Impacts of oil well drilling noise on parental care and nestling condition of chestnut-collared longspurs (Calcarius ornatus)
Bibliographic record
Abstract
Grassland songbird populations are in steep decline across North America, largely due to habitat loss. Oil and gas infrastructure and its associated noise are one of several factors impacting the remaining grasslands. Oil well operating noise affects the breeding behavior of several bird species, but the effects of drilling noise are less understood. Drilling noise occurs at a louder amplitude than chronic operating noise and is more unpredictable, which may affect songbirds to a greater extent. Chestnut-collared longspurs (Calcarius ornatus) are a species at risk in Canada and are dependent on mixed-grass prairie, much of which is impacted by oil and gas development. To determine the effects of oil well drilling noise on chestnut-collared longspur parental behavior, I created an experimental noise system and deployed cameras on 63 chestnut-collared longspur nests between 2019 and 2021 in southern Alberta. I reviewed and recorded parental behavior across over 800 hours of nest videos. I also measured the brood mass and the age at fledge at each nest to determine the effects of drilling well noise and parental care on nestling condition. Chestnut-collared longspur males provided less care near drilling noise, while female care was unaffected. Additionally, the infrastructure itself may have provided preferable foraging opportunities as parental care was higher closer to infrastructure. Nestling condition was not impacted by changes in paternal care, but surprisingly, more female care was associated with lower brood mass and a younger age at fledge. Drilling noise, independent of parental care, was associated with lower brood mass and an older age at fledge close to the infrastructure. My results suggest that the impacts of drilling noise on nestlings is not due to the effects of noise on parental care, even though paternal care is affected by drilling noise. Changes in both brood mass and the age at fledge have an impact on fledgling survival in songbirds and may affect population recruitment in chestnut-collared longspurs. Therefore, it is important to consider management strategies such as erecting temporary sound barriers or postponing drilling during peak breeding season to reduce the effects of drilling noise on chestnut-collared longspurs.
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 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".