Lake Whitefish Diet, Condition, and Energy Density in Lake Champlain and the Lower Four Great Lakes following Dreissenid Invasions
Bibliographic record
Abstract
Abstract Lake Whitefish Coregonus clupeaformis support some of the most valuable commercial freshwater fisheries in North America. Recent growth and condition decreases in Lake Whitefish populations in the Great Lakes have been attributed to the invasion of the dreissenid mussels, zebra mussels Dreissena polymorpha and quagga mussels D. bugensis, and the subsequent collapse of the amphipod, Diporeia, a once-abundant high energy prey source. Since 1993, Lake Champlain has also experienced the invasion and proliferation of zebra mussels, but in contrast to the Great Lakes, Diporeia were not historically abundant. We compared the diet, condition, and energy density of Lake Whitefish from Lake Champlain after the dreissenid mussel invasion to values for those of Lake Whitefish from Lakes Michigan, Huron, Erie, and Ontario. Lake Whitefish were collected using gill nets and bottom trawls, and their diets were quantified seasonally. Condition was estimated using Fulton's condition factor (K) and by determining energy density. In contrast to Lake Whitefish from some of the Great Lakes, those from Lake Champlain Lake Whitefish did not show a dietary shift towards dreissenid mussels, but instead fed primarily on fish eggs in spring, Mysis diluviana in summer, and gastropods and sphaeriids in fall and winter. Along with these dietary differences, the condition and energy density of Lake Whitefish from Lake Champlain were high compared with those of Lake Whitefish from Lakes Michigan, Huron, and Ontario after the dreissenid invasion, and were similar to Lake Whitefish from Lake Erie; fish from Lakes Michigan, Huron, and Ontario consumed dreissenids, whereas fish from Lake Erie did not. Our comparisons of Lake Whitefish populations in Lake Champlain to those in the Great Lakes indicate that diet and condition of Lake Champlain Lake Whitefish were not negatively affected by the dreissenid mussel invasion.
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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 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".