Impacts of grazing management options on pasture and animal productivity in a Heteropogon contortus (black speargrass) pasture in central Queensland. 2. Population dynamics of Heteropogon contortus and Stylosanthes scabra cv. Seca
Bibliographic record
Abstract
The dynamics of Heteropogon contortus and Stylosanthes scabra cv. Seca populations were studied in a subset of treatments in an extensive grazing study conducted in central Queensland between 1988 and 2001. These treatments were 4 stocking rates in native pasture and 2 of these stocking rates in legume oversown and supplement/spring burning treatments. For the 1999–2000 summer, population data for H. contortus in 5 of these native pasture and supplement/burning treatments were compared with those for an additional burnt treatment. Seasonal rainfall throughout this study was below the long-term mean and mean annual pasture utilisation ranged from 24 to 61%. Increasing stocking rate from 5 to 2 ha/steer in native pasture reduced H. contortus plant density. Increasing stocking rate reduced seedling recruitment as a result of its effect on soil seedbanks. Seedling recruitment was the major determinant of change in plant density, although some individual H. contortus plants did survive throughout the study. Burning in spring 1999, particularly at light stocking rate, promoted seedling recruitment above that in both unburnt native and legume oversown pasture and resulted in increased H. contortus plant density. In the legume oversown treatments, S. scabra cv. Seca density increased rapidly from 15 plants/m2 in 1988 to 140 plants/m2 in 2001 following a lag phase between 1988 and 1993. This increased S. scabra density was associated with an eventual decline in H. contortus plant density through reduced seedling recruitment. It was concluded that H. contortus population density is sustainable at stocking rates of 4 and 5 ha/steer (30% pasture utilisation) and that spring burning at light stocking rate can promote H. contortus populations. Increasing densities of S. scabra need to be managed to prevent its dominance.
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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".