Functional and numerical responses of ovenbirds (<i>Seiurus aurocapilla</i>) to changing seismic exploration practices in Alberta’s boreal forest
Bibliographic record
Abstract
:Rapid development of energy reserves in the boreal forest of western Canada has raised concerns about the potential impacts of forest fragmentation caused by seismic lines. Seismic lines are narrow linear corridors cut by the energy sector to access remote areas. Traditionally, seismic lines were cut using a bulldozer and averaged about 8 m in width. In response to concerns about conventional seismic line impacts, some energy companies have turned to new “best practices” that use lower-impact techniques to reduce their footprint (2- to 3-m-wide lines). Crucial to assessing the efficacy of this change in seismic policy for maintenance of biodiversity is determining how conventional and low-impact seismic lines are perceived by wildlife. We assessed the functional and numerical response of male ovenbirds (Seiurus aurocapilla) to conventional and low-impact seismic lines in mature aspen forest in northeastern Alberta. Based on radio-telemetry, ovenbirds perceived conventional seismic lines as creating a gap in the forest and used it as a territory boundary. In contrast, ovenbirds incorporated low-impact seismic lines within their territories. Spot-mapping data suggested no differences in ovenbird density in stands with a single conventional seismic line, multiple low-impact lines, or reference plots with no seismic lines. Despite the lack of numerical response to any seismic practice, we believe it is prudent to recommend that energy companies consider using new low-impact approaches in their seismic operations to minimize the ecological risks of energy sector activity for forest birds.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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".