Behavior of Moose Relative to a Road Network
Bibliographic record
Abstract
Roads often negatively affect terrestrial wildlife, via habitat loss or fragmentation, noise, and direct mortality. We studied moose (Alces alces) behavior relative to a road network, in an area with a history of moose–vehicle accidents, to determine when moose were crossing roadways or using areas near roads and to investigate if environmental factors were involved in this behavior. We tracked 47 adult moose with Global Positioning System collars in a study area crossed by highways and forest roads. We hypothesized that moose would avoid crossing roads but would make occasional visits to roadsides to feed on sodium-rich vegetation and avoid biting insects. Further, we expected moose avoidance to be greater for highways than forest roads. We recorded 196,710 movement segments but only observed 328 highway and 1,172 forest-road crossings (16 and 10 times lower than expected by chance). Moose usually avoided road proximity up to ≥500 m on each side but 20% of collared moose made visits to areas within 50 m of highways, which might have resulted from moose searching for sodium in vegetation and roadside salt pools. In fact, vegetation along highways had higher sodium concentrations and was browsed in similar proportions to vegetation in adjacent forest, despite moose avoidance of these zones. Moose, however, did not use areas near roads more during periods of biting insect abundance. Our results supported the hypothesis of scale-dependent selection by moose; avoidance of highways at a coarse scale may confer long-term benefits, whereas selection of highway corridors at finer scales may be part of a strategy to overcome short-term limiting factors such as sodium deficiency. We found a positive relationship between home-range size and the proportion of road axes they contained, suggesting that moose either compensated for habitat loss or made specific movements along highways to gather sodium. The presence of sodium along highways likely increases moose–vehicle accident risks. Removal of salt pools or use of a de-icing salt other than sodium chloride should render highway surroundings less attractive to moose.
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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 | 0.000 | 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".