Influences of various forms of nitrogen additions on carbon mineralization in natural secondary forests and adjacent larch plantations in Northeast China
Bibliographic record
Abstract
Soil organic matter decomposition, a major process that affects soil carbon (C) storage, is controlled by the available nitrogen (N) in soils. However, little is known about the effects of the various forms of N input on organic matter decomposition in typical temperate forest types such as secondary forests and larch plantations. A 56-day laboratory incubation experiment was performed to determine the effects of dominant N forms (ammonium dominant = NH4+; ammonium nitrate dominant = NH4NO3; and nitrate dominant = NO3−) and four N levels (control = no N added; low N = 25 mg N·kg soil−1; medium N = 50 mg N·kg soil−1; and high N = 75 mg N·kg soil−1) on soil C mineralization in secondary forest and larch plantation soils. The results indicated that the addition of N inhibits C mineralization, regardless of the form of N applied in the secondary forest soil, whereas NH4+-dominant soil decreased C mineralization in the larch plantation soil. Furthermore, among the various forms of N, the addition of NH4+ reduced C mineralization the most compared with NO3– and NH4NO3 additions in the secondary forest soil. Additional N generally suppressed phenol oxidase activity but had no effects on activities of exoglucanase, β-glucosidase, and N-acetyl-β-glucosaminidase or soluble organic C in the secondary forest soil. The decrease in phenol oxidase activity that was associated with the addition of N is likely to have an effect on soil C mineralization. We also observed that soil pH decreased with the increasing rate of N input in the secondary forest soil, which indicates that soil C mineralization may be sensitive to the amount of N through changes in soil pH. Overall, the addition of N resulted in changes in soil C mineralization that depended on the form of the N input and the forest type. The application of NH4+-dominant N influenced soil C dynamics in the secondary forest and larch plantation soils in this short-term experiment.
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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 | 0.001 | 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) | 0.000 | 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".