Factors affecting the permeability of transportation and riparian corridors to the movements of songbirds in an urban landscape
Bibliographic record
Abstract
Summary 1. Linear features associated with transportation and riparian corridors are known to inhibit the mobility of birds and other wildlife, yet the factors contributing to their barrier effects are poorly understood. The diversity of roads in urban landscapes provides an opportunity for elucidating the relative importance of factors such as noise, traffic volume, gap width and adjacent vegetation on animal movement. 2. Using an avian mobbing call as a lure, we tested the willingness of forest songbirds to cross four types of linear features in the urban landscape of Calgary, Alberta, Canada: (1) roads of varying widths and traffic volumes, (2) conventional railways and light transit lines, (3) transportation bridges across riparian corridors, and (4) rivers. 3. Using mixed effects logistic regression, we found that the size of the gap in vegetation was the most important determinant of movement (P < 0·001). As the gap in vegetation exceeded 30 m, the likelihood of movement decreased dramatically and by 45 m, birds were only half as likely to move across gaps as they were to move an equivalent distance in continuous tree cover. Traffic volume also had a significant dampening effect on movement (odds ratio = 0·952 per 1000 vehicle per day increase; P < 0·001) and generally explained more variation in the data than noise levels. 4. Railroads proved to be the most permeable of the features we tested, probably owing to their relatively narrow width, which never exceeded 30 m. Surprisingly, rivers were less permeable than the anthropogenic linear features we tested, with a significant barrier effect evident even at widths <50 m. 5. The birds in our study showed a marked preference for flying over, rather than under, transportation bridges, particularly when adjacent vegetation was available. 6. Synthesis and applications. Our results suggest that linear features, both anthropogenic and natural, can significantly impede the movements of forest songbirds and that managing adjacent vegetation is a potentially effective way to mitigate these barrier effects in cities and other fragmented landscapes.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 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".