Response of plant community abundance and diversity during 10 years of cattle exclusion within silvopasture systems
Bibliographic record
Abstract
The effects of cattle ( Bos taurus L.) grazing on upland plant communities in forested rangelands are poorly understood. Cattle interactions with plant communities were studied in intensively managed (precommercially thinned (PCT) and repeatedly fertilized) silvopasture systems in young lodgepole pine ( Pinus contorta Dougl. ex Loud. var. latifolia Engelm.) forests. We investigated the response of plant community abundance and diversity to cattle grazing and how these responses were affected by PCT and repeated fertilization. The study was conducted inside and outside cattle exclosures over 10 years in two regional replicates in south-central British Columbia, Canada. PCT and repeated fertilization increased both the amount and quality of forage. Effects of cattle grazing on plant community abundance and diversity were variable and significantly influenced by the nutrient status of the site. In fertilized stands, cattle grazing increased species richness and diversity, particularly for the herb layer, although these treatment effects often took several years to be expressed. In unfertilized stands, cattle grazing did not significantly reduce herb or shrub volumes; however, species richness and, to a lesser extent, diversity of the shrub layer declined. In a landscape context, management strategies for silvopasture should promote heterogeneity for conservation of plant diversity through a variety of grazing pressures, as well as forest enhancement treatments such as PCT and repeated fertilization.
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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 | 0.000 | 0.000 |
| 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".