Nitrogen availability in forest floors of three tree species on the same site: the role of litter quality
Bibliographic record
Abstract
Forest floor samples from a 25-year-old plantation of three tree species (Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco), lodgepole pine (Pinus contorta Dougl. var. latifolia Engelm.), and paper birch (Betula papyrifera Marsh.)) growing on the same site were incubated (aerobically) in the laboratory for 29 days. Rates of N mineralization in the forest floors of Douglas-fir (165.1 µg/g) was significantly greater than either birch (72.9 µg/g) or lodgepole pine (51.2 µg/g). Douglas-fir forest floors also had the highest N concentration, lowest C/N ratio, and highest NH4-N concentrations, followed by paper birch and lodgepole pine. Douglas-fir forest floors also mineralized more N per unit of either N or C than the other species. There were no differences in rates of CO2-C mineralization in forest floors among the three species. Nitrogen mineralization rates were positively correlated with the N concentration of the forest floor (r2 = 0.81) and also with the C/N and NH4-N concentration of the forest floor. Nitrogen concentration, C/N, and lignin/N of foliar litter were poor predictors of N mineralization rates resulting from Douglas-fir litter having the lowest N concentrations in litter but the highest rates of net N mineralization in the forest floor. Nitrogen mineralization in the forest floor was negatively correlated (r2 = 0.67) with the lignin concentration in foliar litter. Douglas-fir litter had low lignin concentrations, which may allow more of the mineralized N to remain in inorganic forms rather than being bound in humus. Our results suggest that a component of Douglas-fir might improve N availability in coniferous forest floors.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".