Reforestation and slope-position effects on nitrogen, phosphorus pools, and carbon stability of various soil aggregates in a red soil hilly land of subtropical China
Bibliographic record
Abstract
The impact of slope position on forest restoration processes may dominate the interaction among topsoil aggregates, nutrients, and organic carbon (C) stability following reforestation on degraded hilly land. Six paired plots of shrubland and Masson pine (Pinus massoniana Lamb.) plantation reforested on shrubland were selected at different positions along a 25° slope in subtropical China. Soil and ecosystem nitrogen (N), phosphorus (P), and organic C stocks were quantified using a combination of excavation, harvest, and modeling methods. Carbon stability in differently sized soil aggregates was measured using dry sieving and closed-jar alkali-absorption methods. Reforestation increased total ecosystem C, N, and P stocks, but did not alter soil C and P stocks, and decreased N stocks at 0–75 cm soil depth by 18%. The shift from shrubland to forests increased organic C stability for various soil aggregates, particularly with a mean increase of 34% and 30% at lower and middle slope positions, respectively. The slope-position effect was largely attributable to the increased mean mass diameter of soil aggregates and the reduced organic C mineralization potential in larger soil aggregates relative to smaller soil aggregates. Soil aggregates had more stable organic C in forests than in shrubland due to increase in the carbon to nitrogen (C/N) and carbon to phosphorus (C/P) ratios with reforestation. Slope position influenced restoration effectiveness in the red soil hilly region.
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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 | 0.001 |
| Science and technology studies | 0.000 | 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".