Natural selection on floral traits of <i>Lobelia</i> (Lobeliaceae): spatial and temporal variation
Bibliographic record
Abstract
The strength and direction of natural selection on floral traits can vary spatially and temporally because of variation in the biotic and abiotic environment. High spatial variation in selection should lead to differentiation of floral traits among populations. In contrast, high temporal variation in selection should retard the evolution of population-specific floral phenotypes. To determine the relative importance of spatial vs. temporal variation in natural selection, we measured phenotypic selection on seven floral traits of the wildflowers Lobelia cardinalis and L. siphilitica in 1999 and 2000. Lobelia cardinalis experienced significant temporal variation in selection, whereas L. siphilitica experienced spatial variation in selection on the same traits. This variation in selection on floral traits was associated with spatial and temporal differences in the soil microenvironment. Although few studies of natural selection include spatial or temporal replicates, our results suggest that such replication is critical for understanding the distribution of phenotypes in nature.
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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 | 0.000 |
| 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 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".