Impact of grazing and conservation opportunities for nesting grassland birds in a community pasture
Bibliographic record
Abstract
Multiple bird species-at-risk nest on the ground in hayfields and pastures, making nests susceptible to inadvertent destruction from agricultural activity (e.g., trampling by livestock). To better understand the impact of Domestic Cattle (Bos taurus) grazing, we assessed the distribution and breeding status of nesting grassland birds in 2019 and 2020 at the Grey Dufferin Community Pasture, a ~234 ha pasture in southern Ontario, Canada. We estimated there were 86 male Bobolink (Dolichonyx oryzivorus) in the community pasture in 2019 and 100 in 2020 before grazing began; observed abundance decreased by 73% in fields after grazing in 2020. Eastern Meadowlark (Sturnella magna) maintained territories after grazing and fledged young in 67% (n = 21) of territories. Savannah Sparrow (Passerculus sandwichensis) was common across the community pasture before and after grazing occurred. We detected evidence of nesting more frequently in Bobolink and Savannah Sparrow territories in ungrazed than in grazed fields. Our results support previous research indicating nesting Bobolink often disperse from moderately to heavily grazed fields, whereas Eastern Meadowlark and Savannah Sparrow largely remain and renest. Despite the inadvertent negative impacts of cattle stepping or laying on nests and consuming vegetative cover, the community pasture provides areas for successful nesting, with Eastern Meadowlark faring better than Bobolink. Flexibility in the timing and duration of grazing in rotational grazing systems may enable strategic management in target fields (e.g., maintaining enough vegetation for nesting Bobolink). Information about the distribution and abundance of birds can be used to target particular fields for conservation.
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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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".