Reducing Moose???Vehicle Collisions through Salt Pool Removal and Displacement: An Agent-Based Modeling Approach
Bibliographic record
Abstract
"Between 1990 and 2002, more than 200 moose???vehicle collisions occurred each year in Quebec, including about 50/yr in the Laurentides Wildlife Reserve. One cause is the presence of roadside salt pools that attract moose near roads in the spring and summer. Using the computer simulation technique of agent-based modeling, this study investigated whether salt pool removal and displacement, i.e., a compensatory salt pool set up 100 to 1500 m away from the road shoulder, would reduce the number of moose???vehicle collisions. Moose road crossings were used as a proxy measure. A GPS telemetry data set consisting of approximately 200,000 locations of 47 moose over 2 yr in the Laurentides Wildlife Reserve was used as an empirical basis for the model. Twelve moose were selected from this data set and programmed in the model to forage and travel in the study area. Five parameters with an additional application of stochasticity were used to determine moose movement between forest polygons. These included food quality; cover quality, i.e., protection from predators and thermal stress; proximity to salt pools; proximity to water; and slope. There was a significant reduction in road crossings when either all or two thirds of the roadside salt pools were removed, with and/or without salt pool displacement. With 100% salt pool removal, the reduction was greater (49%) without compensatory salt pools than with them (18%). When two thirds of the salt pools were removed, the reduction was the same with and without compensatory salt pools (16%). Although moose???vehicle collisions are not a significant mortality factor for the moose population in the Laurentides Wildlife Reserve, in areas with higher road densities, hunting pressure, and/or predator densities it could mean the difference between a stable and a declining population, and salt pool removal could be part of a good mitigation plan to halt population declines. This model can be used, with improvements such as spatial memory of salt pool locations and the addition of a road avoidance behavior, to assess the effectiveness of mitigation measures intended to reduce moose???vehicle collisions."
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".