Panmixia and Limited Interspecific Introgression in Coyotes (Canis latrans) from West Virginia and Virginia, USA
Bibliographic record
Abstract
The expansion of coyotes (Canis latrans) into the eastern United States has had major consequences for ecological communities and wildlife managers. Despite this, there has been little investigation of the genetics of coyotes across much of this region, especially outside of the northeast. Understanding patterns of genetic structure and interspecific introgression would provide insights into the colonization history of the species, its response to the modern environment, and interactions with other canids. We examined the genetic characteristics of 121 coyotes from the mid-Atlantic states of West Virginia and Virginia by genotyping 17 polymorphic nuclear DNA microsatellite loci. These genotypes were compared with those from other canid populations to evaluate the extent of genetic introgression. We conducted spatial clustering analyses and spatial autocorrelation to assess genetic structure among sampled coyotes. Coyotes across the 2 states had high genetic diversity, and we found no evidence of genetic structure. Six to sixteen percent of individuals displayed some evidence of genetic introgression from other species depending on the method and criteria used, but the population possessed predominantly coyote ancestry. Our findings suggested introgression from other canid populations has played less of a role in shaping the genetic character of coyotes in these states compared with populations closer to the Canadian border. Coyotes appear to display a panmictic population structure despite high habitat heterogeneity and heavy human influence in the spatial environment, underscoring the adaptability of the species.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".