Environment drives spatiotemporal patterns of clonality in white spruce (<i>Picea glauca</i>) in Alaska
Bibliographic record
Abstract
Many plant species reproduce by cloning if environmental conditions are unfavorable for sexual reproduction. To test the alternative hypotheses, whether cloning is an “exit strategy” or caused by selection, clonal growth in white spruce (Picea glauca (Moench) Voss) was investigated in three stands in Alaska, each consisting of a core (closed forest) plot and an edge (tree-line) plot. In total, 2571 trees were mapped and genotyped with 11 single sequence repeat (SSR) markers. The proportion of clonal trees follows a moisture gradient and was lowest in the dry Interior basin (4.5%), followed by the sites at the Alaska Range (9.0%) and the Brooks Range (21.7%). At the two latter sites, clonal growth was more frequent in the edge plot. A comparison among 960 aged trees revealed that clonal growth becomes more likely with increasing age and continues over the life span of a tree. Genetic data do not indicate any genetic predisposition for cloning. Clonal growth in white spruce most likely takes place via layering and depends on environmental conditions. Because performance of the trees, and therefore likely plant reproductive success, is lower in plots with a high proportion of clones, selection for clonal growth seems to be highly unlikely.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".