Effects of cattle stocking rate and years grazed on songbird nesting success in the northern mixed-grass prairie
Bibliographic record
Abstract
Grassland bird species are declining more quickly than any other avian group within North America, possibly due in part to declines in nesting success. In 2009-2010, I monitored nests of five songbird species in southwestern Saskatchewan. Two 300-m² plots were located in each of 12 pastures, three of which were ungrazed controls. The remaining pastures had stocking rates ranging from 0.23 – 0.83 AUM/ha, which were grazed for 2-3 or >15 years. Stocking rate affected nest site selection by three species, suggesting that some pastures have a greater availability of nest sites than others. Logistic exposure nesting success models suggested a nonlinear effect of stocking rate on nesting success of Sprague’s Pipit in 2009. The nesting success of two species was negatively correlated with grazing duration in 2009 and 2010, respectively. To encompass the different habitat needs of each species, I suggest maintaining rangeland landscapes with a range of grazing treatments.
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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 | 0.001 | 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 | 0.000 | 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".