Mitochondrial DNA Phylogeography of Black Bears (<i>Ursus americanus</i>) in Central and Southern North America: Conservation Implications
Bibliographic record
Abstract
The American black bear (Ursus americanus) experienced a significant range contraction during the 19th and 20th centuries due to a variety of anthropogenic factors. Although previous molecular studies of black bears provided insight into historic and contemporary forces shaping phylogeographic patterns, none included black bears from the central part of the species distribution. Understanding the historical aspects of the connectivity and genetic differentiation of black bears in this region is important for proper management and conservation programs, but this understanding is confounded by poorly documented translocation efforts and population expansion. To address these issues, we generated mitochondrial DNA sequence data for 409 black bears from 15 populations in North America. Two sampling localities (Manitoba, Canada, and Minnesota) were source populations for translocation into western Arkansas and Louisiana. Major conclusions from our study include: black bears in western Arkansas were affected genetically by the translocation program; eastern Oklahoma has been repopulated by westward expansion of bears from Arkansas with a mixture of translocated bears and remnant individuals; black bears in Louisiana were not affected genetically by the translocation program; black bears in western Texas and northern Mexico dispersed there from the southeastern United States; and bears in White River National Wildlife Refuge (eastern Arkansas) share closer genetic affinities with U. a. luteolus than they do with the widespread U. a. americanus.
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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 | 0.001 |
| 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".