Effects of open-range cattle grazing on deciduous tree regeneration, damage, and mortality following patch logging
Bibliographic record
Abstract
The impact of summer cattle grazing on deciduous tree regeneration within uncut forests, clearcuts, partially harvested areas, and in-block haul road habitats was examined in four experimental pastures of central Alberta during 2008 and 2009. Sampling of 233 field plots, both inside and outside cattle exclosures, was used to document sapling densities, height, and type of damage. Tree densities (primarily aspen (Populus tremuloides Michx.)) differed among habitats but less so with exposure to cattle. Densities were greatest in clearcuts, followed by partially harvested areas and then uncut forest and haul roads. While exposure to cattle reduced total tree regeneration, sapling densities and sizes remained sufficient to meet postharvest standards for deciduous forest regeneration in Alberta, even with exposure to cattle. Cattle damage in harvested areas was primarily from browsing (≤3.2% of saplings), with proportionally more trees affected in uncut forests (8.6%). Browsing was particularly high on balsam poplar (Populus balsamifera L.) (25%) during 2008. Although sapling damage increased with high cattle stocking in 2008 (to 10.5%), total mortality was limited to 15.5% through 2009. These findings show that despite cattle impacts to some saplings, damage levels were insufficient to alter deciduous regeneration, highlighting the compatibility of cattle grazing and sustainable forest management on public lands in this region.
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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".