A protected area influences genotype-specific survival and the structure of a Canis hybrid zone
Bibliographic record
Abstract
It is widely recognized that protected areas can strongly influence ecological systems and that hybridization is an important conservation issue. However, previous studies have not explicitly considered the influence of protected areas on hybridization dynamics. Eastern wolves are a species of special concern and their distribution is largely restricted to a protected population in Algonquin Provincial Park (APP), Ontario, Canada, where they are the numerically dominant canid. We studied intrinsic and extrinsic factors influencing survival and cause-specific mortality of hybrid and parental canids in the three-species hybrid zone between eastern wolves, eastern coyotes, and gray wolves in and adjacent to APP. Mortality risk for eastern wolves in areas adjacent to APP was significantly higher than for other sympatric Canis types outside of APP, and for eastern wolves and other canids within APP. Outside of APP, the annual mortality rate of all canids by harvest (24%) was higher than for other causes of death (4–7%). Furthermore, eastern wolves (hazard ratio ¼ 3.5) and nonresidents (transients and dispersing animals, hazard ratio ¼ 2.7) were more likely to die from harvest relative to other Canis types and residents, respectively. Thus, eastern wolves dispersing from APP were especially vulnerable to harvest mortality. For residents, eastern wolf survival was more negatively influenced by increased road density than for other Canis types, further highlighting the sensitivity of eastern wolves to human disturbance. A cycle of dispersal from APP followed by high rates of mortality and hybridization appears to maintain eastern wolves at low density adjacent to APP, limiting the potential for expansion beyond the protected area. However, high survival and numerical dominance of eastern wolves within APP suggest that protected areas can allow rare hybridizing species to persist even if their demographic performance is compromised and barriers to hybridization are largely absent in the adjacent matrix.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".