Ontogenetic niche shifts and resource partitioning of lake trout morphotypes
Bibliographic record
Abstract
Resource polymorphisms are widely observed in fishes; however, ontogenetic contributions to morphological and ecological differences are poorly understood. This study examined whether ontogenetic changes in niche partitioning could explain morphological and buoyancy differences between lake trout ( Salvelinus namaycush ) morphotypes in Great Slave Lake (Northwest Territories, Canada). Morphometric analysis, buoyancy, capture depth, diet, and stable isotope data were used in concert to determine whether (i) differences occur in small, as well as large, lake trout, (ii) ontogenetic changes in morphology and buoyancy correlate with shifts in depth or diet, and (iii) a subset of small trout, putatively identified as “humpers”, are distinct from other morphotypes. Ontogenetic changes in lake trout morphology were associated with an ecological shift between benthic and pelagic feeding. Resource partitioning between lean and siscowet-like trout occurred within benthic (small trout) and pelagic (large trout) habitats. The humper subset did not differ from small siscowet-like trout. By combining multiple methods and an ontogenetic perspective, our study provides novel perspectives on resource polymorphisms in large, deep lakes and on existing interpretations of stable isotope data from large lakes in general.
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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 | 0.000 | 0.001 |
| 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".