Diversity in selection patterns of five grassland songbirds in dry-mixed grasslands of Alberta
Bibliographic record
Abstract
Declining grassland bird populations across North America continue to be a concern. Understanding local relationships between grassland bird abundance and vegetative and landscape characteristics will enable more prescriptive recommendations to be made to land managers. We used point count survey data collected by the MULTISAR (Multiple Species At Risk) program along with field measurements of habitat and landscape characteristics on 15 ranches in the Dry Mixed-grass Subregion in southern Alberta to improve our understandings of habitat relationships for five grassland bird species: Baird’s Sparrow (Centronyx bairdii), Sprague’s Pipit (Anthus spragueii), Thick-billed Longspur (Rhynchophanes mccownii), Chestnut-collared Longspur (Calcarius ornatus), and Grasshopper Sparrow (Ammodramus savannarum). We used generalized linear mixed models to examine the relationship between the predicted abundance of a species and covariates that represented vegetative structure (e.g., litter), management (e.g., range health), and anthropogenic features (e.g., energy development) of habitat site selection. Model results demonstrate four vegetation structure covariates were of most importance for predicting abundance, including litter, vegetation height, bare soil, and shrub cover. Quadratic relationships were found with litter amounts for the predicted abundance of Baird’s Sparrow, Chestnut-collared Longspur, and Grasshopper Sparrow. Contrastingly, higher amounts of litter reduced the predicted abundance of Thick-billed Longspur. The relationship of vegetation height was quadratic for Sprague’s Pipit and was positive for Baird’s Sparrow, but negative for Thick-billed Longspur. As bare soil percentage increased, the predicted abundance of Baird’s Sparrow and Chestnut-collared Longspur decreased, with Sprague’s Pipit showing a quadratic association. Negative relationships were found with increased amounts of shrub cover for Chestnut-collared Longspur, Sprague’s Pipit, and Thick-billed Longspur. Our results help to further understand individual grassland bird species’ habitat requirements, enabling us to provide land management recommendations for maintaining, improving, or creating the heterogenic environments needed for a variety of grassland birds in the Dry Mixed-grass Subregion.
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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 | 0.001 | 0.001 |
| 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".