PHYLOGEOGRAPHY OF CANADA GEESE (BRANTA CANADENSIS) IN WESTERN NORTH AMERICA
Bibliographic record
Abstract
Abstract Using molecular genetic markers that differ in mode of inheritance and rate of evolution, we examined levels and partitioning of genetic variation for seven nominal subspecies (11 breeding populations) of Canada Geese (Branta canadensis) in western North America. Gene trees constructed from mtDNA control region sequence data show that subspecies of Canada Geese do not have distinct mtDNA. Large and small-bodied forms of Canada Geese were highly diverged (0.077 average sequence divergence) and represent monophyletic groups. A majority (65%) of 20 haplotypes resolved were observed in single breeding locales. However, within both large and small-bodied forms certain haplotypes occurred across multiple subspecies. Population trees for both nuclear (microsatellites) and mitochondrial markers were generally concordant and provide resolution of population and subspecific relationships indicating incomplete lineage sorting. All populations and subspecies were genetically diverged, but to varying degrees. Analyses of molecular variance, nested-clade and coalescencebased analyses of mtDNA suggest that both historical (past fragmentation) and contemporary forces have been important in shaping current spatial genetic distributions. Gene flow appears to be ongoing though at different rates, even among currently recognized subspecies. The efficacy of current subspecific taxonomy is discussed in light of hypothesized historical vicariance and current demographic trends of management and conservation concern.
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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 | 0.000 |
| 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 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".