Songbird abundance in native and planted grassland varies with type and amount of grassland in the surrounding landscape
Bibliographic record
Abstract
Abstract Agriculture and wildlife conservation programs have converted vast amounts of cropland into grasslands planted with exotic species. Understanding how landscape context influences avian use of native and planted grasslands is essential for developing effective conservation strategies in agricultural landscapes. Our primary objective was to determine the extent to which the amount and type of grassland in the surrounding landscape influences the abundance of grassland songbird species on native and planted grassland parcels in southern Saskatchewan and Alberta, Canada. Bird abundance was more strongly influenced by the amount and type of grassland within 400 m of breeding parcels than at larger spatial scales. Grassland specialists responded similarly to habitat and landscape type over both years and provinces. Sprague's pipit ( Anthus spragueii ) and Baird's sparrow ( Ammodramus bairdii ) were most common in native grassland parcels surrounded by native grassland and were more likely to occur in planted grasslands surrounded by native grassland. Bobolinks ( Dolichonyx oryzivorus ) were most common in planted grassland parcels, but their abundance increased with the amount of native grassland surrounding these parcels. Our findings indicate that the suitability of planted grasslands for these species is influenced by their proximity to native grassland. Grassland generalists showed mixed responses to habitat and landscape type over the 2 years (Le Conte's sparrow [ Ammodramus leconteii ]) and between provinces (Savannah sparrow [ Passerculus sandwichensis ] and western meadowlark [ Sturnella neglecta ]). Management to benefit grassland specialists should therefore consider the landscape context when seeding cultivated land to non‐native grassland and conserve extant native grassland. © 2013 The Wildlife Society.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".