Grain spilled from moving trains create a substantial wildlife attractant in protected areas
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Transportation corridors can attract threatened wildlife via habitat enhancement and foraging opportunities, leading to collisions with vehicles. But wildlife may also be attracted to energy‐dense food products that are spilled or discarded from moving vehicles, which is rarely studied. Therefore, we quantified train‐spilled attractants in Banff and Yoho National Parks, Canada, where agricultural products (hereafter, grain) are transported along 134 km of railway and may contribute to wildlife mortality. We measured grain deposition from 2012 to 2015 at 19 sites and assessed the performance of three structures developed to measure spilled grain. We then modeled grain deposition with respect to four types of spatial and temporal variables: those related to grain shipment, physical habitat characteristic, train‐related characteristics and variables specific to the study site. Grain was spilled at a mean rate of 1.64 g m −2 day −1 ( sd = 3.60) from April to October ( n = 3 years) and 1.52 ( sd = 2.37) from November to March ( n = 1 year). Extrapolating annual deposition across the study area yielded enough grain (110 tons) to provide 4.77 × 10 8 kcal of gross energy, which is equivalent to the average annual caloric needs of 42–54 grizzly bears Ursus arctos horribilis ; the regional population is estimated at 50–73 animals. Much of this energy will not be accessible or available to bears; however, their attraction to it could contribute to rising and unsustainable rates of mortality. Models explained 9–31% of the variance in deposition for each grain type, primarily via coarse temporal variables of shipping rates and month. The absence of more specific predictive variables suggests that mitigation should target broader policies, such as prompt reporting and repair of leaky hopper cars, and limits to train stoppage in protected areas. We encourage more global assessment of the under‐studied issue of food attractants spilled by vehicles along transportation corridors.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 it