Evidence of host switching: Sea lampreys disproportionately attack Chinook salmon when lake trout abundance is low in Lake Ontario
Bibliographic record
Abstract
Lake trout (Salvelinus namaycush) is the presumed preferred host of the invasive sea lamprey (Petromyzon marinus) in the Great Lakes, but little is understood about this preference outside of laboratory experiments. By preference we mean sea lamprey attacks on hosts are disproportionate to host relative abundance. The purpose of this study was to quantify host preference of sea lampreys in the field for the first time. We focused our analysis on Lake Ontario, where the two dominant host species for sea lampreys are lake trout and Chinook salmon (Oncorhynchus tshawytscha). Sea lampreys exhibited a strong preference for lake trout when host abundance was ≥ 32% lake trout, but sea lamprey preference switched to Chinook salmon when host abundance was ≤ 13% lake trout. Model results were equivocal with respect to determining whether the primary predictor of sea lamprey preference was relative or absolute abundance of lake trout. Other evidence, particularly the different spatial distributions of the two hosts, suggests that sea lamprey preference for lake trout is based on a higher encounter probability, driven by absolute abundance of lake trout. This study confirms a widely held concern that observed sea lamprey-induced marking rates on lake trout, used to assess the status of sea lamprey control in the Great Lakes, can be influenced by the abundance of alternative hosts. As an alternative host for sea lamprey parasitism, Chinook salmon may contribute to the persistence of lake trout in Lake Ontario.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".