Behavioral responses of migratory caribou to semi-permeable roads in Arctic Alaska
Bibliographic record
Abstract
Migration conveys many benefits to species, ecosystems, and people but relies upon connected landscapes. Anthropogenic development can present barriers for migrants, but many barriers are semi-permeable, allowing unhindered or delayed passage. We used a modified version of the Barrier Behavior Analysis (BaBA) to investigate seasonal movement responses to five roads in northwestern Alaska by adult female Western Arctic Herd caribou (Rangifer tarandus) from 2009 to 2024. Our analyses revealed some altered movement in response to all focal roads. We found that the roads were semi-permeable barriers to movement, with altered behaviors including bouncing away, moving back-and-forth, and tracing along roads. Overall, 63.1% of collared animals encountered (entered a road-specific buffer) at least one focal road. Of these, 61.5% displayed altered movements. At the scale of individual encounters with roads, we found altered movement in 27.1% of road encounters. Most encounters occurred during fall migration and caribou with altered behavior spent an average of 9.4 days longer near focal roads than those with unaltered movement. Altered movements were balanced among the behavioral responses. Most altered movements occurred near the Red Dog mining road (60.3%) or during fall migration (51.9%) but lasted longest during winter (17.2 days on average). We confirm prior findings of altered fall movements near the Red Dog road and demonstrate that movement behavior is also altered around other roads and in other seasons. Nonetheless, many collared caribou did not display altered movements in response to roads, emphasizing the need for further research to understand the mechanistic drivers of caribou movement responses. Given increasing pressures for infrastructure development and global challenges facing migratory species, it is critical to identify mitigation measures and inform management decisions seeking to balance responsible development with conservation of natural systems, including migratory species and the people that rely upon them.
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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".