The comparative lake ecology of two allopatric Arctic Charr, <i>Salvelinus alpinus</i>, populations with differing life histories in Cumberland Sound, Nunavut
Bibliographic record
Abstract
The lake ecology of high-latitude fishes is strongly influenced by seasonal feeding opportunities and environmental stochasticity in Arctic environments. Arctic Charr (Salvelinus alpinus (Linnaeus, 1758)) populations are prevalent throughout the Arctic and show multiple life history strategies across their range. Unlike Old World populations, the lake ecology of Arctic Charr populations on south Baffin Island remains poorly defined. We examined the comparative seasonal lake ecology of two differing Arctic Charr populations (anadromous and landlocked) in Cumberland Sound, Nunavut. Anadromous Charr showed no evidence of feeding occurring within freshwater once they began seaward migrations. Anadromous Charr achieve sexual maturation at a larger size and younger age than landlocked Charr. Landlocked Charr used more lake habitats than anadromous Charr with feeding opportunities as an apparent influence on habitat selection. Landlocked Charr fed year round. They adopted a cannibalistic feeding strategy in the winter but consumed a variety of prey items in the fall. Littoral habitat was found to be important to all sizes of Charr in both seasons. Smaller anadromous Charr (<350 mm) did not use the benthic habitat. The variable ecology and form demonstrated further emphasizes the phenotypic adaptability of Arctic Charr that allows its widespread distribution in the Arctic.
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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 | 0.001 |
| 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".