Soil and Groundwater Quality under a Cattle Feedlot in Southern Alberta
Bibliographic record
Abstract
Abstract Environmental concerns related to manure often focus on land application and the negative effects on soil and water quality. However, there is also potential for contamination of soil and water directly from feedlot sites. The objective of this study was to determine if a newly constructed feedlot in southern Alberta would change soil and groundwater quality under the feedlot within the first four years of operation. A cattle feedlot was constructed at the Agriculture and Agri-Food Canada Research Centre in Lethbridge, Alberta, in 1995 and 1996. Sixteen groundwater wells were installed at the feedlot in 1996. Groundwater chemistry and microbiology were monitored from 1996 to 2000, which included a baseline period of 3 months at the start before the feedlot was stocked with cattle. Soil samples (0- to 0.15-m, 0.15- to 0.3-m, and every 0.3-m to 1.5-m depth) were collected in 1996 and 1999. Mean water-table depth ranged from 1.23 to 2.50 m. Some soil chemical properties, PO4-P, NO3-N, NH4-N and K, were only significantly affected in the top 0.15-m layer. Other soil properties, EC, SAR, SO4-S, Mg, Ca and Na, increased significantly to a depth of 0.6 m. Chloride content increased significantly to a depth of 1.5 m. Groundwater analysis indicated that contaminants had leached to the water table. Chloride concentrations, E. coli counts and total coliform counts increased in the wells within the pen area, whereas there was little change in the wells outside the pen area.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".