Effects of Progressive Clearcut Logging on Newfoundland Caribou
Bibliographic record
Abstract
Abstract: Logging has often been implicated in the decline of caribou ( Rangifer tarandus ), but its effects are incompletely understood. We used a distance‐based approach to assess the effects of progressive clearcut logging on the summer (28 May to 15 Sep) range of caribou in Newfoundland, Canada. We compared distances of random locations and of caribou, from 9 years of radiotelemetry, to landcover types across 3 spatial scales: population range, individual ranges, and radiolocations. We tested for incremental avoidance of cutovers and mature softwood forests, the preferred type for caribou and forest harvesting, while controlling for the confounding effects of each. At the individual range, females selected for hardwood and softwood forests, bogs, and barrens, and they avoided open water. Patterns for males were similar, although they avoided bogs and barrens at both scales. The sexes differed in their response to forest harvesting. Females progressively avoided cutovers, both pre‐ and postharvest, likely due to their spatial proximity. Females maintained an average of 9.2 km from active cutovers. Cutover avoidance was evident even if we controlled statistically for distances to other habitats, and it accounted for heightened disuse of softwood forests. Compared with females, males occurred in proximity, with no incremental response to clearcutting. These results imply deleterious effects of timber harvesting on female caribou. Long‐term investigations will enhance our capacity to evaluate such anthropogenic habitat changes.
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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 | 0.000 |
| 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".