Decay and nutrient dynamics of coarse woody debris in northern coniferous forests: a synthesis
Bibliographic record
Abstract
We synthesize current information on input, accumulation, and decay of coarse woody debris (CWD) compared with other aboveground litter to assess the role of CWD in the nutrient cycles of northern coniferous forests. CWD contributes between 3% and 73% of aboveground litter input, but <20% of N, P, K, and Ca. Although CWD accounts for up to 54% of accumulated organic matter (including forest floor and soil), it contributes <5% of the N, <10% of the P, and <25% of the K, Ca, and Mg. Decay rates of CWD in northern forests range from 0.0025 to 0.071 year -1 . Nitrogen or P concentrations in CWD increase during decay, depending on the initial N/P ratio, which eventually converges at about 20. CWD is initially a sink for N and (or) P, whichever is least available, but becomes a source later in decay. CWD contributes <5% of the N released annually. There is little evidence that CWD retains significant amounts of excess N following disturbance. We conclude that CWD is of minor importance in the nutrient cycles of northern coniferous forests, and that guidelines for CWD retention should be based on other perceived benefits of CWD.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".