Grazing exclosures reveal divergent patterns of change in bunchgrass grasslands of Western Canada
Bibliographic record
Abstract
Thirty-six long-term (14–83 years) cattle grazing exclosures and adjacent grazed pastures spanning a climatic gradient from cooler–wetter to warmer–drier growing seasons in south-central British Columbia were compared for temporal vegetation change. Trajectories of temporal vegetation change from non-metric multidimensional scaling were mostly scattered for the grazed areas, but more directed toward the dominant grasses, primarily rough fescue (Festuca campestris) or Kentucky bluegrass (Poa pratensis), for the exclosures. Plant community differences, detected only after 10 years of grazing exclusion, were primarily due to structural shifts in overall species cover related to growth increases of the dominant grasses inside exclosures. Species richness remained unchanged between the first and last sampling dates in both grazed areas and exclosures, with both treatments showing moderate degrees (15%–30%) of turnover in species composition. Shannon diversity declined in both treatments as a result of the structural changes in species cover. The results highlight the value of repeated monitoring of long-term exclosures for assessment of grassland resiliency to grazing. Further studies of the interaction of grazing and climate are needed for a more complete understanding of the ongoing vegetation change.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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".