Geographic variation in floral traits is associated with environmental and genetic differences among populations of the mixed mating species <i>Collinsia heterophylla</i> (Plantaginaceae)
Bibliographic record
Abstract
Relatively few studies have investigated how geography, environmental factors, and genetics affect floral trait variation. We used mixed-mating Collinsia heterophylla Buist to explore variation in a suite of floral traits related to mating system in populations representing four geographic regions of California, USA, and relate this variation to geography, climatic factors, and local site characteristics. We evaluated the environmental vs. genetic trait variability in the greenhouse. Stage of anther–stigma contact correlated positively with temperature, stage of stigma receptivity was negatively associated with vegetation cover, and flower size differed among populations without any clear relation to environmental factors. Greenhouse data indicated heritability for stage of anther–stigma contact, flower size, and time to flowering, and positive correlations between field and greenhouse for stage of stigma receptivity and flower size; however, stage of anther–stigma contact showed a high degree of environmental influence. Stage of anther–stigma contact covaried positively with stage of stigma receptivity and flower size across maternal families, indicating genetic correlations between traits. In conclusion, phenotypic floral variation within mixed-mating C. heterophylla is mostly determined by a genetic component. Geography, environment, and genetics affect traits differently, suggesting that ecological and evolutionary processes contribute to shaping variability in mating system-related traits.
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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) | 0.000 | 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 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".