Patterns of decomposition and carbon, nitrogen, and phosphorus dynamics of litter in upland forest and peatland sites in central Canada
Bibliographic record
Abstract
We tested whether upland or peatland location affected rates of litter decomposition and nutrient dynamics. We examined the patterns of mass loss and carbon (C), nitrogen (N), and phosphorus (P) gain, retention, or loss in 11 forest tissues over 6 years at three upland and three peatland sites in the Low Boreal, High Boreal, and Low Subarctic zones of central Canada. After 6 years of decomposition, the average litter mass remaining ranged from 35% for fescue grass to 75% for western redcedar needles and 94% for wood blocks placed on the soil surface, with exponential decay coefficients (k) of 0.16, 0.05, and 0.01, respectively. At one pair of sites, the mass remaining and the k values indicated that faster decomposition occurred in the upland site than in the nearby peatland site. The reverse was the case in a second pair. No overall pattern was apparent in the third. In general, Douglas-fir needles decomposed significantly faster in peatland than upland sites, and the reverse pattern occurred for bracken fern. Most foliar litters retained their original N mass and lost P as they decomposed. There were few major differences between N and P dynamics in litters decomposing at upland and peatland sites, though N and P retention in some cases was greater at the peatland sites. These results suggest that longer term (>6 years) differences in decomposition rate and differences in litter quality account for larger C accumulation in peatland than in upland soils.
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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 | 0.002 | 0.001 |
| 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".