Lobelia siphilitica Plants That Escape Herbivory in Time Also Have Reduced Latex Production
Bibliographic record
Abstract
Flowering phenology is an important determinant of a plant's reproductive success. Both assortative mating and niche construction can result in the evolution of correlations between phenology and other reproductive, functional, and life history traits. Correlations between phenology and herbivore defence traits are particularly likely because the timing of flowering can allow a plant to escape herbivory. To test whether herbivore escape and defence are correlated, we estimated phenotypic and genetic correlations between flowering phenology and latex production in greenhouse-grown Lobelia siphilitica L. (Lobeliaceae). Lobelia siphilitica plants that flower later escape herbivory by a specialist pre-dispersal seed predator, and thus should invest fewer resources in defence. Consistent with this prediction, we found that later flowering was phenotypically and genetically correlated with reduced latex production. To test whether herbivore escape and latex production were costly, we also measured four fitness correlates. Flowering phenology was negatively genetically correlated with three out of four fitness estimates, suggesting that herbivore escape can be costly. In contrast, we did not find evidence for costs of latex production. Generally, our results suggest that herbivore escape and defence traits will not evolve independently in L. siphilitica.
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 | 0.000 | 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".