Pasture type and fertilization effects on soil chemical properties and nutrient redistribution
Bibliographic record
Abstract
Soil samples were collected from beef pastures varying in species composition and fertilizer inputs after being grazed by cow-calf pairs for 4 yr (1995-1998) near Brandon, Manitoba. The objective of this experiment is to examine the impact of 4 yr of continuous rotational grazing on soil chemical properties and nutrient redistribution in mixed alfalfa-grass and pure-grass pastures with or without fertilization. Pastures were established on an Orthic Black Chernozemic, fine sandy-loam soil. Compared with N-fertilized pure-grass pastures, alfalfa-grass pastures had greater seasonal soil mineral-N supply, and tended to have higher total soil C, N and organic C. In grazed systems in this environment, the use of alfalfa as the primary N source may be more profitable and sustainable than using fertilizer N. However, considering the seasonal changes in soil nitrification rate observed in alfalfa-grass pastures, caution needs to be taken when stands with high legume content are used to maximize animal performance, because this may increase the risk of N losses into the environment. Fertilization over a 5-yr period (1994-1998) tended to lower surface soil pH. Application of P significantly increased soil “extractable” P levels in the top 15-cm soil layer. However, K fertilization only increased surface soil “extractable” K slightly compared with unfertilized pastures. There was also no effect of S application on soil “extractable” S. Zone effects on soil mineral N and soil “extractable” P, K and S were limited to the surface (0–7.5 cm). For mineral N, the zone effect seemed to be more pronounced in first rotation than in second rotation. The magnitude of K redistribution was greater than for S and P due to higher K intake and excretion. Use of rotational stocking with short grazing periods appears to have resulted in a relatively even redistribution of nutrients derived from animal excreta. Key words: Grazing, beef pasture, nitrogen dynamics, sustainability
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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) | 0.001 | 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".