Dietary breadth and overlap among five sympatric prairie carnivores
Bibliographic record
Abstract
Abstract Ecological communities are shaped, in part, by the manner in which similar species consume and partition food resources. To better understand the structure of a mammalian carnivore community from a prairie habitat in central North America, we determined the dietary breadth and overlap of sympatric American badgers Taxidea taxus, coyotes Canis latrans, red foxes Vulpes vulpes, raccoons Procyon lotor and striped skunks Mephitis mephitis, via stomach content analysis of 411 carcasses salvaged as part of a predator control program in southern Saskatchewan, Canada (2000–2001). Carnivores consumed a total of 25 separate food items; for all species except raccoons, the majority of stomachs contained mammals, whereas other foods such as amphibians, bird remains and insects were also recovered. Raccoon stomachs tended to contain wheat seed, eggshells and birds. Dietary breadth varied among the five carnivore species, being narrowest for raccoons and widest for skunks. Overall, dietary overlap tended to be highest for species pairings associated with the highest level of presumed niche similarity, which included raccoon–skunk and coyote–fox dyads. Yet, levels of dietary overlap exhibited notable interannual variability for most species pairings. The assessment of a larger assemblage of carnivores within a North American prairie community shows that marked interspecific and temporal variation in dietary breadth and overlap may characterize a guild of sympatric species occupying similar habitat.
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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".