Landscape Influence on <em>Canis</em> Morphological and Ecological Variation in a Coyote-Wolf <em>C. lupus</em> × <em>latrans</em> Hybrid Zone, Southeastern Ontario
Bibliographic record
Abstract
The ecology of Coyote-Wolf (Canis latrans × C. lupus) hybrids has never fully been typified. We studied morphological and ecological variation in Canis within a region of Coyote-Wolf hybridization in southeastern Ontario. We assessed Canis morphology from standard body measurements and ten skull measurements of adult specimens and found that Canis in this region are morphologically intermediate between Algonquin Provincial Park Wolves (C. lupus lycaon) and Coyotes, indicating a latrans × lycaon hybrid origin; however, there is a closer morphological affinity to latrans than lycaon. Analysis of 846 scats indicated dietary habits also intermediate between lycaon and Coyotes. We used a geographic information system (GIS) to assess spatial landscape features (road density, land cover and fragmentation) for six study sites representing three landscape types. We found noticeable variation in Canis morphology and diet in different landscape types. In general, canids from landscape type A (lowest road density, more total forest cover, less fragmentation) displayed more Wolf-like body morphology and consumed a greater proportion of larger prey (Beaver [Castor canadensis] and White-tailed Deer [Odocoileus virginianus]). In comparison, canids from landscape types B and C (higher road density and/or less total forest cover, more fragmentation) were generally more Coyote-like in body and skull morphology and made greater use of medium to small-sized prey (Groundhog [Marmota monax], Muskrat [Ondatra zibethicus] and lagomorphs). These landscape trends in Canis types suggest selection against Wolf-like traits in fragmented forests with high road density. The range of lycaon southeast of Algonquin Provincial Park appears to be limited primarily due to human access and consequent exploitation. We suggest that road density is the best landscape indicator of Canis types in this region of sympatric, hybridizing and unprotected Canis populations.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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".