Initial rates and limit values for decomposition of Scots pine and Norway spruce needle litter: a synthesis for N-fertilized forest stands
Bibliographic record
Abstract
Nitrogen fertilization increased concentrations of N, P, S, and K in Scots pine (Pinus sylvestris L.) needle litter, and in those of N, S, and Ca in Norway spruce (Picea abies (L.) Karst.). Lignin concentrations increased for both species. Initial rates and limit values for decomposition were estimated using a simple equation. For Scots pine litter, initial rates ranged between 0.0618 and 0.2986%/day with P, K, N, and Mg being positively related, but lignin and Ca negatively related. For Norway spruce, initial rates were low (0.0455-0.1007%/day) and positively related with initial concentrations of water solubles, K, and P but negatively with N, Ca, and lignin. Limit values for Scots pine litter ranged from 53.1 to 94.3% decomposition in fertilized plots and from 71.5 to 93.2% in controls. They were negatively related to N concentrations and positively to Mn and Ca. Limit values for Norway spruce litter ranged from 53.8 to 74.3% in controls and from 48 to 71.3% in fertilized plots and were positively correlated to Mn and Ca but not to N. The paper concludes that N fertilization will increase the fraction of Scots pine litter that accumulates as humus but not for Norway spruce.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".