Impacts of grazing management options on pasture and animal productivity in a Heteropogon contortus (black speargrass) pasture in central Queensland. 1. Pasture yield and composition
Bibliographic record
Abstract
An extensive grazing study was conducted between 1988 and 2001 in a Heteropogon contortus (black speargrass) pasture in central Queensland. The study was designed to measure the effects of stocking rate on native pasture, native pasture with legume oversown, and native pasture with animal diet supplement/spring burning on pasture and animal production. Summer rainfall throughout the study was below the long-term mean. Mean annual pasture utilisation ranged from 13% at 8 ha/steer up to 61% at 2 ha/steer. Increasing stocking rate treatments reduced total pasture yields while total yields in legume oversown treatments were similar to those in native pasture at the same stocking rate. When spring burning was possible, total yields were reduced in the subsequent autumn. Increasing stocking rate in native pasture tended to reduce H. contortus and Bothriochloa bladhii, increased the composition of intermediate species, such as B. decipiens and Chloris divaricata, and also changed the frequencies of a range of minor species. Oversowing legumes resulted in Stylosanthes scabra cv. Seca increasing from <1% of pasture composition in 1988 to 50% in 2000 and was associated with a reduction in H. contortus and changes in the frequencies of some minor species. Stocking rates heavier than 4 ha/steer resulted in annual pasture utilisation greater than 30% and were unsustainable because they reduced total yield and resulted in undesirable changes in species composition. It was concluded that pasture production was sustainable when stocking rates were maintained at 4 ha/steer, which equates to 30% annual pasture utilisation, and through the judicious use of spring burning.
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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".