Phylogeography, postglacial gene flow, and population history of North American Northern Goshawks (<i>Accipiter gentilis</i>)
Bibliographic record
Abstract
Climate cycling during the Quaternary played a critical role in the diversification of avian lineages in North America, greatly influencing the genetic characteristics of contemporary populations. To test the hypothesis that North American Northern Goshawks (Accipitergentilis) were historically isolated within multiple Late Pleistocene refugia, we assessed diversity and population genetic structure as well as migration rates and signatures of historical demography using mitochondrial control-region data. On the basis of sampling from 24 locales, we found that Northern Goshawks were genetically structured across a large portion of their North American range. Long-term population stability, combined with strong genetic differentiation, suggests that Northern Goshawks were historically isolated within at least three refugial populations representing two regions: the Pacific (CascadesSierra-Vancouver Island) and the Southwest (Colorado Plateau and Jemez Mountains). By contrast, populations experiencing significant growth were located in the Southeast Alaska-British Columbia, Arizona Sky Islands, Rocky Mountains, Great Lakes, and Appalachian bioregions. In the case of Southeast Alaska-British Columbia, Arizona Sky Islands, and Rocky Mountains, Northern Goshawks likely colonized these regions from surrounding refugia. The near fixation for several endemic haplotypes in the Arizona Sky Island Northern Goshawks (A. g apache) suggests long-term isolation subsequent to colonization. Likewise, Great Lakes and Appalachian Northern Goshawks differed significantly in haplotype frequencies from most Western Northern Goshawks, which suggests that they, too, experienced long-term isolation prior to a more recent recolonization of eastern U.S. forests.
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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) | 0.000 | 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".