Signatures of vicariance, postglacial dispersal and spawning philopatry: population genetics of the walleye<i>Sander vitreus</i>
Bibliographic record
Abstract
Population genetic relationships reveal the signatures of current processes such as reproductive behaviour and migration, as well as historic events including vicariance and climate change. We analyse population structure of native walleye Sander vitreus across North America, encompassing 10 nuclear DNA microsatellite loci, 26 spawning sites and 921 samples from watersheds across the Great Lakes, Lake Winnipeg, upper Mississippi River, Ohio River and Mobile Bay of the Gulf Coast. Geographical patterning is assessed using phylogenetic trees, pairwise F(ST) analogues, hierarchical partitioning, Mantel regression, Bayesian assignment and Monmonier geographical networks. Results reveal congruent divergences among population groups, corresponding to historic isolation in glacial refugia, dispersal patterns and basin divisions. Broad-scale relationships show genetic isolation with geographical distance, but reproductive groups within basins do not -- with some having pronounced differences. Greatest divergence distinguishes outlying Gulf Coastal and northwest populations, the latter tracing to dispersal from the Missourian refugium to former glacial Lake Agassiz, and basin isolation approximately 7000 ya. Genetic barriers in the Great Lakes separate groups in Lakes Superior, Huron's Georgian Bay, Erie and Ontario, reflecting contributions from Mississippian and Atlantic refugia, and changes in connectivity patterns. Walleye genetic patterns thus reflect vicariance among watersheds and glacial refugia, followed by re-colonization pathways and changing drainage connections that established modern-day northern populations, whose separations are maintained through spawning site fidelity. Conservation management practices should preserve genetic identity and unique characters among these divergent walleye populations.
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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".