The trophic niche of sculpins <i>Cottus</i> spp. in forage fish assemblages of boreal lakes
Bibliographic record
Abstract
Abstract We compared the trophic niches of freshwater sculpins Cottus spp. with those of other co‐habiting forage fishes in two groups of boreal lakes with distinct habitats and fish communities. Near North Lakes (45° 00′ to 47° 30′ N) were deeper, stratified and contained lake trout Salvelinus namaycush as the apex piscivore, whereas Far North Lakes (51° 10′ to 52° 20′ N) were shallower, did not stratify and contained pike Esox lucius and walleye Sander vitreus as the apex piscivores. Trophic niches of sculpins and other forage fishes were compared based on niche metrics calculated from muscle stable carbon (δ13C) and nitrogen (δ15N) isotope ratios. In Near North Lakes, sculpins were found almost exclusively in deep, offshore waters and their niche positions reflected a greater reliance on pelagic production (lower δ13C) and a higher trophic elevation (higher δ15N) compared with most other forage fishes. Furthermore, sculpins in Near North Lakes tended to have larger trophic niches (occupied greater area in δ13C– δ15N space), particularly in the food chain (δ15N) dimension, than other cohabiting forage fishes. In contrast, sculpins in Far North Lakes were commonly found in the nearshore and had trophic niche positions and sizes that were similar to those of the other cohabiting forage fishes. This study illustrates the flexibility in the realised trophic niches of sculpins in relation to habitat availability and fish community composition in boreal lakes.
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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 | 0.000 |
| 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".