Changes in mass, carbon, nitrogen, and phosphorus in logs decomposing for 30 years in three Rocky Mountain coniferous forests
Bibliographic record
Abstract
Estimates of decomposition rates of coarse woody debris (CWD) and fluxes of nutrients therein are essential components of carbon (C) and nutrient budget models. In a 30-year field experiment, we periodically measured mass remaining and nutrient concentrations in log segments of pine, spruce, and fir in natural, mature coniferous forests in Alberta, Canada. The predicted turnover times (t 95 ; years) were 43–44 years for pine, 42–60 years for spruce, and 38–46 years for fir. Extrapolating from best-fit models, we predict that decomposition of these logs would be complete within 50–60 years. The ratio of carbon to nitrogen (C:N) declined for most of the decomposition period, and ratios of the three species converged at <200 at 90% mass loss. Net release of N occurred only after logs had lost 90% of their original C and C:N had declined to <200. The ratio of carbon to phosphorus (C:P) declined and converged at 500–1000 at 90% mass loss. There was no evidence of net P release from logs even at 90% mass loss. It may be possible to estimate the amounts of N and P that will be incorporated into decaying logs based on the extent to which their initial C:N differs from 200 and their initial C:P differs from 500.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".