Plasticity of inflorescence traits in <i>Lobelia siphilitica</i> (Lobeliaceae) in response to soil water availability
Bibliographic record
Abstract
Many workers have demonstrated a genetic basis for variation in inflorescence traits, but this variation can also have an environmental component. Because flowering can incur significant water costs, I estimated plasticity of inflorescence traits of three populations of Lobelia siphilitica in response to drought. I manipulated soil water availability in the greenhouse and measured seven inflorescence traits. Under drought conditions, plants from one population flowered later and produced fewer flowers with shorter corollas and narrower landing pads. In contrast, the height of the flowering stalk decreased in response to drought in all three populations. Consequently, pollinator-mediated natural selection on these plastic traits may depend on soil water availability. Plastic responses differed between genotypes only for the height of the flowering stalk and the length of the corolla tube and only in one or two populations. This suggests that genotype × environment interactions would not limit the evolution of inflorescence traits in L. siphilitica. The strength and sign of phenotypic correlations among inflorescence traits did not respond plastically to drought, suggesting that indirect selection on inflorescence traits of L. siphilitica will not vary strongly with water availability. My results suggest that plasticity of inflorescence traits may influence their evolution, but the effects are population- and trait-specific.
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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) | 0.001 | 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".