Effects of narrow linear clearings on movement and habitat use in a boreal forest mammal community during winter
Bibliographic record
Abstract
Linear clearings for human activities cause internal fragmentation of otherwise intact native forest, with many potential impacts on wildlife. Across a boreal forest region of some 4,000 km 2 , we investigated how movements and habitat use of ecologically different mammal species are affected by narrow (about eight m) seismic line (SL) clearings associated with fossil fuel extraction, which form extensive networks many kilometers long. We conducted nine repeat snow track surveys during three winters at 14 pairs of one-kilometer transects, each comprising one transect along the SL and a second running perpendicular into adjacent forest. Data for 13 individually-analyzed mammal taxa (species or sets of closely related species) and five mammal groups, categorized based on body size-diet combinations, showed that movements across transects were either unaffected by SL clearings (relative to continuous forest) or restricted only slightly. However, these clearings were favored for linear travel by most species and body size-diet groups (excepting small mammals). The strength of this preference varied in a manner consistent with species’ differing needs to move long distances (associated with their energetic requirements): large predators > large herbivores > mid-sized predators > mid-sized herbivores > small mammals. In terms of overall habitat use, large-bodied predators (e.g., wolves and coyotes) strongly selected SL clearings over forest, medium-sized predators (e.g., mustelids) and medium-sized herbivores (e.g., hares and squirrels) preferred forest, and neither large herbivores nor small mammals had a clear habitat preference. Consequently, there was a net shift in both species and trophic composition within the SL, in favor of large predators and away from medium-sized predators and herbivores. Given the high regional SL density (1.9 km/km 2 ) such shifts are likely to have complex ecological consequences, of currently unknown magnitude.
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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 | 0.001 |
| 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 | 0.001 |
| 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".