Food-niche overlap between arctic and red foxes
Bibliographic record
Abstract
Arctic foxes (Alopex lagopus) in Fennoscandia have retreated to higher altitudes on the mountain tundra, possibly because of increased competition with red foxes (Vulpes vulpes) at lower altitudes. In this study we compare summer food niches of the two species in mountain tundra habitat. Arctic foxes consumed lemmings more often than red foxes did, while red foxes consumed field voles and birds more often. Yet despite substantial variation in the diet of each species among summers, food-niche overlaps between the species were consistently high in most summers, as arctic and red foxes responded similarly to temporal changes in prey availability. Occurrences of field voles and birds in fox scats were negatively correlated with altitude, while the occurrences of lemmings tended to increase with altitude. Since arctic foxes bred at higher altitudes than red foxes, the differences between arctic and red fox diets were better explained by altitudinal segregation than by differences between their fundamental food niches. Arctic foxes should therefore endeavour to use the more productive hunting grounds at the lower altitudes of their former range, but interference competition with red foxes might decrease their access to these areas, and consequently cause a decrease in the size of in their realised niche.
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 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 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".