Wildlife overpass structure size, distribution, effectiveness, and adherence to expert design recommendations
Bibliographic record
Abstract
It is now well evidenced that wildlife crossing structures paired with exclusion fencing reduce wildlife vehicles collisions while facilitating wildlife connectivity across roadways. Managing animal mortality and subpopulation connectivity is crucial to successful species and landscape stewardship. Highway mitigation projects are large economic investments that remain on the landscape for many decades. Governments and planning agents thus strive to balance cost and benefit to build cost-effective structures with the greatest positive impact on local wildlife and motorists. Ideal dimensions of overpasses and underpasses vary by species, but scientists generally suggest that overpasses for large mammals should be approximately 50 m wide. Optimal width also depends on structure length, with longer structures requiring additional width. Accordingly, experts have suggested a width to length ratio of 0.8. We sought to assess how these recommendations manifested in practice-where agencies use this information to design and build structures while also balancing cost and logistical challenges-and the degree to which built structures conform to current recommendations. We identified 120 wildlife overpasses across the world that were constructed to reduce the negative impacts of roads. Using a novel measurement technique, we analyzed the dimensions of these 120 overpasses located in North America, Europe, Asia, and Oceania. The average width of the wildlife overpasses was 34 m. Most wildlife overpasses located in North America and Europe did not meet their respective dimensional expert guidelines. We investigate reasons explaining the non-compliance and provide recommendations for future overpass designs. Building on previous evidence showing that wider overpasses have increased crossing rates, we examined crossing rates for multiple large mammal species across 12 overpasses located in western North America. We qualitatively observed that wider North American overpasses (40-60 m), in or near compliance with expert guidelines, were associated with a more diverse set of species use and had nearly twice the average crossing rates when compared to non-compliant, narrow North American overpasses. In reviewing various studies from around the world, we conclude that wide overpasses (~50 m) continue to present ecologically sound and cost-effective solutions for decreasing the barrier of roadways, especially when targeting width-sensitive species and large assemblages of mammals. Future studies, however, are encouraged to further explore the specific instances when underpasses and narrower overpasses present more cost-effective ecological solutions, or how these structures can complement wide overpasses in successful wildlife crossing systems.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 | 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) | 0.006 | 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 teacher head, 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".