Spatial variability of lake trout diets in Lakes Huron and Michigan revealed by stomach content and fatty acid profiles
Bibliographic record
Abstract
Despite long-term efforts to restore lake trout (Salvelinus namaycush) populations in the Great Lakes, they continue to experience insufficient recruitment and rely on hatchery programs to sustain stocks. As lake trout reproductive success has been linked to diets, spatial heterogeneity in diet compositions is of interest. To assess spatial components of adult lake trout diets, we analyzed stomach contents and fatty acid profiles of dorsal muscle collected throughout Lake Michigan and along Lake Huron’s Michigan shoreline. Lake trout from Lake Huron were generally larger in both length and mass than those from Lake Michigan. However, lake trout from Lake Michigan varied more in size based on depth of capture with smaller fish being caught more in deeper set nets. Fatty acids and stomach contents indicated that alewife (Alosa pseudoharengus) were consumed more in western Lake Michigan in contrast with round goby (Neogobius melanostomus) along the eastern shoreline. Conversely, in Lake Huron, lake trout primarily consumed rainbow smelt (Osmerus mordax). These results indicate that diet compositions of lake trout populations are relatively plastic and offer new insights into within-basin heterogeneity of Great Lakes food webs.
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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 | 0.000 | 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) | 0.001 | 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".