Year-round monitoring at a Pacific coastal campus reveals similar winter and spring collision mortality and high vulnerability of the Varied Thrush
Bibliographic record
Abstract
Abstract Bird–window collisions are a leading cause of direct anthropogenic avian mortality, yet our state of knowledge regarding this threat relies heavily on eastern North American studies. Seasonal patterns of collision mortality may differ along the Pacific coast, and western North American species remain understudied. We therefore surveyed a stratified random sample of 8 buildings for collisions at the University of British Columbia, Vancouver, Canada over 45-day periods during 2 winters, 1 spring, 1 summer, and 1 fall season between January 22, 2015 and March 15, 2017. After accounting for the rate of scavenging and efficiency of observers in finding carcasses, we estimated that 360 collision fatalities (95% CI: 281–486) occurred over 225 days of collision monitoring. Collision mortality was highest in fall, but in contrast to most published research, collision mortality was intermediate in both winter and spring and was lowest in summer. In winter 2017, we performed point-count surveys to assess whether individual species are disproportionately vulnerable to collisions when accounting for population size and found that the Varied Thrush (Ixoreus naevius) was 76.9 times more likely to collide with buildings, relative to average species vulnerability in winter. To our knowledge, this is the first study to report the Varied Thrush as a species that is disproportionately vulnerable to collisions. Further studies are needed to assess the vulnerability of Western North American species and subspecies, and to determine whether similar patterns of seasonal collision mortality are found elsewhere.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".