Carbon, Nitrogen, Phosphorus, and Extracellular Soil Enzyme Responses to Different Land Use
Bibliographic record
Abstract
Extracellular soil enzymes play a key role in soil organic matter decomposition and nutrient cycling. However, it is not fully understood how these enzymes respond to different land use. Long-term research studies were used to evaluate how diversified management practices affect extracellular enzymes driving C cycling [phenol oxidases (PO), peroxidases (PP), α-glucosidase (AG), β-glucosidase (BG), cellobiohydrolase (CB), β-1,-4-Nacetylglucosaminidase (NAG)], N cycling [leucine aminopeptidase (LAP)], and P cycling [phosphomonoesterase (PME)]. The soil pH, contents of total organic C, total N, mehlich-3 P, soil respiration and soil nitrogen supply capacity were also measured. Different land use included tillage frequency, tillage regimes, mineral N fertilization, crop rotations and liquid dairy manure. Compared to medium or high tillage frequency, low tillage frequency increased total organic C and total N and soil respiration as well as NAG and PME activities, whereas it decreased soil nitrogen supply, mehlich-3 P, and soil pH, as well as PO, PP, AG, BG, CB, and LAP activities. Non till was associated with lower PP and PO activities than moldboard plow. Nitrogen fertilization decreased soil pH and PO activity but increased PME activity. Barley ( Hordeum vulgare ) in rotation with forage increased total organic C, total N, soil nitrogen supply and soil respiration by 31, 21, 44, and 33%, respectively, in comparison with barley in monoculture. The application of liquid dairy manure increased soil pH, total N and soil nitrogen supply and soil enzyme activities (AG, BG, NAG) in comparison to the mineral N fertilizer. When principal component analysis was performed, soil pH, PO, PP, CB, LAP, and PME were grouped in the first component, which explained the highest variance. This is the core group controlling the C, N, and P cycling. The activities of C, N, and P acquiring enzymes, soil nitrogen supply and soil respiration were related to changes in soil total C and N, and extractable P contents across a broad range of management practices. Increased PO and PP activities reflect total C decline.
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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 | 0.001 |
| 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".