Intraspecific Divergence in Seed Germination Traits between High- and Low-Latitude Populations of the Arctic-Alpine Annual Koenigia islandica
Bibliographic record
Abstract
ABSTRACT Populations of arctic-alpine plant species inhabit a range of environments, to which their life-history characters are expected to have adapted; yet geographic differentiation among populations is seldom studied. Brief growing seasons mean that germination characters are critical fitness traits, especially for annual species. In this study, striking differences in germination traits among three geographically distinct populations of the widely distributed arctic-alpine annual Koenigia islandica are found. The seeds (achenes) of the Colorado population, which experience the lowest summer temperatures, are conditionally dormant; only scarification breaks dormancy. This germination pattern is consistent in all four investigated subpopulations from Colorado, with no significant differences among them. In contrast, seeds originating in the Yukon, which experience extreme winter temperatures but a relatively warm summer, germinate readily after cold stratification, a pattern consistent with that of summer annuals. Seeds from the Norway population, which experience the mildest climate, germinate readily even if untreated. Cold stratification decreases germination fraction in the Norway population, a pattern characteristic of winter annuals. The strong population differentiation found here provides evidence for divergent selection operating among arctic-alpine habitats and suggests that further investigation of its adaptive significance is merited.
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 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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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".