Oil Infrastructure has Greater Impact than Noise on Stress and Habitat Selection in Three Grassland Songbirds
Bibliographic record
Abstract
Oil extraction may impact wildlife by altering habitat suitability and affecting stress levels and behavior of individuals, but it can be challenging to disentangle the impacts of infrastructure itself on wildlife from associated noise and human activity at well sites. We evaluated whether the demographic distribution and corticosterone levels of three grassland passerine species (Chestnut-collared Longspur, Calcarius ornatus; Baird's Sparrow, Centronyx bairdii; and Savannah Sparrow Passerculus sandwichensis) were impacted by oil development in southern Alberta, Canada. We used a landscape-scale oil well noise-playback experiment to evaluate whether impacts of wells were caused by noise. Surprisingly, higher-quality female Chestnut-collared Longspurs tended to nest closer to oil wells, while higher-quality Savannah Sparrows generally avoided nesting sites impacted by oil wells. Corticosterone levels in all species varied with the presence of oil development (oil wells, noise, or roads), but the magnitude and direction of the response was species and stimulus specific. While we detected numerous impacts of physical infrastructure on stress physiology and spatial demographic patterns, few of these resulted from noise. However, all three species in this study responded to at least one disturbance associated with oil development, so to conserve the grassland songbird community, both the presence of physical infrastructure and anthropogenic noise should be mitigated.
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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 | 0.000 | 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".