Do decomposing Scots pine, Norway spruce, and silver birch stems retain nitrogen?
Bibliographic record
Abstract
The contents of nitrogen (N) have generally been observed to increase in the early stages of decomposition in coarse woody debris and then to decrease slowly. This is potentially an important mechanism of nutrient retention in ecosystems after disturbances. We studied N dynamics in decomposing Scots pine ( Pinus sylvestris L.), Norway spruce ( Picea abies (L.) Karst.), and silver birch ( Betula pendula Roth.) stems in Finland. The oldest stems had decomposed for 34 (spruce and birch) or 45 (pine) years. Concentrations of N in both fallen logs and standing snags increased and C/N ratios decreased with time, and birch had significantly higher N concentrations and lower C/N ratios than pine and spruce. Even though increased N contents were observed in some cases, N was generally already released in the early stages of decomposition and more rapidly from birch than from conifers. Based on model analysis, from 40% (pine and spruce) to 50% (birch) of initial N was released within 30 years. The results suggest that decomposing stems of especially Scots pine and Norway spruce retain N rather effectively in boreal forest ecosystems and form a long-term, small but steady N pool with a slow release rate.
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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 | 0.001 |
| 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".