversity and genetic structure among populations. We found that 95% of plants were outcrossed, and populations were genetically differentiated, where urban populations contained a subset of the genetic variation found in rural populations. Urban populations exhibited lower genetic diversity than rural populations, and we detected a relationship between population census size and habitat on genetic diversity. Despite high outcrossing rates, our results suggest that urbanization reduces the genetic diversity of I. capensis populations, potentially increasing the vulnerability of these populations to long-term population declines and extirpation in response to urbanization.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".