Regional predatory fish diets following a regime shift in Lake Huron
Bibliographic record
Abstract
Over the past 20 years, Lake Huron’s ecosystem has undergone an unprecedented amount of change, including a reduction in offshore productivity, prey fish collapse, and transformation of the benthic food web. Yet, little is known about how these changes affected the diet of key fish species. In this study, we used 18,543 stomach samples collected between 2004 and 2019 to characterize the diet of five key species: lake trout (Salvelinus namaycush), lake whitefish (Coregonus clupeaformis), chinook salmon (Oncorhynchus tshawytscha), rainbow trout (Oncorhynchus mykiss), and walleye (Sander vitreus), from the Ontario waters of Lake Huron including the North Channel, Georgian Bay and the main basin. Specifically, we described regional diets using an index of relative importance and diet biomass proportions, and we determined the Schoener diet overlap index between the five predators. We found that invasive species dominated the diets of the predators. Lake whitefish diets were dominated by dreissenid mussels in the southern main basin and by round goby (Neogobius melanostomus) in the central main basin. Chinook salmon had a very uniform diet of rainbow smelt (Osmerus mordax) and coregonines, contributing to the high levels of diet overlap with lake trout, especially in the North Channel. Our study demonstrates that while invasive species are pervasive in the diets of predatory fish lake-wide, there remains a significant degree of regional variation that needs to be taken into account when considering food web effects of the recent ecosystem changes and when devising management strategies aimed at balancing predator and prey populations.
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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 | 0.000 |
| Science and technology studies | 0.001 | 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".