Response of Antelope Bitterbrush Shrubsteppe to Variation in Livestock Grazing
Bibliographic record
Abstract
Shrubsteppe ecosystems in the Intermountain West have suffered extreme alteration from a variety of factors. Using a retrospective approach, I studied the effects of horse and cattle grazing at the northern edge of the range in southern British Columbia, Canada, where the shrubsteppe is not as heavily altered and ungrazed sites remain in areas dominated by antelope bitterbrush (Purshia tridentata). I measured shrub and understory cover at 10 sites that were either ungrazed, lightly grazed, or heavily grazed. Cover of antelope bitterbrush decreased with grazing, and cover of big sagebrush (Artemisia tridentata) increased with grazing intensity. I sampled 72 species of vascular plants in the understory. Livestock grazing resulted in more bare soil, especially at sandy rather than rocky sites, and in quadrats located in the interspaces between shrubs. More bare soil was associated with less spikemoss (Selaginella spp.) and less microbiotic crust cover. Of the 3 most common bunchgrasses, sand dropseed (Sporobolus cryptandrus) was associated with more bare soil but only at sites without spikemoss. Red three-awn (Aristida purpurea var. longiseta), which grew best without litter or microbiotic crust, was most commonly found with spikemoss. Needle-and-thread grass (Hesperostipa comata), the most palatable abundant bunchgrass, was affected by livestock grazing, with shrub canopy cover offering some protection from grazers at the most heavily grazed sites. Rangeland management prescriptions in this area should take soil differences into account, with sandy soils being more prone to overgrazing and disturbance of the microbiotic crust cover than rocky soils.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".