Evaluation of cattle bedding and grazing BMPs in an agricultural watershed in Alberta
Bibliographic record
Abstract
This paper highlights the environmental impacts of implementing beneficial management practices to address cattle bedding and direct access to the creek in a study watershed in southern Alberta, Canada. Approximately 35 cow-calf pairs grazed 194 ha of grass forage and had direct access to the creek in the spring and summer. During winter, the cattle were fed adjacent to the creek at an old bedding site. The practice changes included off-stream watering, bedding site relocation and fencing for rotational grazing. The cost was $15,225 and 60 h of labour. Four years of data were used in a before-and-after experimental design to evaluate the practice changes. After two years of post-implementation monitoring, riparian assessments showed an increase in plant diversity, but no change in the percent cover of the riparian species Salix exigua and Juncus balitus and a decrease in Carex sp. (P < 0.05). Water quality monitoring showed a decrease in the difference between upstream and downstream concentrations of total phosphorus, total dissolved phosphorus, total nitrogen, organic nitrogen and Escherichia coli (P < 0.10). These results showed that improved environmental changes in riparian and water quality can be measured following the implementation of beneficial management practices for cattle bedding and grazing.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".