Genetic and phenotypic population structure of invasive sea lamprey, Petromyzon marinus, in the Laurentian Great Lakes and Finger Lakes
Bibliographic record
Abstract
Sea lamprey, Petromyzon marinus, are an invasive species in the Laurentian Great Lakes and Finger Lakes. The parasitic feeding stage is particularly damaging to the lakes’ ecosystem as sea lamprey wound and kill environmentally and economically important fish such as lake trout, Salvelinus namaycush. Since the sea lamprey invasion in the late 1800s significant resources are directed towards the control of sea lamprey using tools such as chemical treatment of larvae and trapping of the spawning adults. Understanding population structure is essential for framing a more effective sea lamprey control program. Studies using microsatellite loci have found genetic differentiation between sea lamprey from the upper and lower Great Lakes, and body size variation has been documented across the lakes, but fine-scale genetic population structure has not been studied. We use whole genome resequencing of 9-20 individuals from each of 15 sites (238 individuals) across the Great Lakes and Finger Lakes (Cayuga and Seneca), and body measurements of 9-36 individuals from each site (472 individuals), to identify population structure among and within the lakes. Genomic analyses showed structure between Lake Ontario, the Finger Lakes, and the other Great Lakes, and body size partially differentiated the lakes. Using high-resolution data to delineate spatial population structure will be important for sea lamprey control because management is most efficiently targeted when the geography of demographically independent populations is well-characterized.
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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".