Managing Zone-of-Influence Impacts of Oil and Gas Activities on Terrestrial Wildlife and Habitats in British Columbia
Bibliographic record
Abstract
A “zone of influence” is the difference between an anthropogenic activity’s spatial footprint and the extent of the activity’s effects on surrounding habitat and wildlife. This article reviews studies that have measured zones of influence for site-level activities that are relevant to oil and gas activities in British Columbia in order to inform the development of policies and procedures to manage their effects on terrestrial habitats and wildlife. Creation of edges, as well as noise and activity associated with industrial sites and roads, are the major stressors that generate zones of influence. These stressors create cascading effects that can result in altered ecosystems through a variety of mechanisms. Stressors can create abiotic and floristic effects that generally extend < 100 m into surrounding intact habitat, but effects on wildlife can extend up to 5 km and sometimes farther. Mitigating stressors at their source should reduce zones of influence and the need to apply management buffers to separate industrial activities from ecological resources.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".