Soil quality and plant yield under dryland and irrigated winter forage crops grazed by sheep or cattle
Bibliographic record
Abstract
In New Zealand, the winter grazing of standing forage crops combines high animal stocking densities with soil water and climatic conditions conducive to soil compaction and pugging deformation. The extent of soil damage under winter forage cropping practices and impact of management factors such as stock type and irrigation on soil quality is relatively unknown. A research trial was established, on a Pallic soil type (Aeric Fragiaquept) in the North Otago Rolling Downlands of New Zealand, to compare cattle v. sheep and dryland v. irrigation management. Kale, Swedes, and triticale were direct-drilled in 3 consecutive years and soil physical (macroporosity, bulk density, structural condition score), chemical (total C, total N, C : N ratio), and biological (mineralisable N, mineralisable C, and earth worm mass and numbers) properties were assessed annually post grazing in midwinter. Increased soil compaction was evident following grazing of winter forage crops, with lower macroporosity (P < 0.01) measured at 0–50 mm under cattle grazing compared with sheep grazing for 2 of 3 years and greater bulk density (P < 0.05) measured under cattle grazing for all years. However, there was no affect of stock type on crop yield for all 3 forage crops as a result of the measured differences in soil compaction. There were few differences between treatments or through time in soil chemical or biological properties following 3 years of continuous winter forage cropping as pools of C and N are slow to change under a no-tillage cropping regime and not necessarily measurable over a relatively short time frame.
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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 | 0.001 |
| 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".