Variables influencing germination and initial survival of two critically endangered plants: <i>Warea amplexifolia</i> and <i>Lupinus aridorum</i>
Bibliographic record
Abstract
One challenge of ex situ conservation is developing propagation methods that promote a high rate of survival and genetic diversity. Developing successful propagation methods is especially important for rare species to prevent their extinction. Clasping warea, Warea amplexifolia (Nutt.) Nutt. (Brassicaceae), and scrub lupine, Lupinus aridorum McFarlin ex Beckner (Fabaceae), are two rare species endemic to imperiled Florida sandhill and scrub habitats, respectively. We tested whether the collection site of seeds, seed stratification temperature, and several propagation methods influenced germination and initial survival of W. amplexifolia and L. aridorum. The collection site of seeds and type of pot influenced percent germination of W. amplexifolia, whereas soaking seeds in water and stratification temperature did not. The site where seeds were collected did not influence germination of L. aridorum and treating seedlings with salicylic acid, nitrogen, or salicylic acid and nitrogen sometimes reduced, but did not increase, initial survival of seedlings. Overall, our results will inform additional experiments on ex situ conservation and may be applicable to other herbs endemic to Florida.
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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".