Changes in high arctic tundra plant reproduction in response to long-term experimental warming
Bibliographic record
Abstract
We provide new information on changes in tundra plant sexual reproduction in response to long-term (12 years) experimental warming in the High Arctic. Open-top chambers (OTCs) were used to increase growing season temperatures by 1–2 °C across a range of vascular plant communities. The warming enhanced reproductive effort and success in most species; shrubs and graminoids appeared to be more responsive than forbs. We found that the measured effects of warming on sexual reproduction were more consistently positive and to a greater degree in polar oasis compared with polar semidesert vascular plant communities. Our findings support predictions that long-term warming in the High Arctic will likely enhance sexual reproduction in tundra plants, which could lead to an increase in plant cover. Greater abundance of vegetation has implications for primary consumers – via increased forage availability, and the global carbon budget – as a function of changes in permafrost and vegetation acting as a carbon sink. Enhanced sexual reproduction in Arctic vascular plants may lead to increased genetic variability of offspring, and consequently improved chances of survival in a changing environment. Our findings also indicate that with future warming, polar oases may play an important role as a seed source to the surrounding polar desert landscape.
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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 | 0.001 |
| 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".