Hydrological Properties of a Clay Loam Soil after Long‐Term Cattle Manure Application
Bibliographic record
Abstract
Limited information exists on the effect of long-term application of beef cattle (Bos taurus) manure on soil hydrological properties in the Great Plains region of North America. A site on a clay loam soil (Typic Haploboroll) was used to examine the effect of manure addition on selected soil hydrological properties in 1997 and 1998. The manure was annually applied in the fall for 24 yr at one, two, and three times the recommended rates (in 1973) under dryland (0, 30, 60, and 90 Mg ha(-1) wet basis) and irrigation (0, 60, 120, and 180 Mg ha(-1)). Manure significantly (P < or = 0.05) increased soil water retention (0-5 and 10-15 cm) by 5 to 48% compared with the control at most potentials between 0 and -1500 kPa. Field soil water content (0-5 and 10-15 cm) was increased by 10 to 22% in the summers of 1997 and 1998. Manure increased ponded infiltration by more than 200% at 90 Mg ha(-1) under dryland (1998) and at rates > or = 120 Mg ha(-1) under irrigation (1997). Field-saturated hydraulic conductivity (Kfs) of surface soil (1-cm depth) was significantly increased by 76 to 128% under dryland (1998) and irrigation (1997), as were number of pores > 1120 microm in diameter (37-128% increase). In contrast, manure rate had little or no effect on unsaturated hydraulic conductivity [K(psi)] values (-0.3, -0.5, -0.7, and -1.0 kPa) in 1997 and 1998. Overall, soil hydrological parameters generally had a neutral or positive response to 24 yr of annual manure addition.
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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) | 0.000 | 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".