Patterns of dietary niche breadth and overlap are maintained for two closely related carnivores across broad geographic scales
Bibliographic record
Abstract
Ecological studies investigating niche breadth and overlap often have limited spatial and temporal scale, preventing generalizations across varying environments and communities. For example, it is not clear whether species having restricted diets maintain such patterns relative to closely related species and across their geographic range of co-occurrence. We used stable isotope analysis of hair and fur samples collected from four regions of sympatry for Canada lynx (Lynx canadensis) and bobcat (Lynx rufus) spanning southern Canada and the northern United States, to test the prediction that the more generalist species (bobcat) exhibits a wider dietary niche than the more specialist species (Canada lynx) and that this pattern is consistent across different regions. We further predicted that Canada lynx diet would consistently exhibit greater overlap with that of bobcat compared to overlap of bobcat diet with Canada lynx. We found that Canada lynx had a narrower dietary niche than bobcat, with a high probability of overlap (85–95%) with bobcat, whereas the bobcat dietary niche had up to a 50% probability of overlap with Canada lynx. These patterns of dietary niche breadth and overlap were consistent across geographic regions despite some regional variation in diet breadth and position, for both species. Such consistent patterns could reflect a lack of plasticity in species dietary niches. Given the increasingly recognized importance of understanding dietary niche breadth and overlap across large spatial scales, further research is needed to investigate the mechanisms by which broad-scale patterns are maintained across species and systems.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".