Effects of Native and Non‐Native Grassland Plant Communities on Breeding Passerine Birds: Implications for Restoration of Northwest Bunchgrass Prairie
Bibliographic record
Abstract
Abstract One common problem encountered when restoring grasslands is the prominence of non‐native plant species. It is unclear what effect non‐native plants have on habitat quality of grassland passerines, which are among the most imperiled groups of birds. In 2004 and 2005, we compared patterns of avian reproduction and the mechanisms that might influence those patterns across a gradient of 13 grasslands in the Zumwalt Prairie in northeastern Oregon that vary in the degree of non‐native plant cover (0.9–53.4%). We monitored the fate of 201 nests of all the breeding species in these pastures and found no association of percent non‐native cover with nest densities, clutch size, productivity, nest survival, and nestling size. Regardless of the degree of non‐native cover, birds primarily fed on Coleoptera, Orthoptera, and Araneae. But as percent non‐native cover in the pastures increased, Orthoptera made up a greater proportion of diet and Coleoptera made up a smaller proportion. These diet switches were not the result of changes in terrestrial invertebrate abundance but may be related to decreases in percent bare ground associated with increasing cover of non‐native vegetation. Measures of nest crypticity were not associated with cover of non‐native vegetation, suggesting that predation risk may not increase with increased cover of non‐native vegetation. Thus, the study results show that increased non‐native cover is not associated with reduced food supplies or increased predation risk for nesting birds, supporting the growing body of evidence that grasslands with a mix of native and non‐native vegetation can provide suitable habitat for native grassland breeding birds.
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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 | 0.001 | 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".