Inter- and intraspecific variations of the chemical properties of high-Arctic mosses along water-regime gradients
Bibliographic record
Abstract
We examined and compared the contents of organic chemical components (lignin-like compounds, total carbohydrates and extractives), carbon and nutrients (nitrogen, phosphorus, potassium, calcium, magnesium) among the mosses Calliergon giganteum, Hylocomium splendens, Racomitrium lanuginosum, and among three populations of H. splendens collected from habitats in contrasting water regimes in the Canadian high-arctic tundra. C:N:P ratios were analyzed among and within moss species. Mosses from hydric habitats had lower total carbohydrate and higher nutrients contents than did mosses from drier habitats; however, we found no intraspecific variations in nitrogen and calcium contents in the different populations of H. splendens along water-regime gradients. The contents in lignin-like compounds, extractives and carbon showed no clear trends along water-regime gradients. Mosses from hydric habitats had lower C:N, C:P and N:P ratios than mosses from drier habitats, although we found no intraspecific variations in C:N ratios in H. splendens along water-regime gradients. These results suggest that chemical properties of mosses, especially nutrient contents, are strongly correlated with water availability in high-Arctic tundra.
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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 | 0.000 |
| Science and technology studies | 0.001 | 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".