Evidence That Lake Trout Served as a Buffer against Sea Lamprey Predation on Burbot in Lake Erie
Bibliographic record
Abstract
Abstract The population of burbot Lota lota in Lake Erie recovered during 1986–2003, mainly because of the control of sea lamprey Petromyzon marinus, which began in 1986. Burbot populations continued to grow during 1996–1998, when sea lamprey control was substantially reduced. We calculated mortality parameters for burbot in Lake Erie by estimating age at capture for 2,793 burbot caught in annual gill-net surveys of eastern Lake Erie from 1994 to 2003. Based on catch-curve analysis, annual mortality in Lake Erie during 1994–2003 was estimated as 33%. Annual mortality of the 1992 year-class of burbot was estimated as 30%. The mortality of burbot during the years of reduced sea lamprey control was not different from that during the 3 years preceding reduced control and was significantly lower than that during the entire portion of the time series in which full sea lamprey control was conducted. These results suggest that the reduction in sea lamprey control did not lead to increased burbot mortality. The catch per gill-net lift of large burbot (total length > 600 mm), the size preferred by sea lampreys, was lower than that of adult lake trout Salvelinus namaycush (age 5 and older; total length > 700 mm) before lampricide application was reduced. Although adult lake trout populations declined, the abundance of large burbot did not change during the period of reduced lampricide application. These results support a hypothesis that a healthy population of adult lake trout can serve as a buffer species, acting to reduce predation of burbot by sea lampreys when sea lamprey populations increase. Burbot attained sexual maturity at a relatively early age (3 or 4 years) and a total length (approximately 500 mm) that was smaller than the preferred prey size for sea lampreys. These characteristics and the buffering effect of the lake trout population enabled growth of the burbot population during the brief period when lamprey control was reduced.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".