Genetic structure of raccoons in eastern North America based on mtDNA: implications for subspecies designation and rabies disease dynamics
Bibliographic record
Abstract
Subspecific designations are useful for wildlife management when they represent real barriers to gene flow. In this study, we assess genetic partitioning of mitochondrial DNA control region variation to determine if the structuring is congruent with morphologically defined subspecies of the common raccoon (Procyon lotor (L., 1758)). Mitochondrial control region sequences were analyzed within and among four subspecies ( Procyon lotor elucus Bangs, 1898, Procyon lotor lotor (L., 1758), Procyon lotor hirtus Nelson and Goldman, 1930, and Procyon lotor varius Nelson and Goldman, 1930) that occur along the eastern seaboard of North America through to the central United States. This identified 76 haplotypes, 59 of which were specific to one of the four ranges, while only 1 haplotype was wide-spread. Phylogenetic analysis revealed three distinct lineages: one found primarily in Florida, one along the eastern seaboard, and the third predominantly to the west of the Mississippi River. These lineages likely diverged during the Pleistocene, as a result of rising sea levels creating barriers to gene flow. The range of P. l. elucus is still primarily one lineage supporting the subspecific designation; however, there is considerable lineage mixing across the ranges of P. l. hirtus, P. l. lotor, and P. l. varius, suggesting that they be synonymized to P. l. lotor. While some of these subspecies designations are not supported, we have found that landscape attributes affect gene flow, which can be of use in informing rabies management.
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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".