Community‐informed and codesigned research to understand the impacts of railways on wildlife
Bibliographic record
Abstract
Trains cause mortalities of several animal species, but the ecological impacts of railways are understudied. Most research on wildlife-train collisions has focused on large mammals, but understanding railway-specific risks for underrepresented taxa, especially vulnerable species, is important for developing effective mitigation strategies. Based on the concerns and interests of 2 Anishinaabek communities-Shawanaga First Nation (SFN) and Magnetawan First Nation (MFN)-we collaboratively aimed to fill knowledge gaps with a community-informed approach in which Indigenous knowledge (IK) and Western science were used to investigate wildlife interactions with railways bisecting the 2 Traditional Territories in Ontario, Canada. To inform study design, First Nation community members were invited to share knowledge concerning wildlife-railway impacts in semistructured interviews. Weekly walking surveys were conducted in 3 field seasons along two 3.6-km sections of railway in SFN and MFN during which locations of all wildlife observed alive or dead were recorded. We also deployed game cameras at 500-m intervals along the railway survey areas. On walking surveys, we recorded 462 observations of individuals from 42 species, of which 76% were found dead. These findings complemented the shared IK that railways affect a wide variety of wildlife, often causing mortalities. Reptiles and amphibians were the most severely affected taxa, accounting for 87% of observed mortalities. Seven species at risk of extinction interacted with the railway, including 3 turtle species and one snake species, all of which were found dead on the railway tracks. Cameras recorded 43 wildlife species; most detections were of large and medium mammals, suggesting they frequently interact with the railway but may face lower mortality risks than herpetofauna in our study area. Ultimately, our study highlights the holistic outcomes that are possible through collaborative research that embraces complementary knowledge systems and indicates that reptile and amphibian populations may be particularly susceptible to railway mortality.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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".