Lake whitefish and walleye population responses to dreissenid mussel invasion in eastern Lake Ontario
Bibliographic record
Abstract
We reviewed responses associated with the invasion of dreissenid mussels by two eastern Lake Ontario fish populations and the fisheries they support. Resurging lake whitefish and walleye populations declined following dreissenid mussel invasion in the early 1990s. Impacts on whitefish were associated with the loss of a key diet item, Diporeia, and its replacement with diet items of lower energy value. Impacts featured a die-off, dispersal, declines in juvenile and adult condition and growth rates, delayed age-at-maturity, and several years of reproductive failure. Impacts on walleye were consistent with dreissenid driven ecosystem change, particularly, clearer water. The key response by the walleye population was a downward shift in recruitment levels. This shift appears to be due to a change in the stock-recruitment relationship caused by decreased survival during early life (i.e. egg to 4-months), and suggests that the carrying capacity for these early life stages has diminished. Currently, whitefish reproduction has resumed and walleye reproduction appears stabilized at a lower level. Recent (i.e. 2003 and 2005) whitefish year-classes were relatively large but the fish are growing slowly and annual survival rate is not yet known. The whitefish commercial harvest continues to decline in synchrony with the declining adult whitefish population. The walleye recreational fishery (i.e. effort and harvest) has stabilized at a smaller size consistent with lower walleye year-class strength.
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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 | 0.002 |
| 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) | 0.001 | 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".