Contrasting life-history characteristics between riverine and lacustrine anadromous Arctic char (Salvelinus alpinus) in the western Canadian Arctic
Bibliographic record
Abstract
Freshwater habitat characteristics are known to affect life-history traits of migratory salmonids. Although the life cycle of the anadromous form of Arctic char (Salvelinus alpinus) is typically associated with lakes, there is a small number of anadromous populations in North America that spawn, rear, and overwinter exclusively in rivers. The life-history traits of these relatively understudied populations and how they differ from lacustrine Arctic char are poorly documented. We characterized life-history tradeoffs expressed by anadromous Arctic char originating from a riverine (Hornaday River) and a relatively nearby lacustrine system (Tatik Lake of the Kuujjua River) in the western Canadian Arctic using a 10 year dataset. The riverine population attained smaller average size (600 mm vs. 628 mm, fork length) and age (7.7 vs. 10.6 years), had a lower longevity (14 vs. 26 years), expressed a 44% higher growth rate resulting in larger size-at-age prior to reaching modelled length asymptote (700 vs. 754 mm), had a younger modal age-at-maturity (~6-7 vs. ~11-13 years) and mean age-at-first migration (4.1 vs. 6.4 years), and a higher natural mortality rate (0.31 vs. 0.21 per year). Our results broaden knowledge on the spectrum of life-history strategies exhibited by anadromous Arctic char and underscore how freshwater habitat influence vital rates and life-history tradeoffs, which have implications for conservation and sustainable harvest of salmonids.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".