Vegetation Composition, Forage Biomass and Soil Seed Bank of a Continuously Grazed Rangeland Site in Tropical Sub-Humid Environment, Tanzania
Bibliographic record
Abstract
Most rangelands along the agro-pastoral villages of Tanzania are yearlong grazed and at various states of degradation. These rangelands contribute to over 60% of the meat and milk production in the country. An inventory was conducted to assess the status of grazing resources in a typical agro-pastoral village of Tanzania having communal rangelands. Systematic random sampling techniques were employed whereby line transects and quadrat frame were used following standard procedures to collect samples and undertake field measurements for both vegetation and soil parameters. The vegetation cover for desirable pasture species, undesirable pasture species and litter were 67.7%, 10.5% and 9.4%, respectively. The soil bare patches covered 12.3 % of the surveyed rangeland site. The most dominant grass species were Enteropogon macrostachyus, Bothriochloa insculpta and Heteropogon contortus. Forage dry matter (DM) yield was 806.8 kg DM/ha. Tree density was 1500 trees/ha and the total canopy cover was 63.49%. Combretum collinum was the most dominant tree species. Soil bulk density, pH, organic carbon, nitrogen, phosphorus and potassium were 1.4 g/cm3, 6.3%, 1.14%, 0.09%, 0.89 mg/kg and 0.33 g/kg, respectively. A total of 11 dicotyledonous species mainly forbs and 9 monocotyledonous species including two perennial grasses were revealed from the incubated soil samples. The findings of this study demonstrate that the communal grazing areas have low pasture productivity, poor soil seed-bank and high cover of woody plants mainly bushes. In order, to improve forage biomass at the study site and elsewhere with similar environments selective bush clearing and re-seeding should be considered.
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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 | 0.001 | 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".