Effects of Cattle Grazing on Birds in Interior Douglas-Fir (Pseudotsuga Menziesii) Forests of British Columbia
Bibliographic record
Abstract
Livestock grazing is a dominant land use across North America and although the effects of grazing on birds have been studied in grassland, shrubland, and riparian habitats, studies of the effects in forests are rare. We investigated the effects of cattle grazing in forests on vegetation, the relationships between vegetation characteristics and the abundance of foraging and nesting guilds of birds, and the overall effects of grazing on the bird community in the Interior Douglas-fir (Pseudotsuga menziesii) biogeoclimatic zone of British Columbia. Cattle grazing was associated with reduction in ground vegetation height and grass cover, and increases in the number of shrubs and saplings. Bark insectivores, foliage insectivores, cavity nesters, and shrub/tree nesters all responded positively to sapling density. However, this translated into few overall effects of cattle grazing on birds, with only bark insectivores exhibiting greater abundance on grazed areas. Grazed areas also had fewer aerial insectivores but the mechanism driving this remains unclear. Current forest grazing practices at our study sites appear to have few negative effects on bird abundance and diversity, with the possible exception of aerial insectivores. Study of additional sites is required to assess if forest grazing exerts similar effects throughout the Interior Douglas-fir forest. Furthermore, study of the effects of forest grazing on productivity and survival of birds is needed.
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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 | 0.000 |
| 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".