Hydraulic Conductivity and Aggregation of Fine-Textured Soil Under Intensive Cattle Grazing
Bibliographic record
Abstract
Information on hydraulic conductivity and macro- and micro-aggregate stability is needed for evaluating the ease with which soils slake and erode when in contact with water. In fine-textured soils, it will provide information on ponding of water and decrease in hydraulic gradient with wetting. This study was conducted to determine changes in hydraulic conductivity and macro- and micro-aggregate stability of a fine-textured submerged soil under intense cattle grazing for 15 years. Hydraulic conductivity of the cattle grazing soil ranged from very slow (0.46 cm hr-1) to slow (19.56 cm hr-1) in the top 0-25 cm depth, and attained near zero permeability (0.15 cm hr-1) before 75 cm depth. Permeability was rapid (21.1 to 30.06 cm hr-1) throughout the profile in the non-cattle grazing soil. Organic residues from cattle grazing activities raised the soil total organic carbon to as high as 72 g kg-1 in the top 0-25 cm depth. Wet trampling of organic residues from cattle excreta induced greater soil swelling and loss of soil strength resulting in low aggregated silt and clay (ASC) and clay flocculation index (CFI) within the 25-75 cm depth. Clay dispersion index (CDI) showed significant negative (P < 0.05) relationships with mean weight diameter (MWD) of water stable aggregates and saturated hydraulic conductivity (r = -0.631 and -0.596 respectively). Soil parameters controlling water storage and infiltration in such soils need to be increasingly studied to increase the area of land available for crop production and reduce soil erosion since such soils usually have high chemical fertility status.
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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 | 0.001 | 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 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".