Boreal bird abundance estimates within different energy sector disturbances vary with point count radius
Bibliographic record
Abstract
Responses of boreal birds to changes in forest structure and composition caused by construction of well pads, seismic lines, and pipelines are poorly understood. Bird species associated with older forests are predicted to experience larger population declines with increased disturbance compared with species associated with younger or open habitats; however, point count methods may influence apparent outcomes because the proportional area of disturbed vegetation and the magnitude, uncertainty, and detection of a disturbance response by birds vary as a function of sampling area. We analyzed point count data from 12 energy sector studies and measured how disturbance type and point count radius interacted to affect 531 impact ratios (mean abundance at point counts centered within disturbances relative to abundance at point counts within forest 150–400 m from the nearest edge bordering those disturbances [59 species*3 disturbance types*3 point count radii]). We observed larger disturbance effects (impact ratios) within larger-radius point counts at well pads (100-m and unlimited-distance) and pipelines (unlimited-distance) compared with 50-m point counts at seismic lines, and within 50-m point counts at well pads relative to 50-m point counts at seismic lines. Effect uncertainty was higher at well pads and pipelines than seismic lines, and lower within larger-radius point counts. The probability of detecting a disturbance response was greater for larger-radius point counts at pipelines than for 50-m point counts at seismic lines, and within 50-m point counts at well pads relative to 50-m point counts at seismic lines. On average, a species was more likely to increase in abundance near an energy sector disturbance if the species was not associated with older (>75 yr) forest stages. While the effects of disturbance varied by species and with disturbance type, the effects of pipelines and seismic lines were better detected by larger-radius point counts, while the effects of well pads were better detected by smaller-radius point counts.
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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 | 0.001 | 0.005 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".