Decadal manure substitution reshapes microbial communities to drive plant and microbial carbon accumulation in soil carbon fractions
Bibliographic record
Abstract
The transformation of organic residues into particulate organic carbon (POC) and mineral-associated organic carbon (MAOC) governs soil organic carbon (SOC) storage and stability. However, how long-term manure use steers plant- and microbe-derived SOC fractions in paddy soils remains unclear. The SOC in paddy soil was evaluated by measuring amino sugars, lignin and enzyme activities from a 12-yr field trial (rice–wheat rotation) with no fertilizer, 100% mineral N fertilizer, and pig manure (50% and 100% replacement of N fertilizer). Compared to mineral N, the 100% pig manure treatment increased SOC by 26%, mainly through enhanced lignin input and microbial necromass accumulation, leading to significantly higher POC and MAOC levels. Manure application, compared to mineral N, promoted rice growth, which increased total organic C input and nutrient availability, thereby selectively favoring r -strategist bacteria, as reflected by a lower vanillyl acid-to-aldehyde ratio, a higher ratio of cellulose- to lignin-degrading enzyme activity, and greater lignin and bacterial necromass production. In contrast, the combined NPK and pig manure treatment increased the proportion of MAOC in total SOC by 7% compared to the 100% manure treatment, yet this came with enhanced lignin degradation, a lower bacterial phospholipid fatty acid (PLFA)/fungal PLFA ratio, and greater abundance of K -strategist fungi, resulting in less POC accumulation. These findings demonstrate that substituting mineral N with pig manure reshapes microbial community, enhancing the microbial transformation of plant- and microbe-derived residue into stable and labile SOC pools, and more effectively promotes SOC sequestration and persistence than mineral fertilization alone in paddy systems.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".