Caribou encounters with wolves increase near roads and trails: a time‐to‐event approach
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Summary 1. Caribou and reindeer Rangifer tarandus are declining across North America and Scandinavia in part from wolf Canis lupus ‐mediated apparent competition with more abundant ungulate prey species. While caribou generally persist in areas with low wolf density, wolf packs that overlap caribou ranges could trigger caribou declines. Moreover, anthropogenic linear features such as roads, trails and seismic lines are hypothesized to increase predation risk for caribou, yet few studies have examined the mechanistic effects of linear features or spatial overlap on wolf–caribou encounter rates and predation risk. 2. We used (a) time‐to‐event models of wolf–caribou encounters estimated from concurrent global positioning system (GPS) radio‐collar data from wolves and caribou and (b) wolf resource selection models of travel locations, to determine the potential influence of wolf–caribou spatial overlap, linear features, elevation and season on encounter rates. Analyses were based on data from 35 adult female caribou and 37 male and female wolves from 11 wolf packs from Banff and Jasper National Parks, Canada, from 2002 until 2010. 3. Wolf–caribou encounter rates increased with high wolf–caribou overlap, proximity to linear features and lower elevations. Wolves strongly selected low elevations, especially during winter and spring. Selection for linear features as travel routes increased with elevation. 4. Caribou risk of encounter was highest during the summer and autumn when wolves spent the most time at high elevations. Most wolf‐caused mortalities ( n = 12) occurred during spring and summer. 5. Synthesis and applications . The presence of anthropogenic linear features and the amount of time wolves spend in caribou range could be equally as important as wolf density when prioritizing caribou recovery actions such as wolf or primary prey reductions or re‐introductions. The use of GPS locations and time‐to‐event modelling offers a powerful tool for evaluating factors affecting predation risk of threatened and endangered species.
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.
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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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