Active carbon pools and enzyme activities in soils amended with de-inking paper sludge
Bibliographic record
Abstract
Application of paper mill wastes generally improves soil organic matter content, biological activity and physical properties. However, the impact of large application rates (>50 Mg ha −1 ) on soil microflora and their activity has not been assessed. A field study was undertaken on a well-drained clay loam and a poorly drained silty clay loam amended with de-inking paper sludge (DPS) at rates of 0 (control), 50 or 100 Mg ha −1 . K 2 SO 4 -extractable C (C ext ), soil water content (SWC), microbial biomass C (MBC) and different enzyme activity rates were periodically measured in soil during 1075 d following DPS incorporation. Compared with control soils, C ext content increased by 100 to 200%, and soil water content increased by 35% following incorporation of DPS at 100 Mg ha −1 . Those differences decreased in time as DPS decomposed. Soil MBC increased proportionally with the rate of DPS amendment and was about twice the amount in soils amended with 100 Mg ha −1 compared with the control. Microbial quotient (ratio of MBC to total soil organic C) was greater in DPS-amended than in control soils until day 370, reflecting the input of labile C from DPS. Compared with the control, fluorescein diacetate hydrolysis and alkaline phosphatase activity rates increased by 40 to 100% when adding 50 Mg DPS ha −1 . However, the rates were similar for 50 and 100 Mg DPS ha −1 . We concluded that DPS promoted microbial growth and activity in the soil by improving C and water availability. However, levelling off of enzyme activity at a DPS loading rate above 50 Mg ha −1 could reflect changes in soil microbial community, or some kinetic interference or nutrient deficiency induced by excessive C input. Key words: Microbial biomass, active carbon, soil enzyme, paper sludge
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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 | 0.001 |
| 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 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".