Trophic ecology of juvenile lean and siscowet lake charr (<i>Salvelinus namaycush</i>) in Lake Superior: assessing for potential competition
Bibliographic record
Abstract
We investigated the spatial overlap, diet, isotopic niche, and growth of juvenile lean and siscowet lake charr ( Salvelinus namaycush) in Lake Superior to address concerns of potential competition with implications to the study of resource polymorphism. Catch data revealed the greatest levels of sympatry in waters from 40 to 60 m. Juvenile lean and siscowet diet changed ontogenetically with Mysis being the dominant prey item for the smallest lake charr but differentiating with onset of piscivory. As ecotypes increased in size, lean diets became dominated by pelagic prey, whereas siscowets had equal proportions of benthic and pelagic prey. Isotopic niche overlap declined between ecotypes coincident with siscowet lake charr shifting to deeper habitats around 400 mm. Lean and siscowet exhibited different growth trajectories. However, length at age-4 declined in parallel for both ecotypes with no trend in condition suggesting that lake charr growth is sensitive to prey biomass and unlikely related to competition. Our findings indicate minimal evidence of competition and support the concept that multiple sympatric ecotypes of lake charr in Lake Superior are maintained by resource polymorphism.
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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 | 0.000 | 0.000 |
| 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".