Germination time influences post-germination life-history traits and progeny seed germination patterns in the desert annual <i>Erodium laciniatum</i> (Geraniaceae)
Bibliographic record
Abstract
Annual plants in arid regions germinate at different times within a growing season, from early in the season to late, and this may affect post-germination traits. For this study, I tested the effect of germination timing on post-germination life-history traits, including progeny seed germination in the desert annual Erodium laciniatum var. pulverulentum (Cav.) Boiss. Traits of November- and February-germinated individuals were studied in a field survey carried out in northwestern Saudi Arabia, and the germination of freshly matured and after-ripened seeds from both early- and late-germinated plants was assessed. Overall, E. laciniatum showed significant phenotypic plasticity in life-history traits arising from different germination times. Density, survivorship and reproductive success of early-germinated plants were all significantly greater than for those that germinated later. Late-germinated plants flowered earlier, bolted at smaller size and allocated more biomass to reproduction than did early-germinated individuals. Delayed germination shortened both flowering period and life span. Seeds produced by late-germinated plants had greater germination percentage than did seeds from early-germinated plants.
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) | 0.000 | 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 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".