Influence of fertilization and organic amendments on organic‐carbon fractions in Heilu soil on the loess plateau of China
Bibliographic record
Abstract
Abstract The influence of fertilization on organic‐carbon fractions separated by density and particle size in Heilu soil (Calcic Kastanozems, FAO) was investigated in a 20‐year (1979–1999) long‐term experiment on the Loess Plateau of China. Compared to an unfertilized treatment, N application alone did not increase total organic carbon (TOC) and its fractions of density and particle size. However, the treatment of N + P fertilization significantly increased salty‐solution–soluble organic carbon (SSOC), microbial biomass C (MB‐C), and organic C associated with fine silt. When manure was applied alone and in combination with N and P fertilizer, the light fraction of organic C (LFOC), SSOC, and MB‐C were increased significantly, and the TOC was as high as that of a native Heilu soil. Organic C associated with different particle‐size fractions was also increased significantly, and the allocation of C among the fractions was altered: the proportions of C in sand (>50 μm), coarse‐silt (20–50 μm), and fine‐clay (<0.2 μm) fractions were increased whereas fine‐silt (2–20 μm) and coarse‐clay (0.2–2 μm) fractions were decreased. It is concluded that N fertilizer alone is not capable of restoring organic‐matter content in the Heilu soils of the Loess Plateau and that C‐containing material like manure and straw is necessary to produce significant increase in soil organic carbon in these soils.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 teacher head, 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".