 Interaction between graminoids and shrubs modify responses of these plants to warming and nitrogen addition in a boreal bog
Bibliographic record
Abstract
The warmer and/or nitrogen-enriched conditions may significantly affect boreal bog vascular plants. These environmental changes may also alter the vascular plant interaction that can modify the responses of the plants to the ecological changes. Here, we combined vegetation removal treatments with warming and nitrogen addition experiments to investigate the effects of the abiotic and biotic changes on the above and below-ground growth of graminoids and shrubs at a Canadian boreal bog. We found that graminoids positively responded to nitrogen addition with the increases in leaf growth, cover, and decreases in root biomass. Warming did not affect the cover and root biomass of graminoids; however, this treatment enhanced graminoid root distribution in the deeper peat layer. Shrub removal had no effect on leaf growth, cover, and root biomass of graminoids, while the removal of shrubs modified the effects of nitrogen addition and warming on graminoid root biomass and root distribution. Our results also reveal that nitrogen addition and warming stimulated the above-ground growth of boreal bog shrubs. Meanwhile, the cover of shrubs was enhanced by warming and not affected by nitrogen addition. Graminoid removal significantly affected the cover, above and below the growth of shrubs in the boreal bog. These findings highlight the significant role of graminoid and shrub interaction that regulates the responses of these plants to warming and nitrogen addition. Our results suggest an increasing trend of boreal bog vascular plants under future warmer, nitrogen-enriched conditions. The dynamics of vegetation may significantly alter the vital services of boreal bogs.
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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 | 0.000 |
| 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".