Long-term decomposition of above- and below-ground tissue of two Arctic shrub species
Bibliographic record
Abstract
Arctic soils may become a major source of greenhouse gas emissions, as the climate changes. It is thus crucial to understand decomposition dynamics of permafrost soils, which are influenced by a myriad of abiotic and biotic factors including changing plant communities. Here, litterbags filled either with dried twigs, leaves, and roots of two shrubs ( Salix arctica Pall and encroaching Salix richardsonii Hook) were buried at two different soil depths (0–10 and 10–20 cm) at a site on Bylot Island, Nunavut, Eastern Canadian Arctic, to assess the decomposition (i.e., percent mass loss) of the plant material after a 4-year incubation period. Decomposition was greatest for leaf litter, followed by twigs, and then root tissue of S. richardsonii at shallow depths. Further, root tissue (and to a lesser degree leaf tissue) of S. arctica was more susceptible to decomposition than that of S. richardsonii. Also, mass loss of S. arctica leaf tissue was greater at shallow soil depths compared to deeper soil depths. Hence, shrubification can impact Arctic decomposition dynamics.
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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 | 0.001 | 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".