Effects of intermittent noise from oil well infrastructure on abundance and nesting success of grassland songbirds
Bibliographic record
Abstract
Grassland songbirds are particularly sensitive to noise pollution due to their reliance on acoustic communication, and they have experienced greater population declines than any other group in North America. The development of energy extraction, and the presence of its associated chronic and intermittent noise pollution, can exacerbate the pre-existing effects of habitat loss, fragmentation, and disturbance already being experienced in that ecosystem. This study aimed to compare the impacts of chronic and intermittent noise associated with energy extraction activities on the abundance, nesting success, and nestling body condition of grassland songbirds. I predicted that grassland songbirds evaluated in this study would have lower abundances, decreased nesting success, and lower nestling body conditions when exposed to intermittent noise compared to chronic noise, due to the distracted prey hypothesis. I experimentally exposed grassland songbirds to chronic and intermittent extraction playbacks in the mixed-grass prairies of southern Alberta. Chestnut-collared longspurs (Calcarius ornatus), endemic to the Great Plains and a Species at Risk, and Savannah sparrows (Passerculus sandwichensis) showed avoidance of all playback types and loud drilling playbacks, respectively, and no other species experienced specific changes to abundance due to intermittent or chronic noise. The nesting success of either species, and chestnut-collared longspur nestling body condition, was not impacted by any noise playback patterns. These results suggest that noise amplitude is a driver of noise avoidance patterns, rather than noise pattern, and that some species may be more sensitive than others and may exhibit responses differently depending on their life-history strategies. These results should be taken into consideration when making management decisions, as they indicate the importance of reducing noise amplitude and the distribution of noise disturbance in grasslands.
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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".