What can routine germination tests in seed banks tell us about the germination ecology of endemic and protected species?
Bibliographic record
Abstract
Protocols for the conservation of threatened plants are often constrained by the absence of data on germination ecology. However, seed bank managers periodically monitor the viability of stored seed collections using germination tests. Here, we argue that data from those tests can and should be used to provide information on germination requirements of threatened species. Twelve taxa endemic to Portugal were used as a test case to determine the effect of incubation temperature and pretreatments upon germination and to identify major factors eliciting germination and releasing dormancy. We achieved maximum germination percentages >95% for nine taxa. Temperature significantly affected the final germination and mean germination time in most taxa. Maximum and faster germination at cool temperatures (15 °C or alternate 20/10 °C) was the prevailing trend. Cold stratification improved germination in one species, suggesting physiological dormancy. Scarification increased the germination percentage of one species among those expected to exhibit physical dormancy. Seed bank data provided valuable information on germination ecology, which can be used in in-situ conservation and as a baseline for further germination studies. Given the increasing threats to plant diversity, accessibility to seed bank data are paramount.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".