Diet reveals potential for competition and coexistence among coyotes (<i>Canis latrans</i>), red foxes (<i>Vulpes vulpes</i>), and gray foxes (<i>Urocyon cinereoargenteus</i>)
Bibliographic record
Abstract
Species can alleviate competition by reducing diet overlap. Non-native coyotes (Canis latrans Say, 1823) and historically native gray foxes (Urocyon cinereoargenteus (Schreber, 1775)) have expanded their ranges and may compete with native red foxes (Vulpes vulpes (Linnaeus, 1758)). To examine potential competition among canids in Maine, USA, we compared δ13C and δ15N from muscle and hair samples to assess relative resource use, and we compared frequency of occurrence of prey items from stomach contents to assess diets. For these species, red foxes consumed anthropogenically based foods the most in fall and early winter, gray foxes consumed anthropogenically based foods the most in summer, and coyotes consumed anthropogenically based foods the least in all seasons. Coyotes held the highest relative trophic position in fall and early winter, red foxes held the highest relative trophic position in summer, and gray foxes held the lowest relative trophic position. Based on stomach contents, gray foxes had the broadest diet and consumed the most plants, and coyotes had the narrowest diet. Red foxes were the only species to show isotopic niche overlap with both potential competitors across seasons. Thus, they may be most susceptible to competitive exclusion among these canids, with implications for community dynamics as ranges shift due to human activity.
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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 | 0.000 |
| 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".