Feeding habits and trophic niche overlap between sympatric golden jackal (<i>Canis aureus</i>) and red fox (<i>Vulpes vulpes</i>) in the Pannonian ecoregion (Hungary)
Bibliographic record
Abstract
The feeding ecology of the golden jackal ( Canis aureus L., 1758) and its interspecific trophic relationship with the sympatric red fox (Vulpes vulpes (L., 1758)) was investigated in an area of recent range expansion of the golden jackal in Hungary, central Europe. Diet composition was determined by scat analysis (over 4 years: jackal 814 scats; fox 894 scats). Compared with jackals, foxes consumed more small mammals (mean biomass consumed: jackal 77%; fox 68%) and to a lesser extent plant matter (6% and 18%, respectively). The importance of other prey, such as wild boar ( Sus scrofa L., 1758), cervids, brown hare ( Lepus europaeus Pallas, 1778), birds, reptiles, fish, invertebrates, and domestic animals, was minimal. Both mesocarnivores consumed primarily small animals (<50 g: 92% and 87%, respectively); this implies a typical searching and solitary hunting strategy. The trophic niche breadth of both species was very narrow and the fox proved to be more of a generalist. The food overlap index between the two canids was high (mean, 73%) and varied with the decreasing availability and consumption of small mammals. Based on prey remains found in scats, small-mammal specialization over a 2-year period and seasonal predation upon wild boar piglets (mainly by the jackal), seasonal fruit eating (mainly by the fox), and scavenging on wild or domestic ungulates (both predators) were found.
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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".