Effects of different amendments on aggregate stability and microbial communities of coastal saline–alkali soil in the Yellow River Delta
Bibliographic record
Abstract
Abstract Organic amendments have been widely used in coastal saline–alkali soil remediation; however, the mechanisms involved and the interactions between organic and inorganic amendments are still unclear. In this work, furfural residue (particulate; C/N ratio: 51.87; O‐alkyl C + di‐O‐alkyl C: 42.35%, aromatic C: 40.89%) and black liquor (dissolved; C/N ratio: 3.11; O‐alkyl C + di‐O‐alkyl C: 32.20%, aromatic C: 28.32%) were tested to examine their effects on chemical properties, water‐stable aggregate fractions, chemical compositions of solid‐state soil organic matter (SOM), gloaming‐related soil protein contents, and microbial communities of coastal saline–alkali soil under a 400‐day incubation experiment. Furthermore, organic amendments mixed with mineral amendment (4:1) were employed to explore the interactions between organic and inorganic amendments. Furfural residue had stronger and longer effects on soil macroaggregate stability (~240 days, intense) than black liquor (~15 days, weak), and mineral amendment addition had a positive effect on the stability of microaggregates. Our results revealed that qualities (primary form, C/N ratio, and chemical composition) of organic amendment which can change microbial communities by increasing soil C/N ratio and effective chemical compositions of solid‐state SOM, are the key factors in promoting the rapid formation and longer stability of coastal saline–alkali soil aggregates. Moreover, inorganic amendment addition can further improve the formation and stability of microaggregates rather than those of macroaggregates. This study provided a much‐needed technical basis for remediation of coastal saline–alkali soil.
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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 | 0.000 | 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".