Evidence That Sea Lamprey Control Led to Recovery of the Burbot Population in Lake Erie
Bibliographic record
Abstract
Abstract Between 1987 and 2003, the abundance of burbot Lota lota in eastern Lake Erie increased significantly, especially in Ontario waters. We considered four hypotheses to explain this increase: (1) reduced competition with lake trout Salvelinus namaycush , the other major coldwater piscivore in Lake Erie; (2) increased abundance of the two main prey species, rainbow smelt Osmerus mordax and round goby Neogobius melanostomus ; (3) reduced interference with burbot reproduction by alewives Alosa pseudoharengus ; and (4) reduced predation by sea lampreys Petromyzon marinus on burbot. Species abundance data did not support the first three hypotheses. Our results suggested that the apparent recovery of the burbot population of Lake Erie was driven by effective sea lamprey control. Sea lamprey predation appeared to be the common factor affecting burbot abundance in Lakes Michigan, Huron, Erie, and Ontario. In addition, relatively high alewife density probably depressed burbot abundance in Lakes Ontario and Michigan. We propose that a healthy adult lake trout population may augment burbot recovery in some lakes by serving as a buffer against sea lamprey predation and will not negatively impact burbot through competition.
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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 | 0.000 | 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) | 0.002 | 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".