The effects of drought and waterlogging conditions on the performance of an endemic annual plant, <i>Aster</i> <i>laurentianus</i>
Bibliographic record
Abstract
Aster laurentianus Fernald is an annual plant endemic to the St. Lawrence estuary. It typically grows in salt marshes at the periphery of shallow lagoons. In this habitat, the water level fluctuates greatly both within and between years. Such fluctuations may induce significant interannual variations in marsh-plant populations. In this study, we experimentally determined the effects of different water availability conditions, imposed at various stages of plant development, on the performance of A. laurentianus. Waterlogging had no significant effect on net carbon assimilation rate, plant growth, and biomass allocation. However, a drought stress at the time of reproductive-bud differentiation had a negative effect on flower-head production. We propose that occasional reproductive failures resulting from late-summer droughts may cause significant interannual fluctuations in the size of A. laurentianus populations, potentially making them more susceptible to local extinction.Key words: Aster laurentianus, endemic plant, Îles-de-la-Madeleine, rare plant, salt marshes, water stress.
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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".